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Advice on making the most of basketball three-point shot data.

George Minoso 2024-05-21T13:46:56-05:00 May 17th, 2024 | General , Research , Sports Management |

Authors: George Terhanian1

Corresponding Author:

George Terhanian, PhD 200 Hoover Avenue, #2101 Las Vegas NV, 89101 [email protected] 646-430-3420

1 George Terhanian founded Electric Insights after holding executive positions at The NPD Group, Toluna, and Harris Interactive. He has also served on boards or advisory groups for several organizations, including the US National Academy of Sciences, the Advertising Research Foundation, and the British Polling Society. He is known for conceiving how to make survey data, including pre-election forecasts, more accurate through statistical matching methods.

Making the most of basketball three-point shot data

This study’s primary goal is to help National Basketball Association (NBA) and other basketball teams worldwide increase their three-point shooting accuracy and decrease their opponents’, a key to winning more games.  A related goal is to explain how a combination of good data, logistic regression analysis, likely effects reporting in probabilities or percentage points, and self-serve simulation can improve communication among data analysts, basketball coaches, and players, and enhance each group’s effectiveness.  Logistic regression analysis of 32,511 NBA three-point shots shows six factors affect the three-point shooting percentage: closest defender’s distance to the shooter, time left on the 24-second shot clock, whether the player shot after dribbling or catching the ball, game period, shot distance, and venue.  In the past, data analysts conveyed the results of such analyses to coaches and players using terms such as regression, logits, and odds.  Some NBA executives say doing so again would be disastrous.  An alternative is to emphasize probabilities and percentages in communication and create self-serve simulators coaches and players can use to predict how changes in critical factors affect three-point shooting percentages.  NBA and other teams worldwide can apply this approach to new and existing datasets they maintain, enhance, and build.

Key Words : self-serve simulation, predicted probabilities, logistic regression, likely effects reporting, psychotherapy

INTRODUCTION

The National Basketball Association (NBA) releases specific three-point shot characteristics, such as shooter name and shot distance.  Aside from the 2014-15 season’s first 903 of 1,230 games (and 2015-16’s first 631, though the latter data are no longer publicly available), the released data exclude a variety of individual shot characteristics such as the closest defender’s distance to the shooter, a crucial defensive effectiveness measure (14).  Teams are said to consider the excluded characteristics proprietary.  As Mike Zarren, assistant general manager and chief legal counsel for the NBA’s Boston Celtics, explained, “You can’t share stuff with other teams…We are not at an equilibrium point where all the teams know what everyone else is doing.  There are some advantages that some teams have over others” (15) (51:47). 

The analyses here use the 2014-15 shot dataset, the last and largest single-season one containing full shot data that is publicly available.  The main goal is to help NBA and other basketball teams worldwide increase their three-point shooting accuracy and decrease their opponents’.  Teams that do so should win more games.  A related goal is to explain how a combination of good data, logistic regression analysis, likely effects reporting in probabilities or percentage points (e.g., “Shooting off the catch rather than the dribble is associated with a two-percentage-point increase in our three-point shot make percentage.”), and self-serve simulation can improve communication among data analysts, basketball coaches, and players, and enhance each group’s effectiveness.  NBA and other teams worldwide can apply this approach to new and existing datasets they maintain, enhance, and build.  Aspects of the approach are also portable to many other issues and areas where the key outcome variable is binary (26).

This paper has seven additional sections (excluding references and other ancillary information).  The first summarizes basic rules and strategies for NBA basketball, highlighting the importance of the three-point shot.  It also explains why data analysts seeking to communicate effectively with coaches and players should consider using non-technical language.  The second section describes the three-point shot data used in this paper’s analyses.  It then provides the rationale for relying on logistic regression analysis for model building and prediction.  The third section reports the results of the analyses and suggests how data analysts might share them with coaches and players.  It also explores why academic researchers tend not to report likely effects in probabilities or percentage points.  The fourth details how data analysts can build self-serve simulators that report likely effects in probabilities or percentage points.  The limitations of this paper’s analyses are discussed in the fifth section.  The next-to-last section describes how teams might apply the approach described here, while the final section provides concluding remarks.

NBA Basketball: Basic Rules and Strategies

NBA games have two teams with five players competing for four 12-minute periods (excluding possible five-minute overtime periods).  To score, a team needs to shoot the ball through the basket.  With the clock running, a successful shot is worth three or two points, depending on the shooter’s distance from the basket.  The clock stops for free throws, which are uncontested 15-foot shots worth a single point awarded for specific infringements.  One can calculate each shot’s expected value (EV) by multiplying its potential value by its average make percentage.  For the 2022-23 regular season, the expected value of a three- and two-point shot was almost identical: 1.08 points (3*.36) for a three-pointer and 1.10 (2*.55) for a two-pointer.  Each free throw’s expected value was .78 points (1*.78) or 1.56 for a more typical pair (3).  A recent example shows why the expected value measure can be strategically important.

In the second round of the 2020-21 playoffs, the Atlanta Hawks shocked the heavily favored Philadelphia 76ers, coming from behind to win the seven-game series four to three.  The Hawks’ decision to foul Ben Simmons repeatedly to force him to shoot free throws contributed to the victory.  As Hall-of-Fame player Earvin “Magic” Johnson observed, “…it fueled the Hawks’ comeback” (13).

Simmons shot just 33% (15 for 45) from the free-throw line for the series, far below his 61% (and the league’s 77%) regular season average.  Simmons’s 33% figure suggests the Hawks expected him to score only .66 points for two free throws in a series in which his team made 40% of its three-pointers (for an expected value of 1.22 points) and 52% of its two-pointers (for a 1.05 expected value).  That means the Hawks expected to gain .56 points (1.22 – .66) for a replaced three-point shot and .39 points (1.05 – .66) for a replaced two-pointer with the foul Simmons strategy.  Perhaps more notably, it may have affected Simmons’s decision-making.  To his team’s detriment, Simmons chose not to attempt an open lay-up or dunk with 3:30 remaining in game seven (4), arguably for fear of getting fouled and having to shoot free throws (21, 27).

Overstating three-point shooting’s significance is difficult.  In 2022-23, the Toronto Raptors, Charlotte Hornets, and Houston Rockets won 41, 27, and 21 (of 82) regular season games, too few to qualify for the post-season playoffs; their three-point shooting percentages of 34%, 33%, and 33% were the league’s worst.  The Philadelphia 76ers, Golden State Warriors, and Los Angeles Clippers won 54, 44, and 44 games, enough to compete in the playoffs; they were top performers in three-point shooting at 39%, 39%, and 38%.  These data and separate multi-season analyses (18, 20) suggest that winning in the NBA hinges heavily on making (and defending) three-point shots. 

Clear Communication  

An excellent statistical model is “a simplified version of reality, like a street map that shows you how to travel from one part of a city to another” (28) (p. ix).  But that map will not help you find your way if it includes esoteric terms or unfamiliar signs or symbols.  Likewise, if data analysts use uncommon language when giving advice, coaches and players may feel lost.  Mike Zarren would agree.  If Celtics’ data analysts were to apply logistic regression to three-point shot data, he would tell them to communicate what they learn “without using the word regression because that’s a disaster” (15) (11:18).  Terms like logits, standard deviations, odds, odds ratios, and z scores also would be off-limits.  Zarren does not believe coaches and players are unintelligent.  Even good data analysts can find aspects of logistic regression challenging.  That is why DeMaris (7) (p. 1,057) observed, “…there is still considerable confusion about the interpretation of logistic regression results.”  And why Gelman and Hill (11) (p. 83) commented, “…the concept of odds can be difficult to understand, and odds ratios are even more obscure.”

Washington Wizards’ assistant coach Dean Oliver’s views on clear communication resemble Zarren’s.  “When I directed quantitative analysis for the Denver Nuggets and would prepare stuff for coaches,” he said, “there were actually very few numbers in there.  It was usually words because it was easier for them to absorb…” (15) (48:54). 

An alternative to avoiding numbers is to report key predictor variables’ likely effects with familiar ones like probabilities and percentages—the NBA reports various descriptive statistics and cross-tabulations on its website, emphasizing percentages, hence coaches’ and players’ familiarity. 

The NBA has used technology to gather detailed player performance data since the 2013-14 season via SportVU, then Second Spectrum.  The analyses here use SportVU data, described as “real-time and innovative statistics based on speed, distance, player separation, and ball possession for comprehensive analysis of players and teams” (25).  How did the SportVU system work?  In each arena’s rafters, six cameras recorded information throughout each game in .04-second intervals, producing 25 images per second.  A computer algorithm then plotted the locations of the ball, basket, and 10 players.  SportVU delivered data and reports to each team and the league as a last step.

As noted earlier, the NBA made available SportVU raw, shot-level data—including the defender distance variable—for three-quarters of the 2014-15 regular season.  (The NBA also made available raw, shot-level data early in the 2015-16 season before discontinuing the practice entirely in January 2016.  The latter dataset is no longer publicly available.)  The 2014-15 dataset (17)—the last and largest single-season one publicly available—contains 21 variables and 128,069 three- and two-point shots, as described in the Appendix.  After making minor changes (e.g., removing two-point shots), the remaining three-point shots totaled 32,511—11,426 makes and 21,085 misses—taken from October 28, 2014, through March 4, 2015.

Analysis Method  

Logistic regression models the relationship between a binary outcome (e.g., made or missed three-point shots, or nearly anything with a yes or no interpretation) and, typically, several predictor or explanatory variables.  It is ideal for identifying and estimating the effects of actions to increase or decrease the size or proportion of the group of interest, specifically, made three-point shots.  It can also predict each three-point shot’s probability of belonging to the “made” rather than the “missed” group.  Many academic researchers consider it “the standard way to model binary outcomes” (11) (p. 79), “dominating all other methods in both the social and biomedical sciences” (2) (para. 1).

RESULTS The final logistic regression model comprises one dependent and six predictor variables.  The predictor variables were selected based on their relationship with the dependent variable, one another, theory, availability, and their effect on the model’s predictive accuracy.  Below are descriptions of the seven variables and brief explanations for how they may differ from the original ones described in the Appendix.

• ShotResult: The dependent variable: whether the shooter made the shot. (Values: 0=Missed, 1=Made; Original variable: Fgm)
• DefDist: The closest defender’s distance to the shooter in feet (ft.). Basketball players and coaches recommended a four-category variable after discussions and preliminary analyses. (Values: 1=0-3 ft., 2=3-6 ft., 3=6-9 ft., 4=9+ ft.; Original variable: Close_Def_Dist)
• ShotClock: The number of seconds (secs.) on the 24-second shot clock. Analyses showed steep drops in the make probability at the 4- and 2-second marks, thus the decision to create a variable with three categories. (Values: 1=0-2 secs., 2=2-4 secs., 3=4+ secs; Original variable: Shot_Clock)
• Catch: Whether the shooter took the shot off the catch or dribble. The original variable reported the number of dribbles the shooter took before shooting. Basketball players and coaches recommended a two-category variable after discussions and preliminary analyses. (Values: 1=Off Catch, 2=Off Dribble; Original variable: Dribbles)
• Period: The game period when the shot was taken, with fourth period and overtime shots pooled because of their similar make percentages. (Values: 1=1, 2=2, 3=3, 4=4+; Original variable: Period)
• ShotDist: The distance in feet from the center of the basket to the shooter. Basketball players and coaches recommended a four-category variable after discussions and preliminary analyses. (Values: 1=22-24 ft., 2=24-25 ft., 3=25-26 ft., 4=26+ ft.; Original variable: Shot_Dist)
• Venue: Whether it was a home or away game for the shooter’s team. (Values: 0=Away, 1=Home; Original variable: Location)

Table 1 reports the logistic regression analysis results, notably, standard information such as logit coefficients, odds, z scores, and a measure of statistical significance (i.e., p>z).  It also reports useful non-standard information such as frequencies, (predicted) probabilities, and expected values.  The rationale for reporting standard and non-standard information, to borrow from the statistician Frederick Mosteller, is to “let weaknesses from one…be buttressed by strength from another” (16) (Ch. 4, p. 116), a concept he referred to as “balancing biases.”  As envisioned, data analysts can rely on standard information when building and evaluating logistic regression models, and non-standard when communicating the results and their implications to coaches and players.

Results of final logistic regression analysis

Note . n=32,511.  Log pseudolikelihood, starting value: -21,078.18; final value: -20,827.69.  Likelihood ratio (degrees of freedom=13): 498.44, p > chi 2 = 0.00. Tjur R 2 : 0.014; McFadden R 2 : 0.012.  Stukel chi 2 (1) = 4.10, p > chi 2 = 0.043

Standard versus Non-Standard Interpretations

Table 1 shows that the defender distance variable (DefDist) affects the outcome variable.  A standard interpretation would emphasize odds ratios and statistical significance:

Controlling for other variables’ effects, three-point shots taken with the closest defender 9+ feet away have a:

• 60% higher odds (i.e., 1.6/1) of going in than those taken with the closest defender 0-3 feet away,
• 24% higher odds (i.e., 1.6/1.29) than those with the defender 3-6 feet away, and
• 10% higher odds (i.e., 1.6/1.46) than those with the defender 6-9 feet away.

Each effect is statistically significant, as their z scores show.

Although the standard interpretation is correct from a technical standpoint, coaches and players may not understand or act on it, given Zarren’s and Oliver’s comments (as well as those of DeMaris, Gelman, and Hill).  Now consider a non-standard interpretation (that relies on Table 1’s non-standard information).  Note that each percentage’s associated expected value is in parentheses.

All else unchanged, the percentage of three-point makes would decrease from 35% (1.05 pts.) to:

• 29% (0.86 pts.) with the defender always 0-3 feet away from the shooter, and
• 34% (1.02 pts.) with the defender always 3-6 feet away.

It would increase from 35% to:

• 37% (1.11 pts.) with the defender always 6-9 feet away, and
• 39% (1.17 pts.) with the defender always 9+ feet away.

NBA coaches and players would probably prefer the non-standard interpretation.  Arguably, reporting the likely effect in percentage points instead of odds is more intuitive and actionable (26, 30). 

Calculating Each Shot’s Make Probability

Another number to note in Table 1 is the constant of -1.46 logits which translates to a predicted make probability of 19% (0.56 pts.).  The -1.46 number represents a three-point shot with the lowest value on each predictor variable:

• Defender 0-3 feet away
• 0-2 seconds on the shot clock
• Off the catch
• First period
• Shot distance of 22-24 feet

An implication is that it is possible to calculate the predicted make probability of each of the 32,511 shots.  Such information can spark curiosity and foster improved performance for a player scrutinizing his own (or opponents’) shot data.  For example, Row 1 of Table 2 reports the logit coefficients associated with the first three-point shot Klay Thompson of the Golden State Warriors attempted in 2014-15.  In the third period of an away game versus the Sacramento Kings with 4.6 seconds on the shot clock, Thompson missed from 22 feet off the catch with the defender 3.9 feet away.  As the column titled Prob shows, that shot’s predicted make probability was 38% (.38*100), calculated by applying the following formula to select Table 2 numbers: exp (sum of logit coefficients + constant)/ (exp (sum of logit coefficients + constant) +1).

Upon closer examination, Thompson could have asked the team’s data analysts how that shot’s make probability would have changed had the defender been 9+ rather than 3.9 feet away.  To respond, an analyst could have replaced the DefDist logit coefficient of 0.25 with 0.47, the one corresponding to a 9+ feet value.  As shown in Row 2, the make probability would have risen to 42%, a four-percentage-point increase or likely effect. 

Thompson next might have asked how shooting off the dribble rather than the catch would have affected the 42% probability.  After replacing the Catch logit coefficient of 0 with-0.09, an analyst could have reported that the probability would have dropped to 39%, as Row 3 of the Prob column shows. 

Thompson, an excellent shooter, would probably work to improve specific aspects of his shooting if he had such data for all his three-point shots (31).

Simulating the effect of changes on a single shot’s make probability  

Predicting the Likely Effect of Multiple Changes to Multiple Predictor Variables

Coaches thinking more broadly might focus on all 32,511 shots and ask analysts to predict the likely effect of multiple changes to the values of multiple predictor variables. Building on the Thompson example, analysts could approach the task by conceptualizing changes as scenarios.  Below, and graphically in Figure 1, are three illustrative ones.

Scenario 1 . Players take all 32,511 three-point shots with the defender 9+ ft. away.  

Prediction: 39% of all three-pointers will go in, an increase of four percentage points compared to the 35% baseline, translating to 1,297 more makes and 12,723 total ones.

Scenario 2 . Players take all 32,511 three-point shots:

• with the defender 9+ feet away 
• from 22-24 ft. away from the basket

Prediction: 42% of all shots will go in, a three-percentage-point gain vs. Scenario 1.  This translates to 808 more makes and 13,531 total makes.

Scenario 3.  Players take all 32,511 three-point shots:

• with the defender 9+ ft. away 
• with 4+ seconds on the 24-second shot clock

Prediction: 43% of all shots will go in, an increase of another percentage point compared to Scenario 2, translating to 370 more makes and 13,901 total ones.

Percentage of predicted makes by scenario  

Each scenario’s likely effect results from all-or-nothing simulation.  How does it work?  For any predictor variable, such as Catch, data analysts select one target value—either “Off Catch” (occurring 75% of the time) or “Off Dribble” (25%).  Assume they choose “Off Catch,” with a logit coefficient of 0, as Table 1 shows.  For the 8,127 “Off Dribble” shots, they would replace the coefficient of -0.09, also shown in Table 1, with 0 and calculate the new likely effect: 158 more made three-pointers for the season, translating to 11,584 total makes. 

Adopting a fine-tuning approach is another possibility.  After examining the frequency distribution of the Catch values, analysts could specify a new distribution, such as 92% “Off Catch” and 8% “Off Dribble,” ensuring the total sums to 100%.  They would keep the original 24,384 “Off Catch” values (i.e., 75%) and change the -0.09 coefficient to 0 for another 2,600 selected randomly from the original 8,127 “Off Dribble” values to achieve the 92:8 ratio.  The change would result in 11,530 made three-pointers, 54 less (i.e., 11,584-11,530) than if players had taken all shots off the catch.

If coaches and players embrace simulation, there could be too many scenarios for data analysts to handle.  To stay ahead of demand, they could build self-serve simulators tailored explicitly for coaches’ and players’ use.  Finding prototypes in academic research will be a struggle, however, arguably because of the non-linear relationship between logits and probabilities (26, 30) and its dampening effect on reporting likely effects in probabilities or percentage points.  Figure 2 plots illustrative logit and probability values to cast light on that relationship.

The non-linear relationship between logits (x-axis) and probabilities (y-axis)  

Note how a one-logit increase from zero to one on the x-axis corresponds to a .23 probability increase (from .5 to .73) on the y-axis.  Yet a one-logit increase from four to five (or minus 5 to minus 4) translates only to a tiny probability increase.  As shown in Table 1 (and later in Table 3), it is still possible to report the effect of a predictor variable, x, on a binary outcome, y, in probabilities or percentage points (e.g., a one-unit change in x is associated with a three-percentage-point increase in y, all else being equal).  Arguably, it is also sensible to do so, not least because NBA players make roughly 35% of their three-point shots and the relationship between logits and probabilities is reasonably linear between .2 and .8 on the probability scale, as Figure 2 shows.  But in more extreme cases, as Figure 2 suggests, the effect size will depend heavily on the value of y and the values of the model’s other predictor variables.  More precisely, the size of the effect will decrease near 0 and 1.  As a result, x’s effect on y in probabilities percentage points “…cannot be fully represented by a single number” (19) (p. 23).  That may be why some logistic regression experts (6-8) have advised against using probabilities or percentage points to report and interpret logistic regression coefficients’ overall effects.  It also may be why most major statistical software packages do not produce effects in probabilities or percentage points through pre-packaged procedures or built-in modules.  As an unintended consequence, some data analysts seeking guidance likely have had to fend for themselves.           

A GUIDE TO BUILDING SELF-SERVE SIMULATORS Data analysts can use this guide to build simulators that report likely effects in probabilities or percentage points.  (For convenience, references are made to the three-point shot data used in this paper’s analyses, although the guide is general and should work across areas of interest.)  Several steps are involved in the process:

Step 1 . Ensure sufficient three-point shot data are available to conduct logistic regression analysis, which should be a straightforward task for NBA teams given the league’s business relationship with Second Spectrum (which replaced SportVU).  How does one define sufficient?  As a rule of thumb, at least 10 shot attempts are needed for each predictor variable in logistic regression model, adjusting for the expected shot make rate (or miss rate if it is lower than the make rate).  For context, this paper’s main analysis with six predictor variables and a 35% expected make rate required a minimum of 171 three-point shot attempts: 10 * (6 /.35).  For non-NBA teams requiring raw data, assistant coaches can record key shot characteristics with paper and pencil or specialized hand-held apps. 

Step 2 . Develop a model to predict successful 3-point shots, the binary outcome of interest.  Logistic regression produces a weight—a logit coefficient—for each category of each predictor variable.  In an optimal model, those weights maximize the predicted probability gap between the mutually exclusive outcomes (1).  

Step 3 . To calculate a single 2014-15 three-point shot’s make probability, sum the weights corresponding to its characteristics and add the constant.  After that, apply the formula shown earlier to the result: exp (sum of logit coefficients + constant)/ (exp (sum of logit coefficients + constant) +1).  Alternatively, request the predicted probability from the statistical software.

Step 4 . Do the same for the 32,510 remaining shots, sum all 32,511 probabilities, then take the average to compute the overall make probability.  If the model predicts players will make 35% of all three-point shots, it translates to 11,426 makes (.35*32,511).   

Step 5 . To enable the simulator to work online or in a mobile app, develop an algorithm using JavaScript.  The simulator’s purpose is to let users see how changes they make to the values of the predictor variables affect the .35 probability.  

Step 6 . Design a user interface, possibly by enlisting the support of someone familiar with website and app development.

Step 7 . Keep things simple initially—permit users to change only one value of one predictor variable.  If it has two response choices like Away and Home, let the user change every Away response to Home or vice versa.  Think of this as the  all-or-nothing  option.  

Step 8 . For all 32,511 three-point shots, change the corresponding Away or Home logit coefficient (but no others) to align with the user’s selection, then recalculate the predicted make probability.  The likely effect is the difference between the new and starting probability (and the new and starting makes).   

Step 9 . Follow the same process to let users change the values of several predictor variables simultaneously. 

Step 10 . Go further and allow users to change any predictor variable’s frequency distribution as they please, ensuring the distribution sums to 100%.  Think of this as the  fine-tuning  option.  The algorithm will need rules to accommodate the changes.  

What would all-or-nothing and fine-tuning self-serve simulators look like, and how would they function?  Figure 3 shows a screenshot of a working all-or-nothing simulator (accessible at https://www.electricinsights.com/hoops1 ).  The first column contains the predictor variables and their values.  Column 2 shows the changes (in blue) the user made to the 2014-15 frequencies; the third column displays the original frequencies.

All-or-nothing simulation  

As Figure 3 shows, the user selected values of “0-3 ft.” for “Defender Distance,” “0-2 secs.” for “Time Left on Shot Clock,” “Dribble” for “Off Catch or Dribble?” and “26+ ft.” for “Shot Distance.”  The likely effect is a 22-point decrease in the make probability, translating to 7,229 fewer makes and 4,197 total ones.

Personalized simulators for players like Klay Thompson and Stephen Curry could be more beneficial (and accurate) than a generic, all-player one.  To support this point, Table 3 reports the results of a new analysis of Curry’s 2014-15 three-point shots.  Note how the values of many key measures, such as frequencies and expected values, differ substantially from their Table 1 counterparts.  Table 3 shows, for instance, that Curry took 54% of his three-pointers off the dribble with an expected value of 1.32 points per shot.  But Table 1 showed NBA players (including Curry) took only 25% of their three-pointers off the dribble with a 1.01 points-per-shot expected value.  Curry is not your average three-point shooter, hence the need for personalization.  

Results of Steph Curry logistic regression analysis  

Note .  n=j.  Log pseudolikelihood, starting value: -305.04; final value: -294.46.  Likelihood ratio (degrees of freedom=13): 21.16, p > chi 2 = 0.07. Tjur R 2 : 0.047; McFadden R 2 : 0.035.  Stukel chi 2 (1) = 4.38, p > chi 2 = 0.11.

A working fine-tuning simulator—a complement to the Curry analysis—is available at https://www.electricinsights.com/curry1 .  It lets users change any value of any predictor variable by any amount and see the likely effect.  In the screenshot shown in Figure 4, the user changed Curry’s 2014-15 season frequencies (in parentheses) for “Defender Distance,” “Off Catch or Dribble?” and “Shot Distance.”  The likely effect is a seven-percentage-point increase to his 42% average make probability, translating to 31 more makes (i.e., 220-189).

Figure 4  

Steph Curry’s fine-tuning simulator  

If the sample size of three-point shots allows, data analysts can build all-or-nothing and fine-tuning simulators that include all teams and players, each team, and each player.  Given sufficient demand, they can also do so with data for other major shot types (i.e., two-pointers and free throws).    

Several caveats are in order before describing how basketball teams might act on the results the approach described here, using the results (and simulators) shown earlier for illustration.  First, inferences drawn from the 2014-15 dataset may no longer apply because of the time gap.  Nor did this dataset include several three-point shot characteristics (e.g., closest defender’s height and reach, the game score at each shot) that could be important, which is a second caveat. 

A third caveat concerns the “all else the same” assumption, a logistic regression analysis theoretical staple.  In practice, it may not hold up.  Giving excellent three-point shooters more playing time, for example, could worsen teams defensively.  Deciding who plays and why, a type of optimization, lies outside this paper’s scope.

Another caveat involves ease of implementation.  Building and updating simulators like Curry’s for NBA players who shoot, say, 175 or more three-point shots per season may require automation.  To characterize the task as trivial would be misleading.

Humility and ignorance are two key factors to consider as the fifth caveat.  Some NBA data analysts may have already adopted an approach combining good data, logistic regression, likely effects reporting in probabilities or percentage points, and self-serve simulation.  As noted earlier, they work mainly in secrecy.  And when they make comments at analytics conferences or similar forums, some are instructed “to go up on stage and talk about something without saying anything” (15) (51:37), according to Zarren.

Application In Sports

Good basketball coaches position their players to make the highest percentage of three-pointers possible, all else equal.  They also implement a defense to minimize opponents’ three-point make percentage.  The analyses presented here suggest six factors affect the make percentage:

• Closest defender’s distance to the shooter
• Time left on the 24-second shot clock
• Whether the player shot off the dribble or catch
• Game period
• Shot distance

How might coaches act on these findings?  There are numerous possibilities, starting with game pace.  Fast ball movement from defense to offense (e.g., before the defense sets) gives the offensive team more time to find an open three-point shot, preferably before the four-second mark on the shot clock where shooting percentages dip, and unquestionably before the two-second mark where they plummet.  As the NBA’s all-time leading three-point shooter, Steph Curry understands this well.  Table 3 showed he attempted only two percent (compared to a five percent NBA average) of his three-point shots with less than two seconds on the shot clock.

Coaches should design offensive plays and patterns to create at least three feet of space between the shooter and defender.  A 22-24-foot shot’s make probability with the defender 0-3 feet away is only 29%, all else equal.  It increases to 34% with the defender 3-6 feet away.  Space is critical for Curry, too.  He shot 11% of his three-pointers with the defender 0-3 feet away versus the NBA average of 6%, reducing his overall make percentage.  It could have been worse.  Had he taken all 448 of his shots with the defender 0-3 feet away, all other factors being equal, his make probability would have dropped from 42% to 24%.

Making sure players understand the characteristics of a desirable three-point shot is another opportunity.  Personalized simulators like Curry’s can make each player’s shooting strengths and weaknesses obvious.  For instance, some players may make a higher percentage of three-pointers off the dribble than catch.  Others may suffer only a slight percentage point decline when guarded tightly or shooting from 26+ rather than 22-24 feet.  And if those simulators contain opponents’ shot data, coaches could use them to determine how to exploit specific opponents’ weaknesses.

Analyses show the three-point make percentage drops in the fourth period.  Player fitness could be a contributing factor.  Without applicable data (e.g., feet, meters, or miles logged since tip-off), it is difficult or impossible to test the hypothesis.  Maybe the players on the court lack the skills needed to shoot higher percentages.  Or game stress could affect shooting performance—data on the game score at each shot would clarify the matter.  For context, the all-or-nothing simulator would show that the highest probability three-point shot (46%) has these characteristics:

• Defender 9+ feet away
• 4+ seconds on the shot clock
• 22-24 feet from the basket
• At home 

The simulator would also show that the 46% make probability drops to 42% in the fourth period, changing nothing else.  That means players have grown tired, different players are on the court, game pressure has taken its toll, or unknown variables caused the drop.  So how should head coaches make sense of this?  Working with assistant coaches and data analysts, they can explore ways to increase players’ fitness levels, optimize substitution patterns, and help players cope better with pressure.  If teams can access variables that were unavailable for analysis here, their analysts can include them in new models to estimate their likely effect.

Players make a higher percentage of three-point shots at home than on the road, all else equal.  Crowd noise, characteristics (e.g., lighting) of the less familiar setting, travel effects (e.g., uncomfortable hotel beds), or some combination of these may explain why.  Coaches can look outside the league for ideas to help players overcome such obstacles.  For instance, former US Navy SEAL commander Mark Divine prepares SEAL candidates for training by replicating the challenges they are likely to encounter, including Hell Week during which “each candidate sleeps only about four total hours but runs more than 200 miles and does physical training for more than 20 hours per day” (5). 

Contrary to conventional wisdom, Divine’s SEALFIT program places particular emphasis on skills like positive visualization, breath control, and meditation because, as he said, “People who haven’t learned to control their mind and emotions quit or they get hurt” (10).  Does SEALFIT work?  Divine reports that nine of 10 SEAL candidates who complete SEALFIT training become SEALs (versus a 20% norm).  He is confident that NBA players would benefit from the program (M. Divine, personal communication, March 11, 2022).

A complementary tool for improving performance is psychotherapy.  As described earlier, Ben Simmons’s decision to avoid attempting an open lay-up or dunk (arguably) for fear of being fouled and having to shoot free throws may have cost his team the 76ers a 2021 playoff series to the Hawks.  As his teammate Joel Embiid declared, “That was the turning point” (12) (1:08).  Psychotherapist Richard Schwartz, who developed the Internal Family Systems (IFS) therapeutic model (23), would probably concur then speculate that Simmons’s widely criticized decision (21, 27) originated from past trauma linked to his poor free-throw shooting.  After citing evidence (24) of IFS’s effectiveness, Schwartz might posit that a protective part of Simmons’s mind—a “guardian of [his] inner world” (23) (p. 184)—compelled him to pass rather than shoot to prevent a traumatized part—think of it as a deeply wounded child—from re-experiencing pain or shame at the free throw line.  Were Schwartz to work with Simmons, he would likely try to communicate with his mind’s traumatized part as if it were an actual person, restore its faith in Simmons’s free-throw shooting abilities, and encourage the protective part to undertake different tasks.  The more traditional coaching approach of advising, or even requiring, Simmons to practice harder with expert guidance did not—and may never—work.  As Early (9) observed, “Simmons has been reluctant to seek help from top shooting coaches…He reportedly clashed with his former team (the 76ers) years ago over who he would work with, preferring to practice with his brother rather than team shooting coach John Townsend.” 

Coaches can use the same strategies to reduce their opponent’s three-point shooting percentage they use to improve their own.  Table 1 data (and the all-or-nothing simulator) suggest the key lies in forcing opponents to shoot with less than four seconds on the clock, off the dribble, from long distances while being closely guarded.  Stepping up the defensive intensity in the first and third periods where the likelihood of making a three-point shot is relatively high, and motivating the home crowd to unsettle opponents makes sense, too.

Coaches can also think about implementing a full- or three-quarter court press more often, maybe for entire games.  The goals of a 2-2-1 three-quarter court press, for example, are control and containment, not turnover generation.  As envisioned, its use would slow down the game and force opponents to shoot a higher percentage of difficult three-pointers with less time on the clock, reducing their make percentage.  As Hall-of-Fame coach Jack Ramsay explained in Pressure Basketball , “The tempo of the game is controlled by the defensive team and the best manner of control is through the exertion of pressure at some point on the court” (22) (p. 80).

Good data, logistic regression analysis, and self-serve simulation can also promote truth and trust, positive attributes for any coach or leader.  Maybe tongue in cheek, former NBA coach Jeff Van Gundy (15) (17:40) confessed to lying to his players. “If I saw what I wanted to change,” he said, “I would either use numbers to support it or make them up because the players are not going to know the difference.”  Giving players tools that predict the likely effects of their potential actions would be more truthful and potentially more effective, too. 

Conclusions

Keeping things simple is critical in basketball.  According to Zarren (15) (7:00), “There are 20 things in (the coach’s) head that will get us X number of wins per season, but you can only focus on six of them in practice, and the players might only remember four and actually execute one in a game.  So you’ve got to pick your battles if you’re a stats guy who…needs to talk to a coach.  But if you’re a coach, you need to pick your battles, too.”

Van Gundy (15) (16:51) offered data analysts and coaches strong advice related to this point from his coaching experience.  “I wouldn’t tell a guy you’re 38% on three to four dribbles so dribble a fifth time because you go up to 40%,” he said.  “You better be pretty sure about what you’re saying…You want players to feel confident.  You don’t want them out there saying, ‘Was that [four] dribbles or [five] when I pull up?’” 

To mitigate the risk of generating harmful insights, data analysts should actively engage coaches and players in making key analytical decisions (e.g., ensuring predictor variables and their levels are meaningful), not least because Van Gundy and others who share his philosophy consider basketball sense —the capacity to make wise choices that benefit the team—to be of paramount importance.  

Arguably, self-serve simulation with likely effects reporting in probabilities or percentage points is steeped in such basketball sense.  As a benefit, data analysts will not need to rely on technical terms (e.g., “he shoots two standard deviations below the league average when you force him to the left” (15) (48:20)), as former Memphis Grizzlies’ executive John Hollinger once did.  Instead, they can speak with more authority using plain language (e.g., “his make probability drops to 28% when you force him to the left”).  Or they can make self-serve simulators available to players (and coaches) and let them figure it out on their own.  They may appreciate it, even cynics sharing Hall-of-Fame player Charles Barkley’s views: “Analytics don’t work at all.  It’s just the crap that some people who are really smart made up to try to get in the game because they had no talent” (29) (2:05).

NBA and other basketball teams worldwide should consider adopting an approach that combines good data, logistic regression analysis, likely effects reporting in probabilities or percentage points, and self-serve simulation.  The possible benefits are myriad.  It can help teams increase their three-point shooting percentages while lowering their opponents’; improve communication among data analysts, coaches, and players; enhance each group’s effectiveness; and lead to more wins. 

Variables in the 2014-15 NBA shot dataset

• Game_Id: The game’s unique identifier.
• Matchup: The teams competing.
• Location: Whether it was a home or away game for the shooter’s team.
• Outcome: Whether the shooter’s team won or lost.
• Final_Margin: By how many points the shooter’s team won or lost.
• Shot_Number: The shooter’s nth shot that game.
• Period: The period in which the shooter took the shot.
• Game_Clock: Minutes and seconds left in the period in which the shooter took the shot.
• Shot_Clock: Seconds remaining on the 24-second shot clock when the shooter took the shot.
• Dribbles: Number of dribbles the shooter took before shooting.
• Touch_Time: Number of seconds the shooter had the ball before shooting.
• Shot_Dist: Distance in feet from the center of the basket to the shooter.
• Pts_Type: Whether the shooter attempted a two- or three-point shot.
• Shot_Result: Whether the shooter made the shot.
• Closest Defender: Name of the defender closest to the shooter.
• Closest_Defender_Player_Id: The closest defender’s unique identifier.
• Close_Def_Dist: The closest defender’s distance to the shooter in feet.
• Fgm: Whether the shooter made the shot.
• Pts: The shot’s point value (0, 2 or 3).
• Player_Name: The shooter’s first and last name.
• Player_Id: The shooter’s unique identifier.

Note: The original dataset contained 128,069 two- and three-point shots. After removing all two-point shots, and all three-point shots with a missing (or unimputable) value on the Shot_Clock variable, the size decreased to 32,511. For a value to be imputable, there had to be 24 seconds or less on the game clock when the player took the shot. In that case, the decision was made to replace the missing Shot_Clock value with the Game_Clock value.

ACKNOWLEDGEMENTS

The author would like to thank David Clemm, Robert Eisinger, Ward Fonrose, John Geraci, Ryan Heaton, Adam Hoeflich, Priam Lacassagne, Roxane Lacassagne, and Mark Naples for reviewing earlier versions of this paper, and for providing helpful comments and suggestions. The author is particularly thankful to Dan Dougherty (who passed away in 2022) and Tom Northrup for their indirect contribution. Their longstanding beliefs and ideas about how basketball should be played permeate this paper’s “implications for coaches” section.

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An Analysis of the Geographic Distribution of Minor League Sports Teams

George Minoso 2024-05-01T12:50:45-05:00 May 3rd, 2024 | General , Research , Sports Management |

Authors: Dr. Mark Mitchell 1 , Richard Flight 2 , and Sara Nimmo 3

Mark Mitchell, DBA

Professor of Marketing

Associate Dean, Wall College of Business

NCAA Faculty Athletics Representative (FAR)

Coastal Carolina University

P. O. Box 261954

Conway, SC 29528

[email protected]

(843) 349-2392

1 Mark Mitchell, DBA is Professor of Marketing at Coastal Carolina University in Conway, SC.

2 Richard Flight, PhD is Associate Professor of Marketing at Coastal Carolina University in Conway, SC. He previously worked in minor league baseball with the Memphis Redbirds and Birmingham Barons as well as in DI collegiate athletics at Samford University.

3 Sara Nimmo currently serves as Assistant Director of Marketing for San Diego State University Athletics. She previously served as a Fan Engagement Assistant with MiLB’s Myrtle Beach Pelicans.

Purpose: The purpose of this study is to evaluate the geographic distribution of minor league sports teams in the United States and Canada.

Methods: A census of minor league sports teams was assembled by collecting data from league websites and other sources. Then, the data was sorted by city and state (or Canadian province). This process allowed the identification of the cities and states/provinces that host the largest number of minor league teams and leagues.

Results: Minor league sports teams can be found in 43 of 50 U.S. states (86%) and the District of Columbia (i.e., Washington, DC) and 8 of 10 (80%) Canadian provinces. There are 12 North American cities or metropolitan areas that host four or more minor league teams: Atlanta, GA; Austin, TX; Birmingham, AL; Dallas-Fort Worth, TX; Des Moines, IA; Las Vegas, NV; New York, NY; Oklahoma City, OK; Salt Lake City, UT; San Antonio, TX; San Jose, CA; and Toronto, Ontario. Additionally, there are 24 cities that host three minor league teams that are distributed across 20 different states and provinces.

Conclusions: While select cities have attracted multiple minor league teams to their communities, these teams tend to be dispersed all over the United States and Canada. As expected, states with larger populations tend to host more teams. States with weather that allows year-round outdoor play tend to host more teams. Cities with successful franchises can use that demonstrated fan support to attract new teams and leagues to their communities.

Applications in Sport: In addition to offering family entertainment, the minor leagues offer both players and professional staff the opportunity to enter the business of professional sports and work toward careers at the major league level. The results of this study illustrate where minor league teams can be found in the United States and Canada. From this list of cities, sports fans can watch up-and-coming players develop. Furthermore, sport educators can direct their students (i.e., aspiring sport administrators) to the cities and teams that may provide them with an entry-point into the field of sports administration.

Key Words: Minor league sports, sports expansion possibilities, minor league team affiliations

Organized sports may be thought of as the games people play. However, there is a very large business and financial infrastructure behind the scenes to allow those games to be played and the related fan experiences to be realized. Plunket Research estimated the total U.S. sports and recreation industry to be valued at over $550 billion in 2020 with the global market estimated to be worth $1.5 trillion (28).

Players making it to the major league of their sport have had to successfully navigate a developmental path by playing in the minor league system and earning successive promotions to earn a spot on a major league roster. In some cases, such as baseball, basketball, and hockey, these minor league teams represent hierarchical levels in a player development path that is clearly laid out. This focus on player development prompted Major League Baseball to restructure its minor league system beginning with the 2021 season. The new model provided for increased player salaries, modernized facilities, and reduced travel time and costs. The restructuring reduced the number of affiliated teams from 160 to 120 (12, 20).

Many colleges and universities offer sport management programs to serve interested students. Currently, there are 421 sport management programs in the United States at the Associates, Bachelors, Masters, and Doctoral levels (33). At the undergraduate level, Sport Management is the 38th most popular major among students. Each year, over 11,000 bachelor’s degrees in sport management are awarded (10). Furthermore, students from other disciplines (e.g., business, physical therapy, nutrition, hospitality, and others) often seek to apply their skills in the business and operation of sports teams. Much like athletes who seek to secure a position in the minor leagues to begin their hopeful path to the major leagues, many people interested in careers in sports administration and sports management begin their careers in the minor leagues as well.

The purpose of this study is to conduct an analysis of the geographic distribution of minor league sports teams and leagues in the United States and Canada. The results of this study will illustrate the cities, states, and provinces that currently host the most minor league teams. From this data, sports fans can incorporate a minor league game into their travel plans while prospective employees can see where their opportunities may be found and focus their job search activities accordingly. First, a broad overview of major and minor league sports is provided, including a look at the possible affiliations between major and minor league teams. Second, the geographic distribution of minor league teams will be provided to illustrate those states and cities that host multiple teams. Finally, the matrices of major and minor league cities are examined to identify the communities most likely to be discussed as expansion cities for major league sports.

THE ORGANIZATION OF MAJOR LEAGUE AND MINOR LEAGUE SPORTS  

In the sections that follow, the teams and leagues involved in the major spectator team sports are profiled. Sports that have a longer professional history (such as football, baseball, or basketball) have a clear path of player development and a delineation between their ‘major’ and ‘minor’ leagues. For these sports, the minor league teams are included in this study.

Other newer professional leagues (such as women’s soccer, women’s ice hockey, or men’s lacrosse), have not yet established a hierarchical path for player development. Rather, it is evolving and, in some cases, changing annually. As such, the athletes who do progress to compete at the highest available professional level (i.e., NWSL, PWHL, or NLL) do realize a pinnacle or ‘major’ achievement. However, these teams and leagues are more similar operationally (attendance, budgets, etc.) to minor league sports rather than the traditional major league sports of football, baseball, or basketball. For these sports, these teams and leagues are included in this study. In the future, with the stability and expansion of these leagues, these sports may attain the classification of ‘major’ league sports.

Men’s Baseball

There are currently 30 Major League Baseball (MLB) teams operating in the United States and Canada (18). Each of these teams has an affiliated Triple-A, Double-A, High-A, and Low-A team. Additionally, MLB operates two leagues for first-year players: Arizona Complex League (ACL) and the Florida Complex League (FCL) where games are played at the Spring Training sites of MLB teams. Additional teams bring the total to 179 teams across 17 leagues in 43 states and 4 provinces (20). A list of minor league baseball teams is provided in Appendix A.

Appendix A: Major League Baseball and Minor League Affiliates  

Source: (20).  

Men’s Basketball

There are currently 30 National Basketball Association (NBA) teams playing in the United States and Canada; 28 of these teams have an affiliated G-League (or, minor league) team (27). Two teams (G League Ignite of Las Vegas, NV; Capitanes Ciudad De Mexico of Mexico City) operate independently and without NBA team affiliation (1). A profile of NBA G-League teams is provided in Appendix B.

Appendix B: G-League Teams and NBA Affiliations  

Source: (27). 

Women’s Basketball

There are currently 12 Women’s National Basketball Association (WNBA) teams playing in the United States (40). There is no existing minor league development system for the WNBA. With just 12 teams and a maximum of 12 roster spots per team (compared to 15 roster spots for the NBA), the competition for one of these coveted roster spots is intense. Players selected in the three-round draft are not guaranteed a roster spot. There has not been any recent expansion of the WNBA despite calls to expand opportunities for women athletes (39).

Men’s Hockey

There are currently 32 National Hockey League (NHL) teams playing in the United States and Canada (24). The American Hockey League (AHL) serves as the top development league for the NHL. There are currently 32 AHL teams playing in the United States and Canada (6). The vast majority of AHL players were selected in the NHL draft and have been signed to player development contracts (17). A level below the AHL is the ECHL (formerly known as the East Coast Hockey League) with 28 teams, with each team affiliated with an AHL and NHL team (11). A list of AHL and ECHL teams is provided in Appendix C.

Appendix C: American Hockey League Teams and Affiliated NHL Teams  

Source: (13). 

Men’s Soccer

There are currently 29 Major League Soccer (MLS) teams playing in the United States and Canada (19). The USL Championship League is sanctioned by the U.S. Soccer Federation as a Division II professional league. The USL Championship League includes 24 teams located in the United States with expansion teams planned. A level below, the USL League One has 12 teams with 2 expansion teams planned. (36). A list of USL Championship and USL League One teams is provided in Appendix D.

Source: (36). 

Women’s Soccer

There are currently 14 National Women’s Soccer League (NWSL) teams competing in the United States (26). A list of NWSL teams is provided in Appendix E. The United Soccer League (USL) is introducing the USL W League in Summer 2024. There are plans for 44 teams located in 20 different states. The USL W League hopes to “bring elite women’s soccer to communities across the U.S., creating more opportunities to play, watch and work in the women’s game.” The USL W league will be introduced as a para-professional league, meaning the players will retain their amateur status (37). For this reason, these teams are not included in this analysis.

Men’s Football

There are currently 32 National Football League (NFL) teams competing in the United States (23) and 9 Canadian Football League (CFL) teams competing in Canada (9). Over time, there have been competing and/or feeder leagues to the NFL, including the World Football League (WFL), the United States Football League (USFL), the Extreme Football League (XFL), and the Spring League. In December 2023, it was announced that the USFL and XFL would merge to create the United Football League (UFL) and begin play in the spring of 2024 (32). Through the merger process, eight teams were retained and eight teams ceased operations. One city (Houston, TX) previously hosted both USFL and XFL teams prior to the merger. The XFL Houston Roughnecks ‘survived’ the merger while the USFL Houston Gamblers did not. The following cities lost their USFL and XFL teams beginning in the 2024 season (16):

New York/New Jersey Metro

New Orleans, LA

Philadelphia, PA

Pittsburgh, PA

Orlando, FL

Seattle, WA

Las Vegas, NA

Indoor or Arena Football has been played in various locations since the mid-1980s with the Indoor Football League (IFL) being the longest-running league. There are 16 IFL teams playing in 2024. IFL personnel, including players, coaches, scouts and front office professionals have transitioned to the National Football League (15). In addition, the National Arena League (NAL) operates a 6-team league (22). A review of the various non-NFL football teams is provided in Appendix F.

Men’s Lacrosse

There are currently 15 National Lacrosse League (NLL) teams competing in the United States and Canada (25). The league plays its games in indoor arenas, often the same arenas that host minor league hockey and NBA G-League basketball teams. A list of NLL teams is provided in Appendix G. Beginning in Summer 2023, the Premier Lacrosse League started play with 8 teams in the United States. In its inaugural season, all 8 teams travelled to a select city for competition each weekend. City names are not attached to teams (29). As such, these teams are not included in this analysis.

Women’s Professional Hockey

The Professional Women’s Hockey League (PWHL) began its inaugural season in January 2024. The newly-created league consists of 6 teams across the United States and Canada with teams located in Boston, Minneapolis, Montreal, New York City, Ottawa, and Toronto (30).

Miscellaneous: Athletes United

Since 2020, Athletes Unlimited has introduced professional leagues in women’s basketball, volleyball, lacrosse, and softball. The leagues state they are ‘player-centric’ while avoiding the traditional model of city-identified teams. With this model, many American athletes can play professionally in their home country rather than competing abroad (7). However, teams are not based in home cities. As such, these teams are not included in this analysis.

METHODOLOGY  

The minor league teams and leagues profiled above that operated in the 2023-24 seasons were identified and assembled into a database to allow the analysis of the location of the teams. The sorting function in Microsoft Excel allowed the researchers to identify the frequency of occurrence for city, state, and province, resulting in the identification of the following groups: 

• States and/or provinces that host the most minor league teams; 
• Cities that host the most minor league teams; 
• Cities that are most likely to be considered for league expansion in the future. 

While select cities have attracted multiple minor league sports teams to their communities, these teams tend to be dispersed all over the United States and Canada. In the United States, 43 of 50 states (86%) host at least one minor league team. The states that do not current host a team are Alaska, Hawaii, Louisiana, Montana, North Dakota, Vermont, and Wyoming. In the Lower 48 states (excluding Alaska and Hawaii), minor league sports can be found in 43 of 48 (90%) of the states with the missing states being sparsely populated (with the notable exception of Louisiana).

In Canada, minor league teams can be found in 8 of 13 Canadian Provinces or Territories. The provinces that do not current host a team are New Brunswick, Northwest Territories, Nunavut, Prince Edward Island, and Yukon. Similar to the pattern found in the United States, teams can be found in 8 of 10 Canadian provinces (80%) with no teams located in the three more sparsely-populated Canadian Territories of Northwest, Nunavut, and the Yukon.

A city-by-city mapping of each minor league team located in the United States and Canada is presented in Figure 1. The heat mapping function in Microsoft Excel was used to generate Figure 2, a visual presentation of the frequency of location of minor league teams per state and province.

Interestingly, minor league teams have been located previously in Hawaii (baseball), Louisiana (baseball), Montana (baseball), North Dakota (indoor football), Vermont (baseball), and Wyoming (baseball). However, no teams existed in these states during the 2023-24 season. In fact, some of these baseball teams were among the 40 teams affected by the realignment of minor league baseball to begin the 2021 season (see 20, 31).

State-by-State Analysis

The following states host the largest number of minor league teams:

California (26 teams in 17 different communities)

Texas (25 teams in 15 different communities)

Florida (23 teams in 16 different communities)

New York (19 teams in 12 different communities)

North Carolina (17 teams in 12 different communities)

Pennsylvania (12 teams in 9 different communities)

Ohio (10 teams in 7 different communities)

Georgia (9 teams in 8 different communities)

Iowa (8 teams in 5 different communities)

Michigan (8 teams in 5 different communities)

South Carolina (8 teams in 4 different communities)

Oklahoma (7 teams I 2 different communities)

Washington (7 teams in 4 different communities)

Arizona (7 teams in 3 different communities)

Indiana (7 teams in 3 different communities)

Virginia (7 teams in 5 different communities)

Province-by Province Analysis 

The following Canadian provinces host the largest number of minor league teams:

Ontario (6 teams in 3 communities)

British Columbia (3 teams in 2 communities)

Quebec (3 teams in 2 communities)

Alberta, Manitoba, Newfoundland and Labrador, Nova Scotia, and Saskatoon (1 team each)

It must be noted that junior hockey is a very popular spectator sport in Canada. However, most junior hockey players are classified as ‘amateurs’ (2). For this reason, Canadian junior hockey teams are not included in this analysis.

City-by-City Analysis 

As illustrated above, many communities host more than one minor league team. Furthermore, some cities with minor league teams also host major league sports teams. For example, Charlotte, North Carolina hosts an NFL team (Carolina Panthers), an NBA team (Charlotte Hornets), and an MLS team (Charlotte FC) in addition to hosting minor league teams in baseball, hockey, and soccer. Nearby Greensboro, North Carolina also hosts three minor league teams in basketball, indoor football, and baseball but hosts no major league teams.

Table 1 provides an overview of the 12 cities that host four or more minor league teams. The reader will note that some the cities are larger metropolitan areas with teams located both in the city and the suburbs. Atlanta, for example, has one team in the city but four teams in its suburbs in close proximity to central Atlanta. These communities with a concentration of minor league teams often host additional sporting events, such as golf tournaments, auto races, or college football bowl games.

San Diego is an interesting case. In addition to hosting the San Diego Padres (MLB), the city previously hosted an NFL team (San Diego Chargers) and two NBA teams (San Diego Rockets and San Diego Clippers). All three of these professional teams continue to exist but relocated to other cities. San Diego has effectively attracted minor league teams to fill the voids left by the departure of these teams. Recently, the San Diego Loyal soccer team (USL Championship League) ceased operations after the 2023 season after failing to find a long-term home stadium option (14). However, an MLS expansion team (to be known as San Diego FC) will begin play in the 2025 season (34).

Table 2 provides an overview of cities that host three minor league teams. Included in Table 2 is each city’s ranking in size as a media market (21). Also, any professional teams in these same cities are shown with their table cell shaded. Sports not currently playing in those communities represent opportunities to expand a city’s minor league sports portfolio. It is interesting to note that some of these 3-team cities (such as Worchester, MA or Tacoma, WA) are very close to neighboring cities of top 15 media markets.

DISCUSSION  

As expected, larger states with larger populations tend to host more minor league teams. Concurrently, cities with larger populations (and larger media markets) tend to host more minor league teams. The three states with largest number of minor league teams (California, Texas, and Florida) also offer a climate conducive to year-round outdoor activities. Cities with successful franchises can use that demonstration of fan support to attract new teams and leagues to their communities. Furthermore, shared facilities (such as an arena that can host basketball, hockey, and arena football) can help bring new teams to a community.

As previously noted, many cities host both major and minor league teams. Intuitively, these locations should attract the most attention should leagues consider expansion as the fan bases have demonstrated sufficient levels of support to sustain a major league team. These cities are listed in Table 3. Additionally, these cities tend to be the larger media markets with larger numbers of consumers. As an illustration, at the time of this writing the Oakland Athletics are strongly considering moving to Las Vegas, NV and have already received the approval to move by Major League Baseball owners (3-5).

INSERT TBL3

A Cautionary Note – Minor League Baseball Relocations  

In 2020, Major League Baseball issued new facility standards for minor league teams, including: minimum clubhouse sizes for both home and visiting teams; food preparation and dining areas attached to clubhouses; better field lighting; more and better training space for players; separate space for female staffer, and others (31). Given that many minor league stadiums are municipally-owned, some communities may be unwilling or unable to make the needed investments in upgrades and may see their teams migrate to other communities, particularly at the A- and AA-levels.

In fact, some team movement has already been announced as the Kinston, North Carolina team (now known as the Down East Wood Ducks) have been purchased by Diamond Baseball Holdings (the largest owner of minor league baseball franchises) and will relocate to a new yet-to-be-built stadium in Spartanburg, South Carolina and assume a new team name as early as the 2025 season (8). This move marks the return of minor league baseball to Spartanburg, which previously hosted the Spartanburg Phillies from 1963-1980 and again from 1986-1994 (38).

CONCLUSIONS

Minor league sports teams are widely distributed across the United States and Canada with 86% of U.S. states and 80% of Canadian provinces hosting at least one minor league team. These 43 U.S. states host 97% of the U.S. population while the 8 provinces host 96% of the Canadian population. The highest concentration of teams can be found in four geographic areas in the United States: (1) the southeast Atlantic corridor from Virginia south through Florida; (2) the eastern Midwest and Northeast including Pennsylvania, New York, and Massachusetts; (3) the Southwest including Texas and its border states; and (4) the West coast primarily concentrated in California. In Canada, Ontario (i.e., the Toronto area), British Columbia (i.e., the Vancouver area), and Quebec host more minor league teams than the other provinces.

In addition to offering family entertainment, the minor leagues offer both players and professional staff the opportunity to enter the business of professional sports and work toward careers at the major league level. The results of this study illustrate where minor league sports teams can be found in the United States and Canada. From this list of cities, sports fans can watch up-and-coming players develop. Furthermore, sport educators can direct their students (i.e., aspiring sport administrators) to teams for internships and entry-level employment opportunities.

APPLICATION IN SPORT

In team sports, most professional athletes go through a player development process that includes some stint in the minor leagues in the hopes of earning a spot on a major league team. Similarly, many sport administrators begin their careers working for minor leagues and affiliated teams as they learn their craft and assemble the needed experiences for (hopeful) promotion to the major league level. The results of this study allow interested parties to easily identify the communities with greater access to minor league sports (for both fans and prospective employees). Sports fans should find this information helpful as minor league sports provide a good financial value in family entertainment. College students may find internship and employment opportunities with these minor league teams to aid their entry into a career of sport administration and management. Sport administration educators may find this information helpful as they advise and counsel their students for internships, co-operative employment opportunities, and job placement after graduation.

The communities identified here with multiple sports properties may allow a student to work in multiple sports in the same city (say, basketball in winter and baseball in spring, summer, and fall). In many instances, there may be an overlap in the ownership groups of minor league teams. This overlap in ownership may expand professional opportunities for employees as well-performing employees are offered additional positions and responsibilities elsewhere in the organization.

These communities also tend to host other events, such as college football bowl games or golf tournaments. These special events will need qualified staff to deliver these events, which will include people already living and working in those communities in the sports industry. Much like athletes in the minor leagues work to advance toward the major league ranks, so, too, can staff personnel ‘climb the ladder’ toward careers in the major leagues.

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Male Competitive Powerlifters relationship with Body Image: Utilising the Multidimensional Body Image Self Relations Questionnaire (MBSRQ)

George Minoso 2024-04-22T08:06:50-05:00 April 20th, 2024 | General , Research , Sport Training , Sports Exercise Science |

Authors: Dr. Mark Chen 1 , Dr. Andrew Richardson 2

1School of Health and Life Sciences, Teesside University, UK (corresponding author) 2 Population and Health Sciences Unit, Newcastle University UK

Corresponding Author: Mark Chen Campus Heart, Southfield Road, Middlesbrough TS1 3BX, Tees Valley [email protected]

Dr Mark Chen is a Senior Lecturer in Sport and Exercise Science at Teesside University and is a Chartered Psychologist with the British Psychological Society (BPS). Dr Chen’s research interests include psychological consequences of sports injury and attentional aspects of sports performance.

Dr. Andrew Richardson is a Chartered Heath and Activity Practitioner with the Chartered Institute for the Management of Sport and Physical Activity (CIMSPA) and is currently a Research Associate within the Population and Health Sciences Institute at Newcastle University. Andrew’s other research interests include body image, performance enhancing drugs, transgender sport, esports and public health..

Male Competitive Powerlifters relationship with Body Image: Utilising the Multidimensional Body Image Self Relations Questionnaire (MBSRQ).

Purpose: There is growing evidence to suggest that competitive male athletes in aesthetic sports that scrutinize their body image may experience undesirable mental health outcomes. However, there is limited research to address these issues in strength sports, particularly the sport of Powerlifting. Methods: This study employed the Multidimensional Body Image Self Relations Questionnaire (MBSRQ), which recruited 365 male participants across the following subgroups. Powerlifters (P) (n = 133), Active Subjects (AS) (n = 79), Appearance Based Sports (ABS) (n = 68), Strength Sports (SS) (n = 47) and Other Sports (OS) (n = 38). Results: One–way ANOVA showed significant (p < 0.05) results between all groups across six of the nine MBSRQ subscales. Post hoc comparisons found nine significant results with the powerlifting group achieving two of them against OS (p < 0.01) and AS (p < 0.01) groups respectively. Conclusions: Overall, the results showed that male powerlifters expressed their bodies-as-function rather than their bodies-as-object with regard to health evaluation and fitness orientation. This is supported by their stable and balanced scores across the MBSRQ subscales which indicates they have healthier and lower perceptions of negative body image concerns. The powerlifters results implied that a focus on objective performance improvement and maintaining a healthy body to prevent injury had body image benefits. Applications in Sport: The study concludes that male powerlifters present healthy body image perceptions compared to the other males in their respective sports and focus on their body functionality objectively rather than the subjective perception and presentation of their body image.

Keywords: Powerlifting, Body Image, Weight Classed Sports

For this paper, the definition of Body image is referred to as “relating to a person’s perceptions, feelings and thoughts about his or her body, and is usually conceptualized as incorporating body size estimation, evaluation of body attractiveness and emotions associated with body shape and size” [1-2]. There has been extensive work conducted on the influence of body image in the media [3], in Western culture [4] and job roles such as the fitness industry [5]. Other comparisons include comparing body image within a range of demographic factors such as between athletes and non-athletes [6], age [7], nationality and ethnicity [8]. Cash and Pruzinsky [9] have defined five dimensions of body image, which work together to create an overall body image. However, these dimensions fails to mention the broader cultural and social contexts that influence body image [10]. They suggested that athletes dealing with sporting and societal pressures may experience adverse outcomes such as eating disorders or a negative perception of their body image. Such factors may lead to these pressures as a result of media and advertisements [11], supplements [12] and the use of image and performance-enhancing drugs [13].

Background of Powerlifting

Powerlifting athletes are scored on objective performance measures rather than appearance evaluations. Powerlifting tests athletes on their objective strength and has traditionally been male-dominated [14]. However, in the last twenty years, female participation has significantly increased [15]. Richardson and Chen [16] state that powerlifting is a competitive strength sport comprising three techniques: the Squat, the Bench Press and the Deadlift [17-18]. The aim is to lift the most weight across the three movements for nine attempts [18]. Sports similar to powerlifting that heavily rely upon strength include Olympic weightlifting [19], strongman [20], highland games [21] and the shot–put [22], to name but a few examples. Not all of these sports mentioned have a weight class or a weight requirement, but for those that do, depending on the rules of the competition, this weight requirement may be evaluated within twenty-four or even forty-eight hours prior to the event [23]. Weight classes help ensure fairness in competition and increase the pre-competition demands of participants to enter the weight category that maximizes their advantages. Experts argue that making weight places psychological demands on athletes who may be inclined to make drastic weight cuts to gain a competitive advantage [24]. However, as powerlifters are evaluated on the amount of weight lifted, the training is based on objective scoring criteria. As scoring is objectively determined, and not a third party as in aesthetic sports, this has important implications for positive psychological adaptations [25].

Theoretical models and frameworks

Theoretical models of body image, such as Objectification theory, focus on the impact on men of a culture that increasingly objectifies men’s bodies. It suggests that men, like women, may experience self-objectification [26]. For men, the dual focus on both leanness and muscularity characterizing the male body ideal may motivate a particularly maladaptive set of behaviors designed to achieve these goals, such as rigid exercise routines, hidden use of image and performance-enhancing drugs (IPEDs) [27]. Subsequently, the literature has claimed that men may suffer from body image concerns and dysfunctional behavior [28]. Some research argues that young men experience societal pressure to achieve the muscular mesomorphic body shape, and this behaviour leads to a drive for muscularity [29].

Further, studies have demonstrated that sociocultural pressures mediated by social comparisons and internalization of muscular and low-fat ideals are associated with men’s body dissatisfaction and drive for muscularity, which might lead to disordered eating [30]. Most research has focused on aesthetic sports such as bodybuilding [31-32]. These explanations fail to consider how individuals think, feel and behave concerning their body functionality [33]. How powerlifters think, feel, and behave about their body functionality in a sport concerned with achieving objective demands is essential to achieving a more complete and holistic understanding of body image in this context [34].

Theoretically, the subjective perception of muscularity depends on the individuals’ perception of body image, which for powerlifting tends toward a functional muscularity rather than aesthetic muscularity due to the sport’s rules. Critically, the self-objectification model does not consider the functionally orientated nature of sporting competition and its impact on male psychology [35]. Therefore, the athletes have a strong sense of control and need to prepare, train and diet concerning maximizing objective performance criteria, not gaining approval from judges based on aesthetics. The environmental demand to achieve an objective standard has essential implications for broadening body image, as Ginis et al., [36] reported. They found that the idea of muscularity and physical competence in men [37] are central to their evaluations of their bodies. According to Conceptualisation theory, men are socialized to focus more attention on their body functionality than body-as-object (image) [38]. Therefore, powerlifting males are likely to value the functionality of their body over appearance, not only due to socialization processes that favour the achievement of tangible performance-based outcomes [39-40] but also due to the specific environmental demands of powerlifting which reward objective performance results. In contrast, perceptions of leanness and body fat percentage are less relevant to powerlifters performance. Franzoi [38] defined body-as-process as comprising physical capabilities and internal processes, which is similar to body functionality. The demand for functionality adds sources of experience, such as training to execute specific external and internal demands, that requires knowledge of body functionality (movement) and is, therefore, adaptive for how male powerlifters individuals think and feel about their body image [38].

For example, Richardson and Chen [16] found that female powerlifters, despite presumably having been socialized to experience higher levels of self-objectification and greater body-as-object identification than men, as predicted by self-objectification theory, nevertheless enjoyed their appearance in their sporting environment, indicating that it was not a source of anxiety, presumably due to the enjoyable experience of functional powerlifting training and competition reward. This was evident in other studies using smaller sample sizes and qualitative interviews in the same sport and sex [14 & 41]. Bordo [42] found that individuals who presented with large muscular physiques symbolized strength and masculinity.

Competition achievement and social reward within a sport based on tangible athletic goals [43-44] and psychological characteristics such as aggression when preparing to lift [45] will strongly mitigate against excessive rumination around body appearance and identity. Further reasoning supports the powerlifting community’s emphasis on body functionality [46-47]. From this perspective, male powerlifters likely develop a functional appreciation of their body that is valued separately from its appearance. This construct of functionality appreciation has only recently been investigated in the context of positive body image. It is positively associated with positive body image facets, such as body appreciation [48].

Franzoi [38] proposed that individuals hold more positive attitudes toward their body functionality than their body image. Therefore, it can be predicted that males with this orientation will hold performance adaptive attitudes toward their bodies. Body conceptualization theory offers a rationale for the body functionality being adaptive and reflective of positive male body image and improved mental health, compared to a body image orientation. This theorizing gives scope that negative body image attitudes can be adaptive and motivational within a performance-based environment based on objective rather than subjective and image-based criteria. For the male powerlifters, this would be the performance their bodies execute to meet the environmental needs (e.g., the sporting demands of their event). For example, Gattario and Frisen [49] found that males stated that finding a social context in which they found belonging and acceptance that allowed them to develop agency and empowerment allowed them to move from a negative to positive body image. With this logic, it could be predicted that competitive powerlifters will differ in their positive body image compared to individuals who are active but don’t compete.

Nevertheless, functionality measures have focused predominantly on physical capacities and internal processes and have typically concerned physical strength and muscularity. These aspects of body functionality can be conflated with physical appearance and are accentuated by male appearance ideals and the male gender role emphasizing dominance, power, and strength [50-51]. There has been some research into the body image perceptions of athletes in strength sports. Goltz et al [52] divided 156 male athletes into weight-class sports, endurance sports and aesthetic criteria sports and found no differences in body shape concerning self-depreciation due to physical appearance. Richardson and Chen [16] found no association between negative perceptions of appearance for female powerlifters compared to aesthetic sports individuals. These results suggested that the powerlifting group had contentment with their appearance, perhaps due to the decreased emphasis on body image compared to the increased emphasis on body functionality and focus on improving their skills and strength for their sport.

Apart from these few studies, research has yet to be done on body image and functionality in male powerlifting. The association of the physical body with functional sporting competition achievement based on objective standards may reduce the potential for internalizing negative body image and lead to healthy adaptations based on physical demands. This research will explore what functionality means for male powerlifters and how this impacts body image and functionality. This study aims to compare the body image of male powerlifting athletes against other subgroups of male athletic participation. The aim is to examine if male powerlifting athletes express different body image satisfaction or dissatisfaction with their body image and weight compared to subgroups of active and or sporting males.

Aim and Objectives of the Study 

To compare the body image differences of male powerlifters against a range of male athletic subgroups. 

● The first objective was to determine if the powerlifters have significantly lower scores regarding their bodyweight perception when compared to other male groups in the study.

● To determine if powerlifters present an emphasis on body-as-process rather than body-as-object.

Participant Information

An opportunity sample of 365 males was recruited through Facebook and Instagram. The recruitment period lasted three weeks in length and generated the following subgroups. There were 133 Powerlifters (P), 79 Active Subjects (AS), 68 Appearance Based Sports (ABS) participants, 47 Strength Sports (SS) participants and finally, 38 Other Sports (OS) participants within their respective subgroups. The group sample means and standard deviations for their age were 28.65 (± 7.44), height was 178.58cm (± 13.3cm), and their weight was recorded at 89.99kg (± 18.20kg). 

Within Table 1.0, each subgroup’s means and standard deviations were recorded for their age, height, weight and the length of time they have spent training. The powerlifting (P) group mean age was 27.71 ± 6.86 years, the mean weight was 92.73kg ± 21.24kg, and the mean height was 176.67 ± 15.27cm. Appearance Based Sports (ABS) group mean age was 28.04 ± 7.59 years, mean weight was 86.89 ± 14.55kg, and height was 177.11 ± 12.32cm. The active Subjects (AS) group’s mean age was 30.30 ± 8.19 years, the mean weight was 84.99 ± 12.81kg, and the mean height was 179.85 ± 14.91cm. The strength Sports (SS) group’s mean age was 29.19 ± 7.26 years, the mean weight was 97.41 ± 20.11kg, and the mean height was 181.69 ± 7.02cm. In the final subgroup Other Sports (OS) group, the mean age was 28.95± 7.49 years, the mean weight was 87.19 ± 15.53kg, and the mean height was 181.47 ± 7.87cm. No ethnic identity data was recorded. The study was conducted after obtaining ethical approval from the Teesside University School of Social Science Business and Law Ethical Approvals Committee. 

Measures 

Multidimensional Body Self Relations Questionnaire (MBSRQ): The MBSQR measures Body Image divided into cognitive and behavioral components [53]. Items are ranked on a 1 to 5 Likert scale, where 1 = Definitely disagree, and 5 = Definitely agree. The MSBRQ subscales include Appearance Evaluation (AE), Appearance Orientation (AO), Fitness Evaluation (FE), Fitness Orientation (FO), Health Evaluation (HE), Health Orientation (HO), Illness Orientation (IO), Body Areas Satisfaction (BASS), Overweight Preoccupation (OWP) and Self-Classified Weight (SCW). Illness Orientation is not included as a separate subscale, as it is already reliably accounted for under Health Orientation. The MBSRQ is significantly evidenced in Body Image research [9 & 53] as a well-validated measure [54] through comparison with other tools of Body Image. The MBSRQ has a proven reliability and validity record for body image research [53]. The composite reliability was calculated using an SPSS Omega Macro [55] and is within the acceptable range (Cronbach’s omega = 0.79). The primary author constructed demographic questions to collect information about the participant’ background. These questions included (but were not limited to) sex, age, height, weight, and years spent training. 

Both the MSBRQ and Demographic Questionnaire were developed using Google Documents. Data gathered was stored under the General Data Protection Act [56]. Participants were assigned to groups 1.00 (Powerlifters – P), 2.00 (Appearance Based Sports – ABS), 3.00 (Active Subjects – AS), 4.00 (Strength Sports – SS) and 5.00 (Other Sports – OS), based on their answers from the demographic questionnaire. Participants were given no monetary or external incentive to take part. Participants read the pre-questionnaire information, participant information form and questionnaire instructions. Once read, participants were prompted to check a box that confirmed their consent to the study. All participants completed the questionnaire individually and received no communication from the researcher during data entry. A glossary was provided for technical terminology. Demographic questions were formatted as short answers, rating scales, and multiple-choice. Participants were informed they could opt out anytime during the study for any reason. In total, the questionnaires took about 10-15 minutes to complete.

Data Analysis

An independent group design was used to investigate the differences between the MBSRQ scores of the four. The dependent variables measured the differences in body image between the groups across nine subscales. All data were analyzed using Microsoft Excel version 2016 and Statistical Package for Social Science (SPSS) Version 27. Means and Standard Deviations were calculated for all the subscales. Data were checked for equality of variance between groups and assumptions for the one–way ANOVA where the alpha value was set at 0.05. Post hoc tests were calculated to compare the powerlifting group with the other three groups across the MBSRQ subscales. The post hoc alpha values were corrected for type one error rates using p < 0.01. To estimate the effect size of post hoc mean differences between groups, the Cohens d statistic size was interpreted using the following guidelines: .00-.2 (small), .40-.79, (medium) and .80 + (Large) [57] and 95% Confidence Intervals (CI) were reported. The Hedges g statistic was used if one or both groups being compared had n < 20, otherwise, Cohens d was reported.

The descriptive statistics associated with the MBSRQ scores across the five groups are reported in Table 2.0. It can be observed that the powerlifting group was associated with higher, consistently stable and healthy body image scores in comparison to the other four male sub-groups. Six of the nine MBSRQ subscales reported p-values below 0.05.

Below are the graphs of the nine subscales from the MBSRQ presented to showcase the differences in mean scores for each domain of body image.

DISCUSSION This study aimed to compare the body image of male powerlifters with sporting and physically active males. There were multiple significant results across six of the nine MBSRQ subscales between the groups. Overall, the results of this study suggest that male powerlifters have a healthy relationship with their physical body when compared to all other groups. The powerlifters on average, evaluated both their health and fitness orientation were higher compared to both physically active males and males in other sports. Comparing the groups anthropometrics, all groups expressed similar heights, weights and mean age. Most participants from the powerlifting group were in the late twenties, average weight at 92.73kg and standing around 178cm in height. Nolan, Lynch and Egan [58] used a male sample that was comparable to the current study in size and age. Other studies recruiting male powerlifters all had smaller sample sizes and younger age ranges [59-60] compared to the current study.

The first objective was to determine if the powerlifters had significantly lower scores regarding their bodyweight perception when compared to other male groups in the study. There was no evidence to support this prediction, as the powerlifting group levels of overweight preoccupation and self-classified weight area satisfaction were not significantly different from the other groups. The Powerlifting group had scored 2.49 for the OWP subscale which was higher than both SS and OS groups but lower than AS was the powerlifting and ABS groups. This would appear to indicate that the male powerlifters either do not ruminate on their body-as-object to the detriment of their mental health or that the nature of engagement with the powerlifting competitive demands lends itself toward a functional conceptualization of the body over an image-based focus [61]. These results taken together do not imply that powerlifters demonstrated a negative perception of their body image. Rather, the results suggest that powerlifters link their body image toward objective performance related goals. Although, this is speculative, the intense regime of powerlifting training for competition would result to improved perceptions of body image due to perceived changes in strength over time.

Theoretically, powerlifters interpreting their body-as-process rather than the body-as-object is consistent with larger differences in Fitness Orientation, Health Evaluation and Overweight – Preoccupation compared to the sport male and physically active male groups. These subscales relate more to objective performance concerns, such as physical capacity, rather than the subjective interpretation of body image, thus appear to be accentuated by perceptions of power and strength [50-51]. Fitness orientation refers to, “Extent of investment in being physically fit or athletically competent. High scorers value fitness and are actively involved in activities to enhance or maintain their fitness. Low scorers do not value physical fitness and do not regularly incorporate exercise activities into their lifestyle” [53]. Richardson and Chen [16] found their sample of female powerlifters scored the highest out of this subscale when compared to other groups.

Health Evaluation is defined as, “Feelings of physical health and/or the freedom from physical illness. High scorers feel their bodies are in good health. Low scorers feel unhealthy and experience bodily symptoms of illness or vulnerability to illness” [53]. Richardson and Chen [16] found that their sample of female powerlifters scored the highest on this subscale compared to other sporting females.

Overweight preoccupation reflects “fat anxiety, weight vigilance, dieting, and eating restraint.” [53]. Richardson and Chen [16] found, for their powerlifting group, very stable scores around the normative values with little deviation from the mean, therefore indicating that the group were happy and content with their weight for the function of powerlifting. The Powerlifting group had higher OWP compared to the other two groups but not low enough to indicate extreme weight cutting, dieting or weight anxiety, Although, the nature of powerlifting does require some weight monitoring due to the weight classes requirement, the score was not concerning. An individual-by-individual analysis would need to be considered to accurately assess if an athlete is expressing extreme body weight anxiety or concerns.

Certainly, this does contrast with the findings of the Active subjects (AS) group who had a moderate effect size of greater overweight preoccupation (OWP) and self-classified weight (SCW) compared to Other Sports (OS) and Strength Sports (SS). These difference of the control group (AS) adds further weight for the difference between the powerlifters and the other groups body image. The active subjects were composed of individuals who don’t compete in any sport, but their recreational exercising still did not prevent them from having pre-occupation with their physique. Male exercisers can be as pre-occupied with outward appearance as women due to their motivation for muscularity [62] and also as non-athletes they may lack the functional body appreciation that male athletes possess [63].

The second objective was to determine if powerlifters present an emphasis on body-as-process rather than body-as-object. Theoretically, body functionality can be understood in contrast to appearance ideals and gender roles for men, which emphasise the importance of physical strength, prowess, and bodily control [64]. The absence of negative body image perceptions in the males only lends indirect evidence for a higher emphasis on functional cognitions related to objective performance. There were two significant differences between powerlifters with OS and AS in health evaluation and fitness orientation. There was a moderate effect size difference for health evaluation, with the powerlifting group showing more robust health behaviours than the other sports group.

The other sport group was the smallest group (n=31) and consisted of people who recreationally participated in a variety of sports of which Soccer, Cross fit and Athletics were the most numerous. The health cognitions of the powerlifters place an emphasis on being prepared to execute maximum effort in their training and respecting the possibilities and limit of what they can achieve [65]. Compared to sports such as Athletics and Soccer, which place more emphasis on diverse interceptive open skills in a changing environment and / or endurance, Powerlifting requires maximum and intense concentration to prepare for one explosive movement. Therefore, the powerlifters need to have a healthy attitude toward diet, for example, as performance is related to performing at their physical limits but is not essential for skilled footballers. These results contrast with Goltz et al., [52] who found no differences in self-depreciation due to physical appearance in comparing weight-class sports, endurance sports and aesthetic criteria sports.

The powerlifting group also showed stronger fitness orientation compared to the active subjects groups. This may mean that the powerlifters monitoring of their pre-performance health results in stronger fitness evaluations compared to individuals who only exercise and also individuals in sports with less physically explosive demands [65]. This seems to reinforce the first finding, that male powerlifters have a positive rather than negative view of their body image, in terms of the value they place on health and fitness related cognitions to help prepare for competition. The fitness-orientation aspect can be interpreted for body functionality qualities, as this subscale would support behaviours and cognitions conducive to maintaining good physical condition and a positive view of the body [66]. An explanation in terms of body conceptualization theory is that the functionality of powerlifting competition allows the participants to engage in a wider range of strategies to maintain fitness rather than being concerned with aesthetics, compared to individuals who only exercise [49].

Comparing this to the appearance-based sport (ABS) group, they too also undergo intense and regimented training, as competitors will need to ensure they are in the best condition for competition, although still based on aesthetics. However, where the ABS group differ from the powerlifters is a moderate effect size for overweight preoccupation compared to the OS group. There was also a moderate effect size for self-classified weight compared to the strength sports group. These two subscales are more in line with previous findings [67], in that aesthetic sport participants need to put more effort in body monitoring and judgements related to weight loss or gain. In powerlifting, research has shown that to overcome confounding issues that may affect athletic performance, athletes reported that the following factors help relieve or reduce competition day stressors include, the coach, mental attitudes, technical instruction, training partners and social isolation [67]. When comparing between sexes, the results revealed no fundamental difference in these confounding factors by male and female powerlifters [66]. Within both studies, it was noted that there was no mention of body image when competing to be a compounding factor, which supports the current findings. Nevertheless, the powerlifters body image or perception of their own image was not given as an option in their studies so results may have been different if participants had been given an option to select.

The AS group reported two medium effect sizes against the other sports group and strength sports group, which were in the overweight preoccupation and self-classified weight subscales, but the powerlifting group scored a moderate effect size against the AS group in fitness orientation. The reason for this can be linked to multiple variables. Firstly, the AS group participants as stated earlier in this manuscript are not training to improve their performance within a specific sport or event. They are active males who are training but with no sport specific goal in mind. Hence, these individuals may be more critical of themselves when it comes to focusing on their bodyweight. This can be easily demonstrated in the subscale of SCW where the AS group scored the lowest when compared to the OS and SS groups. As individual in these sports may compete at a weight they are comfortable at, this yields them the best performance advantages when in competition.

Notwithstanding, the AS group did score closer to a mean normative value for their OWP subscale and scored higher than both OS and SS groups. The reason may be that higher scores focus more on weight vigilance and weight anxiety. However, the OS and SS groups scoring lower than AS and having low OWP scores indicates that their sports don’t require, or these athletes didn’t express any worry about their weight when competing.

Nevertheless, there is research to suggest that those who train for body image and pursue masculine muscular ideals may be motivated for these appearances through unhealthy means. These include self – blame and or internalised shame as reported by Larison and Pritchard [68] found that men who scored higher on these variables also reported higher levels of eating disorder symptomology. Yet, in the same study, those same men who scored higher for internalised shame also scored higher on the drive to be more muscular. Finally, Swami and Bedford [69] found that men’s drive for muscularity was significantly predicted by neuroticism and their drive for body appreciated was significantly predicted by neuroticism and extroversion when considering BMI and subjective social status as drivers. However, in other studies the opposite findings have been reported. Reina et al., [67] also reported that males in non-aesthetic sports were more dissatisfied with their body image and were 1.5 times more likely to use exercise to lose weight than non-sport participants.

Limitations The MBSRQ is a valid and reliable and well stablished body image assessment tool and is appropriate for out study [53]. Nevertheless, the MBSRQ does not measure disordered eating or specific ideals of muscularity as compared to other aforementioned assessment tools. The powerlifting group in this study as in the female study by Richardson and Chen [16] is centred around one sport and unlike the other groups they are made up of multiple sports. Ultimately, this will have impacted their scores within their groups and comparing between groups. The powerlifting group as a whole had more training experience than the other groups which is reflected in their larger sample size and more stable scores which has to be factored into the analysis.

CONCLUSIONS In summary, the findings report the powerlifters presented with stable and positive outlooks and evaluations of their body image. This highlights a productive relationship with their own body image and their sport of powerlifting as a body-as-function role instead of body-as-object [47]. Comparing the powerlifters with other sport groups showed similar results. The powerlifters presented with significantly (p < 0.05) better scores for HE and FO subscales in the MBSRQ when compared to the AS and OS groups. The majority of the groups displayed stable MBSRQ subscale scores and healthy outlooks on their body image. The study found that powerlifters did not express or display any extreme perceptions of their body image despite them competing within a defined weight category. These results also find that the athletes recruited for the powerlifting group train for performance and are less concerned about their body image. By positioning their focus on objective performance (lifting as much weight as possible) this appears to have psychological benefits which helps negate negative body image as recorded in the female samples of Richardson and Chen [16] and Vargas and Winter [14]. Future research should focus on qualitative interviews with male powerlifters and additional sports to understanding the relationships between their body image and their sport.

APPLICATIONS IN SPORT The majority of previous research concerning male body image is associated with negative behaviour outcomes such as aggression, violence and or the use of PEDs [70]. This study has taken a different approach to show strength training for males has a positive outlook on their body image helping to create healthy and stable relationships with their mental health using an objective measurement. In this instance, it is the sport of powerlifting that focuses the athletes on the performance to lift as much weight as possible across three events.

Competing in a weight class sport does not necessarily produce extreme group scores and or undesirable behaviours concerning their bodyweight or body image. This implies that strength training methods such as powerlifting for males (and females as shown in Richardson and Chen [16] when seeking to improve their health and fitness are beneficial. The focus on objective strength gains via tracking their lifting through increments using progressive overload allows positive body appreciation. As a positive by-product, they will also develop improved physique through increased levels of physical activity and adherence to a training program. Furthermore, by seeing continued progressions through improving their technical proficiency doing the movements and increased muscle hypertrophy will lead to a better outlook on their mental health and body image. As they are viewing their body for its function not as an object they place less emphasis on subjective body image changes but rather on performance. In populations that include body image disorders and eating disorders, using this form of training will help support clinicians in helping return their patients to exercise routines to support a holistic recovery pathway [71].

Author roles Dr. Mark Chen: Conceptualization, Methodology, Formal analysis, Writing – original draft, Writing – review & editing, Supervision, Project administration.

Dr. Andrew Richardson: Conceptualization, Methodology, Formal analysis, Data curation, Writing – review & editing, Project administration.

Conflict of Interest Statement: The authors declare that have no conflict of interest when writing and or submitting this manuscript for peer review publication to The Sport Journal.

Funding No funding was sought or requested for the formation of this manuscript

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Decision-making on injury prevention and rehabilitation in professional football – A coach, medical staff, and player perspective

George Minoso 2024-04-08T09:47:11-05:00 April 8th, 2024 | General , Research , Sports Management |

Authors: Mads Røgen Noesgaard 1 & Stig Arve Sæther 2

1 Department of Sociology and Political Science, Norwegian University of Science and Technology, Trondheim, Norway 2 Department of Sociology and Political Science, Norwegian University of Science and Technology, Trondheim, Norway

Stig Arve Sæther Department of Sociology and Political Science Norwegian University of Science and Technology, NTNU, Dragvoll, 7491 Trondheim, Norway E-mail: [email protected], https://orcid.org/0000-0002-1429-4746

Mads Røgen Noesgaard is educated as a physiotherapist and holds a master’s degree in sport science from the Norwegian University of Science and Technology. He has an extent experience as a physiotherapist from professional sports especially related to football and handball.

Stig Arve Sæther is an associate professor in sport science at the Norwegian University of Science and Technology, with an extensive research portfolio in talent development within sports and especially football. Sæther is head of the sport science staff, head of education at the department of Sociology and Political science and head of the research group Skill and Performance Development in Sports and School (SPDSS).

Purpose The aim of this study is to research how the decision-making on RTP from the medical staff impact on the perceived short- and long-term performance of the player and the team, from a coach, medical staff, and player perspective. Methods: Two professional football players, one physical coach, one physiotherapist and one assistant coach were interviewed in-depth and recruited because of their insight, experience, and expertise from one Norwegian premiere league club. Results: The decision-making process on RTP in the club were partly based on the hierarchy in the club, where the coach was on the top among these actors. Despite that the actor´s describes the process as a natural dynamic, and felt a shared responsibility in the process, their different roles impact on the decisions. The RTP decision was affected by aspects such as the period in the season, earlier injury experience of the player and the medical staff and coach collaboration. Conclusions: Even though the medical staff and the injury prevention could mean that the player could have a longer career, the choices made in the process of RTP is often based on short term player and team performance. Applications in sport: Professional football players have competition as a living and are expected to enjoy and embrace competing against both other teams related to winning trophies and teammates related to a place on the team in matches. This degree of competition was also seen as a part of the RTP process since the competition with teammates gave the players motivation to overcome their injury situation and get back to compete for their “spot” on the team. Even though this study only includes experiences from one professional football club, it gives insight into how the RTP process is done in a professional football context. Future studies should consider recruiting representatives from the club management, which also could give insight on how the macro aspects of a club impact on the RTP decisions in the coaching team of a professional football club.

Keywords : return-to-play, professional sports, communication

The development of professional football player is complex and consist of a myriad of factors, including injury prevention and rehabilitation through the return to play (RTP) (38). Even though the development of injuries in European professional football has decreased over the last two decades (10), the impact of injuries still plays a major role in both team and individual player development and success (7). Time loss in on field training and matches may have a negative impact on the players development, which makes it vital to minimize the duration of rehabilitation and RTP process. The responsibility of injury prevention, treatment and following RTP has in the literature been described as the responsibility of the medical staff, even though a strong coach and player involvement has been recommended (10). Even so, lack of needed authority in this process, have been highlighted as a challenge since both the coaching team and especially the head coach, and the players are expected to be a part of the decision process, hereby creating a dilemma (26). The need for a high performing medical team is thereby indicated crucial for the present success, but also future accomplishments (7).

Knowing that the major predictor in future injury being previous injury (13, 27-28, 35, 45), it has become standard procedure in European professional football clubs to screen and evaluate both in-squad players and potential investments even though research points to a lack of predictive capabilities (29, 46). Hereby the screening process is arguably/potentially increasing the consequences of previous injuries and treatment of such and the importance of injury preventive measures. In the pursuit of securing the best possible squad at all times injury preventive programmes such as FIFA11+, seems common but often adjusted based on either screening results or coaches’ preferences and hereby losing its evidence-based merits (29-30, 34, 46). Another promising preventive strategy is tracking and managing of load and restitution of the individual player and indicated to both increase the “here and now” short-term performance and the long-term performance. The main aim is to reduce the risk of injuries and illness (19, 24, 36), but it also presents a risk of withdrawing players from training and matches unnecessary.

The rehabilitation process of a player must address and manage the psychological and sociological health of the player (12). Though the general plan and goals of the rehabilitation is clear there is a lack of gold-standard and consensus for RTP which complicates the last steps before returning to training and competition (22). The literature advocates a shared-decision-making process to optimize this process. Coaches, medical staff, physical coaches, and the individual player all possess insight about the state of the player seen in a bio-psycho-social framework (5-6, 8, 47). A process as such is nonetheless challenged by the different profession’s confidence in their own decision, but also potentially with a lack of trust in others, hereby creating a dilemma where authority and power becomes more important than teamwork (9-10, 20). To increase the overall medical effort, the literature advocates an SDM-approach to minimize injuries and rehabilitation periods and improve RTP (1). Still, Paul et al. newly published editorial are highlighting that there has been identified concerns surrounding the social complexities of elite sports and the difficulties of truly applying this concept in practice (37).

Most of the research on this subject and in professional football have used a quantitative approach (7) and there seems to be a need of qualitative insight on how this process unfolds in practice, and how and by whom the decisions are made. An exception is Law and Bloyce (25) who interviewed professional football managers behavior towards injured players. The results indicated that managers at the lower levels felt more constrained to take certain risks related to injured players. The aim of this study is to research how the decision-making on RTP from the medical staff impact on the perceived short- and long-term performance of the player and the team, from a coach, medical staff, and player perspective.

Participants 

Two professional football players, one physical coach, one physiotherapist and one assistant coach were interviewed in-depth and chosen based on strategic selection because of their insight, experience, and expertise in the field and their long-term involvement within one Norwegian premiere league club. The two players have in total more than 15 years in the club, while the physiotherapist and the physical coach has been in the club’s medical team for more than five years and altogether more than 20 years of experience in the field. The assistant coach has more than seven years of coaching experience. The participants are described in table 1.

All interviews were conducted in person and the location chosen by the interviewee. The length of each interview varied from 50 to 90 minutes with a mean at 70 minutes. Each interview was initiated with general questions to start the conversation and to get more background information on each participant. Prior to the interviews the questions were largely prepared to facilitate the conversation into different themes and topics of interest, with prepared follow up questions when depth and more context was needed. The questions varied specificity from general questions about the interviewee’s thoughts on the injury-period (e.g. “How do you think a player can develop while injured”) to more defined questions about the different actors’ actual role in the decision-making process about RTP (e.g. What role does the player has in the RTP-decisions). With these types of specific questions, the former mentioned extensive experience and expertise in the field was highly prioritized in the selection of participants. This made the insight in the specific club more extensive and gave the answers more depth. In addition, all participants were giving the opportunity to read through the transcript and afterwards able to withdraw parts or the interview in full, which none of the participants did. None of the participants neither wanted to alter the transcription. All interviews were audio-recorded and transcribed verbatim. By using pseudonyms for each participant, the transcriptions ensured the interviewee’ confidentiality and furthermore, ethical approval was in accordance with and approved by the Norwegian Social Sciences Data Services (number: 678375).          

Analysis The analysis of data was done with the six steps of theme-centred approach as described by Braun and Clarke (2-3). The process was initiated by the transcription by the first author who afterwards read and reread the data twice. This was followed by initial coding, phase two of the chosen method. In this process the transcription was revisited multiple times until the final codes were discovered and presented to the second writer for discussion. The total of 47 codes were structed using a mind-map, which visualised the third phase of the process and used to structure the data into nine higher-order themes. Phase four was a back-and-forth process rereading the transcript, revising the raw material for clarifying questions, reviewing the codes all in all to elaborate the emerged themes. Through dialog and discussion within the research group the final three/four themes were identified, and subgroups reviewed and hereby phase five concluded. Finally, phase 6 was a detailed process and highly interwoven with the analysis of data. To present the findings in an argumentation related to research question and to illustrate the story of the data it was important to revise the extracts and go back to the both the higher order themes and the final themes in the writing of the report to ensure that the essence of the data was captured and presented. The final report presents the experienced everyday life of the participants in this specific Norwegian Premier League football club, how they perceive the decision-making process in the context of both development and performance and how the structure and reality of modern football plays and important role in both injury prevention and RTP after injury.

The actors in the RTP process – the club hierarchy According to the actors (medical staff, coach and players), the prevention of injury and RTP practice has changed throughout the last decades, from a collective focus to a more specific and individual practice, described as a positive change by all the actors. RTP was described as a process, with benchmarks which was considered a motivational factor in the overall rehabilitation process. The decision-making process in the professional football club related to decisions on injured players and their capacity to play were affected to some degree by a hierarchy in the club. Even though the actor´s in the present study describes the process as a natural dynamic, and that they agree on their shared responsibility of the process, the different roles impact on the decisions.

Highest in the hierarchy are the coaches, and even though they highlight that the medical staff has an impact on their decision, the coaches seem to be the final decision maker in the process. This is indicated as a natural order because the coach is the one to take the ”fall” when the decisions shows to be wrong or more precisely have a negative output and also the final responsibility for the team performance. The coach described therefor a need to keep the medical staff on their toes, which the medical staff described as a challenge of their decisions, often based on what they considered external pressure on performance and results. This again meant that the medical staff had to make the “right” decision to keep their authority in the collaboration with the coaches.

The players felt in this regard that the medical staff had a two-sided role or responsibility both towards the coaches and the players, but that they still according to the players weigh the perspective of the player the heaviest. This double role was considered challenging and could mean lack of support in cases of doubt, while the medical staff considered that the final decision was taken by the coaches and the player. From the player perspective the trust was described as essential in this process. So even though trust, communication and collaboration are fundamental elements to keep a squad of players performing, there is also a need for a trust in the actors’ competencies and loyalty, both highlighted by the coach Lars: “Despite thinking about the result, first and foremost, we of course think: “The best for the player”. Because the player performs best when he is 100% healthy, both physically and mentally.” The physical coach Thomas stated this on the matter:

Thomas: “Because the vast majority of players understand deep down what the point is. They know when they shouldn’t go out there. They want to have hope, that: “yeah, it’s allright” and so sometimes our job is actually just to say: “Yes, it’s actually allright”, even if it’s 50/50, if it’s the last match on the season and they wanna take the chance anyways. Okay, then we have to see that and then just say: “This is allright”.

Thomas argued that their role in the process was to inform the coaches and even though the decision was not always in line with their suggestions, they felt that their opinions was considered vital for the final decision-making.

The factors that impact the decision process

Because of the complexity and uncertainty of who decides which players could play, the medical staff experience situations where at times they felt pressured to clear a player for playing, which in their experience often leads to a longer injury period. And despite the open communication, the pressure got more intense especially before important matches and at the end of the season, as this conversation and the following quotes indicates: Physiotherapist Hans: “You get a player who runs at 60%?”, Coach Lars: “Yes, but he is so important for us in set-pieces, so we have to have him”. This becomes even more prominent at the end of the season as physical coach Thomas highlights: “The fewer matches left, the greater chances you are willing to take with the athlete’s health”.

The decision to deny a player to train or play a match based on the risk of injury, was considered difficult for the medical staff because of uncertainty of the outcome. The coach describes how they in some cases start the player and see how it goes. Even though this was described as happening seldom and especially since this could be considered treating the players differently, which potentially could impact the team dynamic:

Lars: “If you and I play in the same position, and you train 3 times a week but you are a little better than me. I’m training every single day, and then you get to play matches. I train more than you, twice a week, and then arrangements will be made for you to play. That could become a conflict.”

The medical staff points out how this load-management strategy is potentially positive for RTP, the coach argument furthermore how this might add pressure for the next matches both for the player and the medical staff. If the team loses, one could consider that being in minus and that means that the next match must be won. This adds on to the earlier statement that an injury might be a heavy process for a player:

David: “From the moment you feel that you are a part of something, then you will show up the day after you have been injured, then you show up for work. You eat breakfast, you go to the locker room and then the rest of the team go out on field and do what you love the most, they play football. But you wander into a dark gym alone and do what all footballers think is the most boring job, cycling and doing rehab training. As boring as it gets. But you have to do it. You go into such a lonely and confined, empty mental phase, it’s really hard.”

What was considered the “right” decision depended on the perspective, even though obviously the most impacted part is the player:

Niels: “Perhaps I have been lucky in that I have not had so many major injuries, but at the same time the one injury I have had, where it was done the way it was done, that was enough for me to think: “yes, I lost some good matches that year”, then you can think of those who have been injured longer and have had more injuries, how much it has affected them.”

Injuries are however also described by all actors as a natural part of professional football, and that this often means taking risks to be able to perform on the highest level. One of the players, David, describes it as following:

David: “At the top level, you are balancing on a knife’s edge much more often, because you are pushing boundaries all the time and then the need for medical help is all the greater than when you operate at a not so fully professional level.”

It could seem from a professional players perspective that the players consider their everyday life as a footballer as finding the optimal balance to be able to stay fit and avoid injuries, and that this situation is difficult and that they need help from the medical staff to be able to keep staying “in the game”. Even so, the physical coach Lars highlights the difference between pain and injury:

Lars: “I think when you play football and it’s one-on-one, it’s dueling, you can get a knee in the side, you can get hit by an elbow, so after a football match, you might have a bruise here and a little bit of swelling there and you can have, stiffness in generel. That doesn’t mean you need 2-3 days to recover because that pain you feel”.

Protecting the players

The coach stated that it was important to protect the players and not introduce them for unnecessary risk, even though he pointed out that there is a limit in terms of how much consideration one could do for each player. In this regard did the physical coach acknowledges that there had not been a reduction in the number of injuries despite the heavy number of added resources to prevent them. The injuries have changed but one has not been able to eliminate the incident rate:

Thomas: “There is much less ankel rolls, but there are more hamstring injuries and groin injuries because there is more sprinting in the matches and the matches are closer schedueled. And you can’t quite solve that. Even with sufficient sleep, enough nutrition, tablets in the fusion of plasma, i.e. “you name it”, game ready – the player still breaks down and then you see that if you train very well, then maybe you will go through the season with very little damage.”

This was also something the players describes as problematic in certain situations, as stated by Niels: “Coach, physio and they, they really push you back in and then it’s difficult as a player to sit there and say: “I’m not healthy”, it’s difficult!”

The physical coach recons it is all about the time spent on the pitch to improve RTP and the high amount of matches impact on the possibilities for the medical staff to schedule and complete the injury preventions and rehabilitation. One example mentioned are an away match where the travel time is the reason for the player not attending enough training sessions, even though he is ready to train.  Furthermore, the game importance is an important factor because of the impact on the results sportingly and economically and has been found to be the reason as to why players play partly injured, or at least adding on to the pressure on the medical staff and their decision on every player potentially injured.

          Also, one of the players described how he perceived that the players are at their best when the get to train and play matches as much as possible:

David: “All footballers perform at their best when they get the opportunity to play football every day. Play every match. That’s when you get into a rhythm, where you act on intuition in battle and in that moment. In order to do that, you have to have continuity in your training and to have that, you have to be good at taking care of your body, to manage and last through a tough week of training, to perform in every match. So it’s definitely important. You profit from doing a good job (ed. injury prevention) in order to be able to perform in the best possible way. It is absolutely indisputable.”

Both the players and the medical staff highlights that the injury prevention is important for the players to be able to train more.  The physical coach highlights that this injury prevention training has a direct impact on the player opportunity to run faster and develop more power.

One of the players mentions how each club and their culture try to maximise the development and that the club culture is impacting the performance. This was also mentioned by the coach who stated that building the club is one of the most important tasks for the club, which is considered difficult since both players and coaches comes and goes. Another challenge is the impact the head coaches have on how the club perceive injury and development. The physiotherapist describes how the many changes also impact on the medical staff and their way of working:

Hans: “I think that, the biggest challenge in all of this is the constant change in player material, the constant change, at least as it has been in X, that coaches change, and therefore you constantly have different routines. It is natural that a coach who comes in and is boss wants to have it his way, and then a new coach comes in who wants it his way. Then there will always be changes and that means that what you tested on last year will be tested in a different way this year.”

Both players and the physical coach add on to this position, even though they also see positive outputs when new people are trying to collaborate:

Thomas: “Things that work well can also be diluted by poor execution. I think we make it work. I think so. that’s how it is when you bring new things to the table. Basically, it should be a good thing and if you manage to get best out of it, then it will be beneficial.”

The injury situation as an opportunity for development

All the actors thought of the injury period as a period for potential development of performance level of the player. So even though the players considered it as a tough and challenging period, it also contains opportunities. The coach highlighted that this motivation and opportunity had to come from within, and that he medical staff and the coach’s role was to facilitate and further motivate. In that way the injury period can be effective and also an opportunity, which could be considered a win-win situation both for the player and the team. 

Still, at times the players felt pressured to play, and sometimes felt alone and “naked” in the discussion between them, the medical staff and the coaches. This was partly confirmed by the physiotherapist, who described football as being black or white at times, and that he felt the need to protect the player:

Hans: “A player who is out several times and often… It can very quickly become black and white in a football club, “This player is always injured. No, we’ll give up on him a little”, and then it’s challenging to say: “You mustn’t give up on him, even if he’s a bit injured now. There are several factors that cause him to be injured and we have to look at ourselves as well, all of us.” What we have often done is to look at the coach and say: “If we are going to get him out of this, we’ll have to make a change. What we are doing now is not good enough. So we have to take him out of training and have to do this instead of that. He can’t play every game and at the moment”.

However, at other times the medical staff also feel the need to push the players to return to ordinary training or playing matches. They feel the need to be careful since they might misstep. Some players might get pushed back to soon, while others need a push.

Lars: “Sometimes where you have to push a little, and we really do that for the sake of the player, not because we absolutely have to. We don’t take any chances with players, that is. But if we see that he has done what he is supposed to and at the same time it is a player who is a bit more careful with himself. Because that too, you have to know the group, you have to know the player, because there are some who can be too tough too early, and then there are some who are actually ready, but holding back. So you can say that sometimes we have to try and push them in a positive way too, I think. Without us doing anything wrong.”

One of the players Niels stated that for some of the players, they need to be more included in the decision-making-process. One example mentioned by one of the players was the importance to get into the pre-season together with the squad, to be able to compete about his playing position.

The medical staff clearly stated that they did not consider themselves having the definitive solution in every case. They also mentioned the fact that holding a player back from a match based on the fear of being injured might deprive the player from development and potentially economic gain (e.g. club transfer, bonuses etc.) or the team’s performance or the club’s economic gains. Many of the actors highlighted that if the player felt ready to play, and the coaches meant that he would have an impact on the game, the medical staff would take that into consideration. This position of taking a decision which is good for all the actors both in a short-term and long-term perspective was considered a difficult dilemma for the medical staff, since they feel an extra responsibility related to the players health.

Keeping the players on their toes but still together

The coach also highlighted that the competition between players could challenge the individuals in the club. Internal competition is essential and when a player is injured, that could create an opportunity for other players. This competition was also highlighted by the two players, however as a stressor for the injured player. The coach however stated that this type of competition must be present and that it makes the players push each other, and fight for a place on the team. This type of pressure, trying to withhold your place on the team, having the right attitudes, frequent changes in the coaching staff, and short-term results, was describes from all the actors as impacting the medical staff’s opportunity to impact the decision for players to play matches and their development. Both the coach and the medical staff highlighted that this might impact the decision, but never determined the RTP, while the players could consider this as a weighty stressor

The players point out a potential isolation of the injured players by dividing the players into two groups: those who are injured and those who are not, but this division is described differently based on the perspective. They also describe the rehabilitation as lonely, heavy, and boring, especially the acute phase, and experience that the injured players not to be a part of the community in the club, which the player Niels described in the following: “But I want to put it this way, you are down in hell and then you start the ascent from there, and then it becomes a bit like tunnel vision. You don’t see the light at the start, but you see it eventually”. The coach, however, does not describe this as an isolation or division of the team, but rather a natural part of the everyday life in a club, but highlight the importance of joint meals and meeting schedules. The medical staff have another nuance of this division, since an injury might be challenging and create a sense of exclusion, while this could also be good for the team, since the negativity which often comes with an injury does not get spread among the other team members. The physical coach highlights the same and furthermore that it should be attractive not to be injured.

All the actors describe the deprivation from matches in times of doubt about a player’s availability have both sportingly and economic negative impact on the player’s career:

David: “Football can be so simpel that if you, how should I put it , score a hat-trick in the right match against the right team, you can be like… And the salaries are so high, so if you end up in the right place then you, then you can in a way support the whole family for the rest of your life. So it’s quite clear that injuries affect the course of a career.”

Injuries means less time to train, and the actors agree that the time for the specific football training and matches are essential for a player’s individual development. Both the coach and the physiotherapist highlighted however the importance of making the most of the injury period, which could be considered as a window of opportunity to focus on individual skill development, which normally one does not have time for. The physical coach stated however that it might be difficult for a player to develop largely during the rehabilitation process. And this could be related to the somewhat black-white perspective the medical staff and the coach has on injuries. The physiotherapist meant that this approach might have a positive consequence for a player who have experienced an injury. They often work harder than before to be able to get back to football. At the same time Hans also pointed to the fact that the players could be “forgotten” by the coaches if they achieve a “bad” reputation: “But if you first get a reputation of being.. that the coach gets the feeling that he is not available, then it can often be difficult. A fight really. That is my experience”. The coach Lars partly confirmed this by stating that the coaches are aware of players who have a history of injuries, which often mean that they cannot play all matches during a season:

Lars: “In other words, injury follows injury. It’s a bit like that. So there are certain players that you know more or less that he is not going to play 100% of the games. Let’s say there is an exclusive player who often gets hamstring issues, then you know that during the season he will play 70% of the games. It may happen that we have players, who we know are like that.”

In a long-term perspective and focusing on the players career, the coach also highlighted that the players are screened and assessed by clubs if a club transfer is in motion, that a player with a large injury history would be considered as less interesting to recruit:

Lars: “[…] But the more players who don’t have an injury history.. So if you’re going to build a team then you have to get as few players as possible with an injury history, because often you see that those type of issues, especially if it’s the groin or hamstring or those types of injuries, they often come back.”

The coach described players’ injury history as essential when clubs assess which player they could recruit, and that injured players must convince the coaches to become relevant for a club transfer. These types of assessment are important for coaches in their process of building a squad both in a short-term and long-term perspective.

The aim of this study is to research how the decision-making on RTP from the medical staff impact on the perceived short- and long-term performance of the player and the team, from a coach, medical staff, and player perspective. The decision-making process on RTP in this professional football club were partly based on the hierarchy in the club (40). So, despite that the actor´s in the present study describes the process as a natural dynamic, and felt a shared responsibility in the process, their different roles impact on the decisions. The coaches were described highest in the hierarchy and related to them being responsible for the sportingly results and the performance of the team. The players were described as having a say in the decision of his availability, even though they often highlighted an experience of being pressured to play in certain situations (9). The medical staff was considered to have a two-sided role, since they were employed and a part of the coaching team and naturally felt a responsibility on behalf of the coaches and the club, they also felt the need to protect the players and their health as professional health workers (20). Their decisions would often mean that they had to “disappoint” the coaches or the player, by denying the player to play or the availability of a player in a match.

Responsibility was a term especially the medical staff used to describe how they felt about their role, but also when taking part in the final decision in the RTP process. This responsibility became important in the process of making “the right” call based on the information available while trying to account for the interests of all the actors. This might mean that they let a player play, with a “let´s see how it goes” approach, and that the outcome of the decision was described as “right” if the player played the whole game. A dilemma in the process was also related to the natural part of pain and injury as part of professional football described by all the actors in the process (31). So even if protecting the players was important, time spent on the pitch is the main goal for both the individual players and the team’s development and performance. Even so, earlier research (41) has indicated that elite sports have a pain culture where pain is a natural and expected part of elite sports, which could have a negative impact on the players development, if this means that the players do not communicate when feeling injured or unavailable for training and matches.

Professional football is all about results and performance (32). So, a characteristic off successful environments is their constant search of areas to develop further (14). This seemed to be the case in this club as well since a period of injury was considered an opportunity for the player to develop. The players are competing about a place in the starting line-up and need to pick up the glow to get back into the team. Still, there was also a mutual understanding that each RTP case might be different and had to be considered individually. So, in some cases both the medical staff and the coaches felt that some players needed a push to get back. This may in many cases also be in the best interest of the player since it could mean that they in example get identified by scouts, impacting their career by a club transfer. Furthermore, this pressure could mean that the players are willing to take a higher risk by playing while injured. The players in this study described being injured as lonely and feeling isolated from the team, as found in earlier studies (32), which could be perceived as an increased motivation to RTP potentially even before the mind or body are ready.

In accordance with the focus on results and performance in professional football are also the high degree of uncertainty in this professional context (15). This could be related to the small margins between success and failure. This is also related to the RTP process, since all actors in the process of RTP must make the best decision for both the individual and teams’ performance. Still, there is a lack of knowledge related to the potential outcome of the decision. This means that the actors must “take risks” to be able to maximize the opportunity to succeed. While it was not a part of the study, the obvious economically benefits of decreasing time loss in training and competition on both an individually (players, medical team, and coaching team) and club level (potential sale of players), also makes both the rehabilitation and preventive strategies important. The club perspective might conflict with the individual actors in the RTP process, with the example of the club winning the league, while a player got injured because of the overload and hereby potentially ending his career.

All the actors in this study highlight that football is a sport where you must expect to feel pain regularly and that injury is a part of being a professional football player. So even though the medical staff and the injury prevention could mean that the player could have a longer career, the choices made in the process of RTP is often based on short term player and team performance. Professional football players have competition as a living and are expected to enjoy and embrace competing against both other teams related to winning trophies and teammates related to a place on the team in matches. This degree of competition was also seen as a part of the RTP process since the competition with teammates gave the players motivation to overcome their injury situation and get back to compete for their “spot” on the team. Even though this study only includes experiences from one professional football club, it gives insight into howe the RTP process is done in a professional football context. Future studies should consider recruiting representatives from the club management, which also could give insight on how the macro aspects of a club impact on the RTP decisions in the coaching team of a professional football club.

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Comparing Public vs. Private High School Sports-Related Concussions from a Countywide Concussion Injury Surveillance System

George Minoso 2024-03-18T11:04:24-05:00 April 5th, 2024 | General , Research , Sport Training |

Authors: Gillian Hotz 1 , Jacob R. Griffin 2 , Hengyi Ke 3 , Raymond Crittenden IV 4 , Abraham Chileuitt 5

1 Department of Neurosurgery, University of Miami Miller School of Medicine, Miami, FL, USA 2 KiDZ Neuroscience Center, The Miami Project to Cure Paralysis, University of Miami Miller School of Medicine, Miami, FL, USA 3 Department of Public Health, Division of Biostatistics, University of Miami Miller School of Medicine, Miami, FL, USA 4 Department of Neurology, University of Miami Miller School of Medicine, Miami, FL

Gillian Hotz, Ph.D. 1095 NW 14th Ter Miami, FL 33136 [email protected] 305-243-2074

Gillian A. Hotz, PhD is a research professor at the University of Miami Miller School of Medicine and a nationally recognized behavioral neuroscientist and expert in pediatric and adult neurotrauma, concussion management, and neurorehabilitation. Dr. Hotz is the director of the KiDZ Neuroscience Center, WalkSafe, and BikeSafe programs.

Purpose Largely, research on adolescent sports-related concussion (SRC) has focused on public school athletes. SRCs of private school athletes have been studied less and may differ due to differences between school types.

Methods SRCs between Miami-Dade County high school athletes at trained public (n = 1088), trained private (n = 272), and untrained private (n = 79) were compared. Outcomes included days between date of injury (DOI) and clinic date, days between DOI and post-injury ImPACT retest, days withheld, return to play (RTP), ImPACT baseline and post-injury retest completion, and academic accommodation status.

Results Trained public and trained private groups had similar days between DOI and clinic date, days withheld, and percentage who RTP. Differences between the trained public and untrained private groups existed for RTP but not for days between DOI and clinic date or days withheld. Private group athletes were more likely to receive academic accommodations.

Conclusions Public and private high schools trained on the same SRC protocol did not have significantly different outcomes. The untrained private schools, however, had worse outcomes compared to the public group.

Application In Sports SRC outcomes in both public and private high schools may benefit from SRC education, training, an established protocol, and use of a management system.

Keywords : youth athletes, concussion recognition, concussion management, private schools, sports

Each year, an estimated 1.6 to 3.8 million sports-related concussions (SRCs) occur in the United States (1). While the nearly 8 million high school athletes participating in sports annually benefit from the improved social, psychological, and physical health gained from playing sports (2, 3), there is also an ongoing risk of injury due to consistent athlete-exposure (4). SRCs are understandably a concern for high school aged athletes due to the short-term and potentially lifelong behavioral, cognitive, emotional, physical, and psychological effects they can produce (1, 5). These consequences can be particularly worrisome as this population is already experiencing their own ongoing physical and cognitive development changes that can negatively be affected by an SRC (6). Understanding risk factors contributing to adolescent SRCs and what may lead to differences in outcomes is therefore imperative for identifying those most at risk and ensuring the proper management and treatment resources are in place.

Thus far, an overwhelming majority of research on SRCs has focused on or included samples of public high school athletes as opposed to private high school athletes. One example is the High School Sports-Related Injury Surveillance Study, Reporting Information Online (RIO) (7). The High School RIO is an internet-based data collection tool that captures athletic exposures and injury events through athletic trainers (ATs) that report data. It is often used as a source of SRC data for research (4). In the most recent report, nearly 80% of the participating high schools were public with the rest being private (7). Additionally, other studies on SRC incidence and trends have included only athletes from public high schools (8.) The lack of private high school inclusion in adolescent SRC research is an important consideration because known distinctions between public and private high schools possibly lead to differences in SRC incidence and outcomes (4). These include differences in school size, support services and resources, student racial/ethnic backgrounds, rigorous academic programs, and socioeconomics (9).

While there has been recent research that details private high school athlete SRC experiences and reporting behavior (4, 10), there is still a need for continued research into private high school SRC outcomes. Specifically, it would be important to examine how SRC outcomes differ between public and private high schools. Therefore, the purpose of this study was to compare SRC outcomes between public high schools who received specific concussion training and education to private high schools who received the same training and private high schools who did not receive training on the same SRC protocol. The goal of using these three distinct groups was to examine whether differences in SRC outcomes would be a result of differences in SRC education, training, and protocol.

Participants and Procedures

This study included Miami-Dade County (MDC) public and private high school athletes with an SRC that occurred in a practice or game between August 1 st , 2012, and July 31 st , 2022. All athletes were treated at the University of Miami Miller School of Medicine’s Concussion Clinic, UConcussion (UCC). Athletes that sustained an SRC outside of the study period were excluded as well as those with an SRC that did not occur during an MDC public or private high school practice or competition. If an athlete was treated at a provider other than the UCC, they were also excluded. 

 The UCC clinical team hosts an annual SRC training and educational workshop for MDC public high school ATs and athletic directors (ADs). In these workshops, ATs and ADs are trained on how to use the Six Steps to Play Safe protocol (11) and how to administer ImPACT (12) concussion tests. The UCC also makes available specialty concussion clinics where athletes with a suspected SRC can be referred to for management and treatment. The UCC similarly partners with and provides training and education to 8 private high schools within MDC. While athletes at other private high schools within MDC can still be referred to and receive treatment at the UCC, ATs and ADs at these high schools are not provided with the same educational workshops and training on the Six Steps to Play Safe protocol (11). In this study, there were 35 trained public, 8 trained private, and 29 untrained private high schools that were grouped as either “trained public,” “trained private,” or “untrained private,” respectively.              

The Six Steps to Play Safe (11) is a standardized protocol that can be used to manage an athlete’s SRC and safe return to play (RTP) and return to school during recovery (Figure 1). Included in this protocol are, in order, pre-season ImPACT (12) baseline testing, AT sideline testing, post-injury ImPACT testing, SRC clinic follow-up, gradual RTP and return to learn protocols, and SRC injury surveillance form completion.

Variables Reported variables were collected during UCC visits and from surveillance reporting by ATs. Athlete information in the study included demographics and the sport played when the injury occurred. SRC specific information was also reported and included date of injury (DOI), days between DOI and first clinic date, days between DOI and post-injury ImPACT retest, RTP status (yes/no), and days between DOI and RTP (days withheld). To eliminate the few extreme outliers, athletes were only included in days between DOI and first clinic date as well as days withheld mean calculations if the value for these variables was < 120 days. For similar reasons, only athletes with days between DOI and post-injury ImPACT retest < 30 days were included in the calculation. Whether an athlete received academic accommodations was included as a variable because previous research (13) suggests that private high school students experience particularly high levels of stress due to concerns about academic performance and school requests, which potentially impacts whether academic accommodations are prescribed. The percentage of athletes who experienced loss of consciousness (LOC) was also reported because LOC indicates a potentially more severe SRC and is associated with longer recovery than SRCs without LOC (14). Athlete ImPACT (12) baseline testing and post-injury data from the ImPACT test online database was included and used to determine whether athletes had completed a baseline ImPACT test and/or a post-injury ImPACT retest. ImPACT testing comparisons were only included for the trained public and trained private high schools since untrained private high schools either did not use ImPACT or did not grant the UCC access to their records.

Data Analysis Data analysis was performed using R 4.2.2. Athletes sustaining an SRC from MDC public high schools were compared with athletes from private schools between 2012-2022. The eight private schools were particularly selected because they followed a similar protocol and received the same SRC education as the public schools. The other 29 private schools did not receive the training or follow the protocol. For continuous data in the normal distribution like “Age”, mean and standard deviation were reported. For categorical data, such as “Gender”, data was presented as frequency and percentage. For those variables with important clinical significance, such as “Days withheld”, data was reported as median and interquartile range. Propensity score matching was performed to match the public schools with the eight private schools who received similar SRC training. SRC outcomes were therefore compared between trained public and trained private schools before and after matching. This was done to confirm whether one hypothesis, that public and private schools trained on the same SRC protocol would not differ in SRC outcomes, would be true when baseline covariates were and were not controlled for between the groups. Sample T-test was used to detect the significant difference for quantitative data in the normal distribution. The Wilcoxon test was used for quantitative data in non-normal distribution. The Chi-Square test was used to detect significant differences in categorical data. Statistical significance was set at < 0.05.

Participant Demographics A total of 1,088 public, 272 trained private, and 79 untrained private athletes were treated at the UCC during the study period and are included in this study. The average age was similar for each group (16.5 and 16.2). While there were more male than female athletes in all three groups, the percentage of athletes that were female was greater in the trained (38.6%) and untrained (38.0%) private groups than the public group (25.9%). In both the trained and untrained private groups, a greater percentage of athletes were White (28.5% and 25.3%) or Hispanic (62.6% and 68.0%) compared to public athletes (8.0% White, 56.4% Hispanic). The public group instead had a greater percentage of Black athletes (30.9%) than the trained (24.7%) and untrained (6.7%) private groups. Across all three groups, football accounted for the greatest percentage of SRCs but was more prevalent in the public (58.3%) than both private groups (36.4% and 39.2%) (Table 1).

Comparing Trained Public and Trained Private High Schools SRCs Data from trained public and trained private high schools was compared to determine if there were any differences in outcomes between public and private high schools that were trained using the same protocol and program. There were no differences between the groups for days between DOI and first clinic date (P = 0.1), days withheld (P = 0.83), post-injury retest completion (P = 0.06), and RTP (P = 0.30). The average days between DOI and post-injury ImPACT retesting was smaller (P < 0.001) for the public (3 days) than trained private (6 days) group. The public group also had a greater percentage of athletes who completed ImPACT baseline testing (88.5% vs. 80.1%; P < 0.001). The trained private group had a significantly greater percentage of athletes who had academic accommodations (P < 0.001) and experienced LOC (P < 0.001) (Table 2).

After matching, groups had similar demographic characteristics for age, sex, race, grade, and sport (Table 3). Outcomes between the matched groups were also compared, and there were no differences for days between DOI and first clinic date, days withheld, percentage of athletes who completed ImPACT baseline testing and post-injury retesting, and RTP (Table 4). However, average days between DOI and post-injury ImPACT retest was smaller for the public group (4 vs. 6 days, P < 0.001). The public-school group was also more likely to have experienced LOC (P < 0.001) and not receive academic accommodations (P < 0.001).

Comparing Trained Public and Untrained Private High School SRCs Trained public and untrained private groups did not differ in average days between DOI and first clinic date (P = 0.40) or days withheld (P = 0.40). A significantly greater percentage of the public group did RTP (91.9% vs. 81.0%; P = 0.002). More of the athletes in the untrained private group received academic accommodations (P < 0.001) and experienced LOC (P < 0.001) than did the trained public group (Table 5).

Understanding risk factors, whether demographical (e.g., sex, age) or injury event-related (e.g., sport, mechanism of injury), that are associated with differences in SRC outcomes are important for ensuring that those most at risk receive proper SRC treatment and resources. One potential risk factor that was explored in this study was whether an athlete was from a public or private high school. Historically, most research on SRC risk and outcomes has been conducted using public high school athletes (4). This study provides further insight into how SRC outcomes between high school athletes differ based on the type of school attended and if a dedicated SRC protocol and education can help mitigate any differences.

While football accounted for the greatest percentage of SRCs in all three groups, its contribution was roughly 20% percent more in the public group than both private groups. Other sports, including soccer, basketball, and volleyball, were more prevalent in both private school groups. The distribution of sport played during the SRC injury event likely differed between public and private groups because private schools offer a variety of sport options, like crew and sailing, that were not available at public schools. This availability may have impacted the popularity of sports and participation numbers as private school athletes had a greater number of sports to choose from.

To our knowledge, there is only one other study (15) that directly compares SRC experiences between public and private schools. In that study, private school athletes were twice as likely to report a history of SRC compared to public school athletes, but there was no difference in RTP timelines between athletes at the different types of school (15). While the current study did not compare history of SRC between school types, analysis was performed to compare rates of RTP. There was no significant difference between the trained public and trained private school groups for RTP percentage or days withheld (Table 2), similar to the other study that concluded no difference in RTP. After matching, there was still no difference in RTP percentage or days withheld between these groups (Table 4). The untrained private group, however, had significantly less athletes RTP than the trained public group (Table 5). The UCC is a specialized concussion program that provides comprehensive SRC management and treatment, but the program also provides continuing education and a standardized protocol to the trained public and private high schools to better identify, manage, and treat athletes with an SRC (11). Athletes at these participating trained high schools potentially benefited from the coordinated and structured care they receive as a result of these trainings and partnerships, which may have led to better RTP outcomes compared to the untrained private group. These results also suggest that SRC outcomes do not necessarily depend on school type and the systematic differences between public and private schools (4, 9), but instead on AT and AD SRC education and if an SRC protocol is in place and being followed. Additionally, these results also indicate the positive effect an available and established SRC program and protocol with clinicians trained on SRC management and treatment can have on SRC outcomes. Another finding was that the trained public and untrained private groups did not differ in average days between DOI and first clinic date (Table 5). Systematic differences in socioeconomics between public and private high schools (9) may explain why the trained public group did not have significantly fewer average days between DOI and first clinic date than the untrained private group, which was the initial hypothesized result. There is well established evidence (16) that supports a relationship between socioeconomics and access to healthcare, and socioeconomic differences between school type may have led to barriers, including transportation, time, and costs, that delayed public athletes from getting into the UCC (17). Yet, there was also no difference between trained public and trained private groups for average days between DOI and first clinic date in both unmatched and matched comparisons (Tables 2 and 4), suggesting that UCC’s partnership with these schools and the flexibility it provides by offering both on-site and virtual appointments may have alleviated any potential differences. These findings also indicate that educating ATs and ADs on the risks of SRCs leads to quicker identification and subsequent appointments.

The percentage of athletes who received academic accommodations after an SRC was significantly greater for both the trained (unmatched and matched) and untrained private school groups compared to the trained public school group. During recovery from an SRC, athletes may have post SRC symptoms that can interfere with their ability to participate and function in the classroom setting (18). Consequently, return to learn protocols and academic accommodations are often provided to the athlete to help reintegrate them into classes but also prevent worsening symptoms (19, 20). Previous research (13) shows that private school students face a particularly high level of academic pressure, potentially due to more rigorous academic programs (9), which could explain why a greater percentage of private groups in this study received more academic accommodations. These additional academic accommodations may have been provided to reduce the burden private group athletes felt about their academic responsibilities or at the request of academic advisors employed at these schools. However, it is important to ensure that all athletes with a sustained SRC receive any appropriate and necessary academic accommodation, regardless of school type attended, to prevent further symptom development.

Limitations This study is not without limitations. All participants in this study were athletes that attended a public or private high school in MDC. Results may not be generalizable to other playing levels, like youth, middle schools, and college, nor to public or private high schools in other counties. Additionally, while other counties may have their own SRC surveillance system, they may not have a program, such as the UConcussion program, that provides ATs with additional SRC training and encourages timely, accurate reporting. A larger sample population in all three groups would have also been beneficial and provided more evidence on the impact of SRC education and protocol on SRC outcomes in the high school setting.

Public and private high school groups trained on the same SRC protocol did not have significantly different SRC outcomes. The untrained private high school group, however, had worse SRC outcomes compared to the public school group, suggesting that SRC outcomes in the high school setting may benefit from education, training, and an established SRC protocol and program and not on whether the school is public or private.

Applications In Sport

An inherent risk of playing sports is injuries, and SRCs are a particularly concerning injury for high school athletes, especially those playing contact sports. Ensuring those responsible for helping to manage SRCs in high schools are educated about SRCs is important, and a collaborative approach to treating and managing SRCs has been recommended (20). As suggested by this study, all high school personnel involved with athletics should be offered SRC management training and education to help improve outcomes of those that sustain an SRC. Additionally, an SRC protocol, like the Six Steps to Play Safe (11), should be established and can include:

• Pre-season baseline testing, using computer-based tests such as ImPACT (12)
• Sideline testing after a potential SRC injury (SCAT5, Balance Error Scoring System (BESS), etc.)
• Post-testing after a suspected SRC (to compare neurocognitive scores to pre-season baseline tests)
• Clinic appointments with a healthcare professional trained in SRC who can evaluate tests and make recommendations
• Gradual RTP and return to learn protocol after the athlete has been examined by a professional and is asymptomatic
• Injury surveillance system reporting by ATs

ACKNOWLEDGEMENTS The authors would like to thank: Dr. Kaplan and the UHealth Sports Medicine Clinic and Staff, the Division of Athletics and Activities for the Miami-Dade County Public Schools, all Miami-Dade County High School Certified Athletic Trainers, previous UConcussion team members, Dr Kester Nedd who served as medical director of the program from 2012 to 2019, current medical director Dr. Abraham Chileuitt, and The Miami Dolphin Foundation for supporting countywide ImPACT testing and educational workshops. We also want to thank David Goldstein and the Goldstein Family for the development of the Countywide Concussion Care Program and their initial and continued support. The project was supported by the University of Miami Clinical and Translational Science Institute.

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Sport psychology and performance meta-analyses: A systematic review of the literature

Roles Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Department of Kinesiology and Sport Management, Texas Tech University, Lubbock, Texas, United States of America, Education Academy, Vytautas Magnus University, Kaunas, Lithuania

Roles Data curation, Methodology, Writing – original draft

Affiliation Department of Psychological Sciences, Texas Tech University, Lubbock, Texas, United States of America

Roles Data curation, Methodology

Roles Writing – original draft, Writing – review & editing

Affiliation Department of Kinesiology and Sport Management, Honors College, Texas Tech University, Lubbock, Texas, United States of America

Roles Data curation, Methodology, Writing – original draft, Writing – review & editing

Affiliation Faculty of Education, Health and Well-Being, University of Wolverhampton, Walsall, West Midlands, United Kingdom

Roles Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

Affiliation Division of Research & Innovation, University of Southern Queensland, Toowoomba, Queensland, Australia

• Marc Lochbaum, 
• Elisabeth Stoner, 
• Tristen Hefner, 
• Sydney Cooper, 
• Andrew M. Lane, 
• Peter C. Terry

• Published: February 16, 2022
• https://doi.org/10.1371/journal.pone.0263408
• Peer Review
• Reader Comments

Sport psychology as an academic pursuit is nearly two centuries old. An enduring goal since inception has been to understand how psychological techniques can improve athletic performance. Although much evidence exists in the form of meta-analytic reviews related to sport psychology and performance, a systematic review of these meta-analyses is absent from the literature. We aimed to synthesize the extant literature to gain insights into the overall impact of sport psychology on athletic performance. Guided by the PRISMA statement for systematic reviews, we reviewed relevant articles identified via the EBSCOhost interface. Thirty meta-analyses published between 1983 and 2021 met the inclusion criteria, covering 16 distinct sport psychology constructs. Overall, sport psychology interventions/variables hypothesized to enhance performance (e.g., cohesion, confidence, mindfulness) were shown to have a moderate beneficial effect ( d = 0.51), whereas variables hypothesized to be detrimental to performance (e.g., cognitive anxiety, depression, ego climate) had a small negative effect ( d = -0.21). The quality rating of meta-analyses did not significantly moderate the magnitude of observed effects, nor did the research design (i.e., intervention vs. correlation) of the primary studies included in the meta-analyses. Our review strengthens the evidence base for sport psychology techniques and may be of great practical value to practitioners. We provide recommendations for future research in the area.

Citation: Lochbaum M, Stoner E, Hefner T, Cooper S, Lane AM, Terry PC (2022) Sport psychology and performance meta-analyses: A systematic review of the literature. PLoS ONE 17(2): e0263408. https://doi.org/10.1371/journal.pone.0263408

Editor: Claudio Imperatori, European University of Rome, ITALY

Received: September 28, 2021; Accepted: January 18, 2022; Published: February 16, 2022

Copyright: © 2022 Lochbaum et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Sport performance matters. Verifying its global importance requires no more than opening a newspaper to the sports section, browsing the internet, looking at social media outlets, or scanning abundant sources of sport information. Sport psychology is an important avenue through which to better understand and improve sport performance. To date, a systematic review of published sport psychology and performance meta-analyses is absent from the literature. Given the undeniable importance of sport, the history of sport psychology in academics since 1830, and the global rise of sport psychology journals and organizations, a comprehensive systematic review of the meta-analytic literature seems overdue. Thus, we aimed to consolidate the existing literature and provide recommendations for future research.

The development of sport psychology

The history of sport psychology dates back nearly 200 years. Terry [ 1 ] cites Carl Friedrich Koch’s (1830) publication titled [in translation] Calisthenics from the Viewpoint of Dietetics and Psychology [ 2 ] as perhaps the earliest publication in the field, and multiple commentators have noted that sport psychology experiments occurred in the world’s first psychology laboratory, established by Wilhelm Wundt at the University of Leipzig in 1879 [ 1 , 3 ]. Konrad Rieger’s research on hypnosis and muscular endurance, published in 1884 [ 4 ] and Angelo Mosso’s investigations of the effects of mental fatigue on physical performance, published in 1891 [ 5 ] were other early landmarks in the development of applied sport psychology research. Following the efforts of Koch, Wundt, Rieger, and Mosso, sport psychology works appeared with increasing regularity, including Philippe Tissié’s publications in 1894 [ 6 , 7 ] on psychology and physical training, and Pierre de Coubertin’s first use of the term sport psychology in his La Psychologie du Sport paper in 1900 [ 8 ]. In short, the history of sport psychology and performance research began as early as 1830 and picked up pace in the latter part of the 19 th century. Early pioneers, who helped shape sport psychology include Wundt, recognized as the “father of experimental psychology”, Tissié, the founder of French physical education and Legion of Honor awardee in 1932, and de Coubertin who became the father of the modern Olympic movement and founder of the International Olympic Committee.

Sport psychology flourished in the early 20 th century [see 1, 3 for extensive historic details]. For instance, independent laboratories emerged in Berlin, Germany, established by Carl Diem in 1920; in St. Petersburg and Moscow, Russia, established respectively by Avksenty Puni and Piotr Roudik in 1925; and in Champaign, Illinois USA, established by Coleman Griffith, also in 1925. The period from 1950–1980 saw rapid strides in sport psychology, with Franklin Henry establishing this field of study as independent of physical education in the landscape of American and eventually global sport science and kinesiology graduate programs [ 1 ]. In addition, of great importance in the 1960s, three international sport psychology organizations were established: namely, the International Society for Sport Psychology (1965), the North American Society for the Psychology of Sport and Physical Activity (1966), and the European Federation of Sport Psychology (1969). Since that time, the Association of Applied Sport Psychology (1986), the South American Society for Sport Psychology (1986), and the Asian-South Pacific Association of Sport Psychology (1989) have also been established.

The global growth in academic sport psychology has seen a large number of specialist publications launched, including the following journals: International Journal of Sport Psychology (1970), Journal of Sport & Exercise Psychology (1979), The Sport Psychologist (1987), Journal of Applied Sport Psychology (1989), Psychology of Sport and Exercise (2000), International Journal of Sport and Exercise Psychology (2003), Journal of Clinical Sport Psychology (2007), International Review of Sport and Exercise Psychology (2008), Journal of Sport Psychology in Action (2010), Sport , Exercise , and Performance Psychology (2014), and the Asian Journal of Sport & Exercise Psychology (2021).

In turn, the growth in journal outlets has seen sport psychology publications burgeon. Indicative of the scale of the contemporary literature on sport psychology, searches completed in May 2021 within the Web of Science Core Collection, identified 1,415 publications on goal setting and sport since 1985; 5,303 publications on confidence and sport since 1961; and 3,421 publications on anxiety and sport since 1980. In addition to academic journals, several comprehensive edited textbooks have been produced detailing sport psychology developments across the world, such as Hanrahan and Andersen’s (2010) Handbook of Applied Sport Psychology [ 9 ], Schinke, McGannon, and Smith’s (2016) International Handbook of Sport Psychology [ 10 ], and Bertollo, Filho, and Terry’s (2021) Advancements in Mental Skills Training [ 11 ] to name just a few. In short, sport psychology is global in both academic study and professional practice.

Meta-analysis in sport psychology

Several meta-analysis guides, computer programs, and sport psychology domain-specific primers have been popularized in the social sciences [ 12 , 13 ]. Sport psychology academics have conducted quantitative reviews on much studied constructs since the 1980s, with the first two appearing in 1983 in the form of Feltz and Landers’ meta-analysis on mental practice [ 14 ], which included 98 articles dating from 1934, and Bond and Titus’ cross-disciplinary meta-analysis on social facilitation [ 15 ], which summarized 241 studies including Triplett’s (1898) often-cited study of social facilitation in cycling [ 16 ]. Although much meta-analytic evidence exists for various constructs in sport and exercise psychology [ 12 ] including several related to performance [ 17 ], the evidence is inconsistent. For example, two meta-analyses, both ostensibly summarizing evidence of the benefits to performance of task cohesion [ 18 , 19 ], produced very different mean effects ( d = .24 vs d = 1.00) indicating that the true benefit lies somewhere in a wide range from small to large. Thus, the lack of a reliable evidence base for the use of sport psychology techniques represents a significant gap in the knowledge base for practitioners and researchers alike. A comprehensive systematic review of all published meta-analyses in the field of sport psychology has yet to be published.

Purpose and aim

We consider this review to be both necessary and long overdue for the following reasons: (a) the extensive history of sport psychology and performance research; (b) the prior publication of many meta-analyses summarizing various aspects of sport psychology research in a piecemeal fashion [ 12 , 17 ] but not its totality; and (c) the importance of better understanding and hopefully improving sport performance via the use of interventions based on solid evidence of their efficacy. Hence, we aimed to collate and evaluate this literature in a systematic way to gain improved understanding of the impact of sport psychology variables on sport performance by construct, research design, and meta-analysis quality, to enhance practical knowledge of sport psychology techniques and identify future lines of research inquiry. By systematically reviewing all identifiable meta-analytic reviews linking sport psychology techniques with sport performance, we aimed to evaluate the strength of the evidence base underpinning sport psychology interventions.

Materials and methods

This systematic review of meta-analyses followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 20 ]. We did not register our systematic review protocol in a database. However, we specified our search strategy, inclusion criteria, data extraction, and data analyses in advance of writing our manuscript. All details of our work are available from the lead author. Concerning ethics, this systematic review received a waiver from Texas Tech University Human Subject Review Board as it concerned archival data (i.e., published meta-analyses).

Eligibility criteria

Published meta-analyses were retained for extensive examination if they met the following inclusion criteria: (a) included meta-analytic data such as mean group, between or within-group differences or correlates; (b) published prior to January 31, 2021; (c) published in a peer-reviewed journal; (d) investigated a recognized sport psychology construct; and (e) meta-analyzed data concerned with sport performance. There was no language of publication restriction. To align with our systematic review objectives, we gave much consideration to study participants and performance outcomes. Across multiple checks, all authors confirmed study eligibility. Three authors (ML, AL, and PT) completed the final inclusion assessments.

Information sources

Authors searched electronic databases, personal meta-analysis history, and checked with personal research contacts. Electronic database searches occurred in EBSCOhost with the following individual databases selected: APA PsycINFO, ERIC, Psychology and Behavioral Sciences Collection, and SPORTDiscus. An initial search concluded October 1, 2020. ML, AL, and PT rechecked the identified studies during the February–March, 2021 period, which resulted in the identification of two additional meta-analyses [ 21 , 22 ].

Search protocol

ML and ES initially conducted independent database searches. For the first search, ML used the following search terms: sport psychology with meta-analysis or quantitative review and sport and performance or sport* performance. For the second search, ES utilized a sport psychology textbook and used the chapter title terms (e.g., goal setting). In EBSCOhost, both searches used the advanced search option that provided three separate boxes for search terms such as box 1 (sport psychology), box 2 (meta-analysis), and box 3 (performance). Specific details of our search strategy were:

Search by ML:

• sport psychology, meta-analysis, sport and performance
• sport psychology, meta-analysis or quantitative review, sport* performance
• sport psychology, quantitative review, sport and performance
• sport psychology, quantitative review, sport* performance

Search by ES:

• mental practice or mental imagery or mental rehearsal and sports performance and meta-analysis
• goal setting and sports performance and meta-analysis
• anxiety and stress and sports performance and meta-analysis
• competition and sports performance and meta-analysis
• diversity and sports performance and meta-analysis
• cohesion and sports performance and meta-analysis
• imagery and sports performance and meta-analysis
• self-confidence and sports performance and meta-analysis
• concentration and sports performance and meta-analysis
• athletic injuries and sports performance and meta-analysis
• overtraining and sports performance and meta-analysis
• children and sports performance and meta-analysis

The following specific search of the EBSCOhost with SPORTDiscus, APA PsycINFO, Psychology and Behavioral Sciences Collection, and ERIC databases, returned six results from 2002–2020, of which three were included [ 18 , 19 , 23 ] and three were excluded because they were not meta-analyses.

• Box 1 cohesion
• Box 2 sports performance
• Box 3 meta-analysis

Study selection

As detailed in the PRISMA flow chart ( Fig 1 ) and the specified inclusion criteria, a thorough study selection process was used. As mentioned in the search protocol, two authors (ML and ES) engaged independently with two separate searches and then worked together to verify the selected studies. Next, AL and PT examined the selected study list for accuracy. ML, AL, and PT, whilst rating the quality of included meta-analyses, also re-examined all selected studies to verify that each met the predetermined study inclusion criteria. Throughout the study selection process, disagreements were resolved through discussion until consensus was reached.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0263408.g001

Data extraction process

Initially, ML, TH, and ES extracted data items 1, 2, 3 and 8 (see Data items). Subsequently, ML, AL, and PT extracted the remaining data (items 4–7, 9, 10). Checks occurred during the extraction process for potential discrepancies (e.g., checking the number of primary studies in a meta-analysis). It was unnecessary to contact any meta-analysis authors for missing information or clarification during the data extraction process because all studies reported the required information. Across the search for meta-analyses, all identified studies were reported in English. Thus, no translation software or searching out a native speaker occurred. All data extraction forms (e.g., data items and individual meta-analysis quality) are available from the first author.

To help address our main aim, we extracted the following information from each meta-analysis: (1) author(s); (2) publication year; (3) construct(s); (4) intervention based meta-analysis (yes, no, mix); (5) performance outcome(s) description; (6) number of studies for the performance outcomes; (7) participant description; (8) main findings; (9) bias correction method/results; and (10) author(s) stated conclusions. For all information sought, we coded missing information as not reported.

Individual meta-analysis quality

ML, AL, and PT independently rated the quality of individual meta-analysis on the following 25 points found in the PRISMA checklist [ 20 ]: title; abstract structured summary; introduction rationale, objectives, and protocol and registration; methods eligibility criteria, information sources, search, study selection, data collection process, data items, risk of bias of individual studies, summary measures, synthesis of results, and risk of bias across studies; results study selection, study characteristics, risk of bias within studies, results of individual studies, synthesis of results, and risk of bias across studies; discussion summary of evidence, limitations, and conclusions; and funding. All meta-analyses were rated for quality by two coders to facilitate inter-coder reliability checks, and the mean quality ratings were used in subsequent analyses. One author (PT), having completed his own ratings, received the incoming ratings from ML and AL and ran the inter-coder analysis. Two rounds of ratings occurred due to discrepancies for seven meta-analyses, mainly between ML and AL. As no objective quality categorizations (i.e., a point system for grouping meta-analyses as poor, medium, good) currently exist, each meta-analysis was allocated a quality score of up to a maximum of 25 points. All coding records are available upon request.

Planned methods of analysis

Several preplanned methods of analysis occurred. We first assessed the mean quality rating of each meta-analysis based on our 25-point PRISMA-based rating system. Next, we used a median split of quality ratings to determine whether standardized mean effects (SMDs) differed by the two formed categories, higher and lower quality meta-analyses. Meta-analysis authors reported either of two different effect size metrics (i.e., r and SMD); hence we converted all correlational effects to SMD (i.e., Cohen’s d ) values using an online effect size calculator ( www.polyu.edu.hk/mm/effectsizefaqs/calculator/calculator.html ). We interpreted the meaningfulness of effects based on Cohen’s interpretation [ 24 ] with 0.20 as small, 0.50 as medium, 0.80 as large, and 1.30 as very large. As some psychological variables associate negatively with performance (e.g., confusion [ 25 ], cognitive anxiety [ 26 ]) whereas others associate positively (e.g., cohesion [ 23 ], mental practice [ 14 ]), we grouped meta-analyses according to whether the hypothesized effect with performance was positive or negative, and summarized the overall effects separately. By doing so, we avoided a scenario whereby the demonstrated positive and negative effects canceled one another out when combined. The effect of somatic anxiety on performance, which is hypothesized to follow an inverted-U relationship, was categorized as neutral [ 35 ]. Last, we grouped the included meta-analyses according to whether the primary studies were correlational in nature or involved an intervention and summarized these two groups of meta-analyses separately.

Study characteristics

Table 1 contains extracted data from 30 meta-analyses meeting the inclusion criteria, dating from 1983 [ 14 ] to 2021 [ 21 ]. The number of primary studies within the meta-analyses ranged from three [ 27 ] to 109 [ 28 ]. In terms of the description of participants included in the meta-analyses, 13 included participants described simply as athletes, whereas other meta-analyses identified a mix of elite athletes (e.g., professional, Olympic), recreational athletes, college-aged volunteers (many from sport science departments), younger children to adolescents, and adult exercisers. Of the 30 included meta-analyses, the majority ( n = 18) were published since 2010. The decadal breakdown of meta-analyses was 1980–1989 ( n = 1 [ 14 ]), 1990–1999 ( n = 6 [ 29 – 34 ]), 2000–2009 ( n = 5 [ 23 , 25 , 26 , 35 , 36 ]), 2010–2019 ( n = 12 [ 18 , 19 , 22 , 27 , 37 – 43 , 48 ]), and 2020–2021 ( n = 6 [ 21 , 28 , 44 – 47 ]).

https://doi.org/10.1371/journal.pone.0263408.t001

As for the constructs covered, we categorized the 30 meta-analyses into the following areas: mental practice/imagery [ 14 , 29 , 30 , 42 , 46 , 47 ], anxiety [ 26 , 31 , 32 , 35 ], confidence [ 26 , 35 , 36 ], cohesion [ 18 , 19 , 23 ], goal orientation [ 22 , 44 , 48 ], mood [ 21 , 25 , 34 ], emotional intelligence [ 40 ], goal setting [ 33 ], interventions [ 37 ], mindfulness [ 27 ], music [ 28 ], neurofeedback training [ 43 ], perfectionism [ 39 ], pressure training [ 45 ], quiet eye training [ 41 ], and self-talk [ 38 ]. Multiple effects were generated from meta-analyses that included more than one construct (e.g., tension, depression, etc. [ 21 ]; anxiety and confidence [ 26 ]). In relation to whether the meta-analyses included in our review assessed the effects of a sport psychology intervention on performance or relationships between psychological constructs and performance, 13 were intervention-based, 14 were correlational, two included a mix of study types, and one included a large majority of cross-sectional studies ( Table 1 ).

A wide variety of performance outcomes across many sports was evident, such as golf putting, dart throwing, maximal strength, and juggling; or categorical outcomes such as win/loss and Olympic team selection. Given the extensive list of performance outcomes and the incomplete descriptions provided in some meta-analyses, a clear categorization or count of performance types was not possible. Sufficient to conclude, researchers utilized many performance outcomes across a wide range of team and individual sports, motor skills, and strength and aerobic tasks.

Effect size data and bias correction

To best summarize the effects, we transformed all correlations to SMD values (i.e., Cohen’s d ). Across all included meta-analyses shown in Table 2 and depicted in Fig 2 , we identified 61 effects. Having corrected for bias, effect size values were assessed for meaningfulness [ 24 ], which resulted in 15 categorized as negligible (< ±0.20), 29 as small (±0.20 to < 0.50), 13 as moderate (±0.50 to < 0.80), 2 as large (±0.80 to < 1.30), and 1 as very large (≥ 1.30).

https://doi.org/10.1371/journal.pone.0263408.g002

https://doi.org/10.1371/journal.pone.0263408.t002

Study quality rating results and summary analyses

Following our PRISMA quality ratings, intercoder reliability coefficients were initially .83 (ML, AL), .95 (ML, PT), and .90 (AL, PT), with a mean intercoder reliability coefficient of .89. To achieve improved reliability (i.e., r mean > .90), ML and AL re-examined their ratings. As a result, intercoder reliability increased to .98 (ML, AL), .96 (ML, PT), and .92 (AL, PT); a mean intercoder reliability coefficient of .95. Final quality ratings (i.e., the mean of two coders) ranged from 13 to 25 ( M = 19.03 ± 4.15). Our median split into higher ( M = 22.83 ± 1.08, range 21.5–25, n = 15) and lower ( M = 15.47 ± 2.42, range 13–20.5, n = 15) quality groups produced significant between-group differences in quality ( F 1,28 = 115.62, p < .001); hence, the median split met our intended purpose. The higher quality group of meta-analyses were published from 2015–2021 (median 2018) and the lower quality group from 1983–2014 (median 2000). It appears that meta-analysis standards have risen over the years since the PRISMA criteria were first introduced in 2009. All data for our analyses are shown in Table 2 .

Table 3 contains summary statistics with bias-corrected values used in the analyses. The overall mean effect for sport psychology constructs hypothesized to have a positive impact on performance was of moderate magnitude ( d = 0.51, 95% CI = 0.42, 0.58, n = 36). The overall mean effect for sport psychology constructs hypothesized to have a negative impact on performance was small in magnitude ( d = -0.21, 95% CI -0.31, -0.11, n = 24). In both instances, effects were larger, although not significantly so, among meta-analyses of higher quality compared to those of lower quality. Similarly, mean effects were larger but not significantly so, where reported effects in the original studies were based on interventional rather than correlational designs. This trend only applied to hypothesized positive effects because none of the original studies in the meta-analyses related to hypothesized negative effects used interventional designs.

https://doi.org/10.1371/journal.pone.0263408.t003

In this systematic review of meta-analyses, we synthesized the available evidence regarding effects of sport psychology interventions/constructs on sport performance. We aimed to consolidate the literature, evaluate the potential for meta-analysis quality to influence the results, and suggest recommendations for future research at both the single study and quantitative review stages. During the systematic review process, several meta-analysis characteristics came to light, such as the number of meta-analyses of sport psychology interventions (experimental designs) compared to those summarizing the effects of psychological constructs (correlation designs) on performance, the number of meta-analyses with exclusively athletes as participants, and constructs featuring in multiple meta-analyses, some of which (e.g., cohesion) produced very different effect size values. Thus, although our overall aim was to evaluate the strength of the evidence base for use of psychological interventions in sport, we also discuss the impact of these meta-analysis characteristics on the reliability of the evidence.

When seen collectively, results of our review are supportive of using sport psychology techniques to help improve performance and confirm that variations in psychological constructs relate to variations in performance. For constructs hypothesized to have a positive effect on performance, the mean effect strength was moderate ( d = 0.51) although there was substantial variation between constructs. For example, the beneficial effects on performance of task cohesion ( d = 1.00) and self-efficacy ( d = 0.82) are large, and the available evidence base for use of mindfulness interventions suggests a very large beneficial effect on performance ( d = 1.35). Conversely, some hypothetically beneficial effects (2 of 36; 5.6%) were in the negligible-to-small range (0.15–0.20) and most beneficial effects (19 of 36; 52.8%) were in the small-to-moderate range (0.22–0.49). It should be noted that in the world of sport, especially at the elite level, even a small beneficial effect on performance derived from a psychological intervention may prove the difference between success and failure and hence small effects may be of great practical value. To put the scale of the benefits into perspective, an authoritative and extensively cited review of healthy eating and physical activity interventions [ 49 ] produced an overall pooled effect size of 0.31 (compared to 0.51 for our study), suggesting sport psychology interventions designed to improve performance are generally more effective than interventions designed to promote healthy living.

Among hypothetically negative effects (e.g., ego climate, cognitive anxiety, depression), the mean detrimental effect was small ( d = -0.21) although again substantial variation among constructs was evident. Some hypothetically negative constructs (5 of 24; 20.8%) were found to actually provide benefits to performance, albeit in the negligible range (0.02–0.12) and only two constructs (8.3%), both from Lochbaum and colleagues’ POMS meta-analysis [ 21 ], were shown to negatively affect performance above a moderate level (depression: d = -0.64; total mood disturbance, which incorporates the depression subscale: d = -0.84). Readers should note that the POMS and its derivatives assess six specific mood dimensions rather than the mood construct more broadly, and therefore results should not be extrapolated to other dimensions of mood [ 50 ].

Mean effects were larger among higher quality than lower quality meta-analyses for both hypothetically positive ( d = 0.54 vs d = 0.45) and negative effects ( d = -0.25 vs d = 0.17), but in neither case were the differences significant. It is reasonable to assume that the true effects were derived from the higher quality meta-analyses, although our conclusions remain the same regardless of study quality. Overall, our findings provide a more rigorous evidence base for the use of sport psychology techniques by practitioners than was previously available, representing a significant contribution to knowledge. Moreover, our systematic scrutiny of 30 meta-analyses published between 1983 and 2021 has facilitated a series of recommendations to improve the quality of future investigations in the sport psychology area.

Recommendations

The development of sport psychology as an academic discipline and area of professional practice relies on using evidence and theory to guide practice. Hence, a strong evidence base for the applied work of sport psychologists is of paramount importance. Although the beneficial effects of some sport psychology techniques are small, it is important to note the larger performance benefits for other techniques, which may be extremely meaningful for applied practice. Overall, however, especially given the heterogeneity of the observed effects, it would be wise for applied practitioners to avoid overpromising the benefits of sport psychology services to clients and perhaps underdelivering as a result [ 1 ].

The results of our systematic review can be used to generate recommendations for how the profession might conduct improved research to better inform applied practice. Much of the early research in sport psychology was exploratory and potential moderating variables were not always sufficiently controlled. Terry [ 51 ] outlined this in relation to the study of mood-performance relationships, identifying that physical and skills factors will very likely exert a greater influence on performance than psychological factors. Further, type of sport (e.g., individual vs. team), duration of activity (e.g., short vs. long duration), level of competition (e.g., elite vs. recreational), and performance measure (e.g., norm-referenced vs. self-referenced) have all been implicated as potential moderators of the relationship between psychological variables and sport performance [ 51 ]. To detect the relatively subtle effects of psychological effects on performance, research designs need to be sufficiently sensitive to such potential confounds. Several specific methodological issues are worth discussing.

The first issue relates to measurement. Investigating the strength of a relationship requires the measured variables to be valid, accurate and reliable. Psychological variables in the meta-analyses we reviewed relied primarily on self-report outcome measures. The accuracy of self-report data requires detailed inner knowledge of thoughts, emotions, and behavior. Research shows that the accuracy of self-report information is subject to substantial individual differences [ 52 , 53 ]. Therefore, self-report data, at best, are an estimate of the measure. Measurement issues are especially relevant to the assessment of performance, and considerable measurement variation was evident between meta-analyses. Some performance measures were more sensitive, especially those assessing physical performance relative to what is normal for the individual performer (i.e., self-referenced performance). Hence, having multiple baseline indicators of performance increases the probability of identifying genuine performance enhancement derived from a psychological intervention [ 54 ].

A second issue relates to clarifying the rationale for how and why specific psychological variables might influence performance. A comprehensive review of prerequisites and precursors of athletic talent [ 55 ] concluded that the superiority of Olympic champions over other elite athletes is determined in part by a range of psychological variables, including high intrinsic motivation, determination, dedication, persistence, and creativity, thereby identifying performance-related variables that might benefit from a psychological intervention. Identifying variables that influence the effectiveness of interventions is a challenging but essential issue for researchers seeking to control and assess factors that might influence results [ 49 ]. A key part of this process is to use theory to propose the mechanism(s) by which an intervention might affect performance and to hypothesize how large the effect might be.

A third issue relates to the characteristics of the research participants involved. Out of convenience, it is not uncommon for researchers to use undergraduate student participants for research projects, which may bias results and restrict the generalization of findings to the population of primary interest, often elite athletes. The level of training and physical conditioning of participants will clearly influence their performance. Highly trained athletes will typically make smaller gains in performance over time than novice athletes, due to a ceiling effect (i.e., they have less room for improvement). For example, consider runner A, who takes 20 minutes to run 5km one week but 19 minutes the next week, and Runner B who takes 30 minutes one week and 25 minutes the next. If we compare the two, Runner A runs faster than Runner B on both occasions, but Runner B improved more, so whose performance was better? If we also consider Runner C, a highly trained athlete with a personal best of 14 minutes, to run 1 minute quicker the following week would almost require a world record time, which is clearly unlikely. For this runner, an improvement of a few seconds would represent an excellent performance. Evidence shows that trained, highly motivated athletes may reach performance plateaus and as such are good candidates for psychological skills training. They are less likely to make performance gains due to increased training volume and therefore the impact of psychological skills interventions may emerge more clearly. Therefore, both test-retest and cross-sectional research designs should account for individual difference variables. Further, the range of individual difference factors will be context specific; for example, individual differences in strength will be more important in a study that uses weightlifting as the performance measure than one that uses darts as the performance measure, where individual differences in skill would be more important.

A fourth factor that has not been investigated extensively relates to the variables involved in learning sport psychology techniques. Techniques such as imagery, self-talk and goal setting all require cognitive processing and as such some people will learn them faster than others [ 56 ]. Further, some people are intuitive self-taught users of, for example, mood regulation strategies such as abdominal breathing or listening to music who, if recruited to participate in a study investigating the effects of learning such techniques on performance, would respond differently to novice users. Hence, a major challenge when testing the effects of a psychological intervention is to establish suitable controls. A traditional non-treatment group offers one option, but such an approach does not consider the influence of belief effects (i.e., placebo/nocebo), which can either add or detract from the effectiveness of performance interventions [ 57 ]. If an individual believes that, an intervention will be effective, this provides a motivating effect for engagement and so performance may improve via increased effort rather than the effect of the intervention per se.

When there are positive beliefs that an intervention will work, it becomes important to distinguish belief effects from the proposed mechanism through which the intervention should be successful. Research has shown that field studies often report larger effects than laboratory studies, a finding attributed to higher motivation among participants in field studies [ 58 ]. If participants are motivated to improve, being part of an active training condition should be associated with improved performance regardless of any intervention. In a large online study of over 44,000 participants, active training in sport psychology interventions was associated with improved performance, but only marginally more than for an active control condition [ 59 ]. The study involved 4-time Olympic champion Michael Johnson narrating both the intervention and active control using motivational encouragement in both conditions. Researchers should establish not only the expected size of an effect but also to specify and assess why the intervention worked. Where researchers report performance improvement, it is fundamental to explain the proposed mechanism by which performance was enhanced and to test the extent to which the improvement can be explained by the proposed mechanism(s).

Limitations

Systematic reviews are inherently limited by the quality of the primary studies included. Our review was also limited by the quality of the meta-analyses that had summarized the primary studies. We identified the following specific limitations; (1) only 12 meta-analyses summarized primary studies that were exclusively intervention-based, (2) the lack of detail regarding control groups in the intervention meta-analyses, (3) cross-sectional and correlation-based meta-analyses by definition do not test causation, and therefore provide limited direct evidence of the efficacy of interventions, (4) the extensive array of performance measures even within a single meta-analysis, (5) the absence of mechanistic explanations for the observed effects, and (6) an absence of detail across intervention-based meta-analyses regarding number of sessions, participants’ motivation to participate, level of expertise, and how the intervention was delivered. To ameliorate these concerns, we included a quality rating for all included meta-analyses. Having created higher and lower quality groups using a median split of quality ratings, we showed that effects were larger, although not significantly so, in the higher quality group of meta-analyses, all of which were published since 2015.

Conclusions

Journals are full of studies that investigate relationships between psychological variables and sport performance. Since 1983, researchers have utilized meta-analytic methods to summarize these single studies, and the pace is accelerating, with six relevant meta-analyses published since 2020. Unquestionably, sport psychology and performance research is fraught with limitations related to unsophisticated experimental designs. In our aggregation of the effect size values, most were small-to-moderate in meaningfulness with a handful of large values. Whether these moderate and large values could be replicated using more sophisticated research designs is unknown. We encourage use of improved research designs, at the minimum the use of control conditions. Likewise, we encourage researchers to adhere to meta-analytic guidelines such as PRISMA and for journals to insist on such adherence as a prerequisite for the acceptance of reviews. Although such guidelines can appear as a ‘painting by numbers’ approach, while reviewing the meta-analyses, we encountered difficulty in assessing and finding pertinent information for our study characteristics and quality ratings. In conclusion, much research exists in the form of quantitative reviews of studies published since 1934, almost 100 years after the very first publication about sport psychology and performance [ 2 ]. Sport psychology is now truly global in terms of academic pursuits and professional practice and the need for best practice information plus a strong evidence base for the efficacy of interventions is paramount. We should strive as a profession to research and provide best practices to athletes and the general community of those seeking performance improvements.

Supporting information

S1 checklist..

https://doi.org/10.1371/journal.pone.0263408.s001

Acknowledgments

We acknowledge the work of all academics since Koch in 1830 [ 2 ] for their efforts to research and promote the practice of applied sport psychology.

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• Systematic review update
• Open access
• Published: 21 June 2023

The impact of sports participation on mental health and social outcomes in adults: a systematic review and the ‘Mental Health through Sport’ conceptual model

• Narelle Eather   ORCID: orcid.org/0000-0002-6320-4540 1 , 2 ,
• Levi Wade   ORCID: orcid.org/0000-0002-4007-5336 1 , 3 ,
• Aurélie Pankowiak   ORCID: orcid.org/0000-0003-0178-513X 4 &
• Rochelle Eime   ORCID: orcid.org/0000-0002-8614-2813 4 , 5  

Systematic Reviews volume  12 , Article number:  102 ( 2023 ) Cite this article

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Sport is a subset of physical activity that can be particularly beneficial for short-and-long-term physical and mental health, and social outcomes in adults. This study presents the results of an updated systematic review of the mental health and social outcomes of community and elite-level sport participation for adults. The findings have informed the development of the ‘Mental Health through Sport’ conceptual model for adults.

Nine electronic databases were searched, with studies published between 2012 and March 2020 screened for inclusion. Eligible qualitative and quantitative studies reported on the relationship between sport participation and mental health and/or social outcomes in adult populations. Risk of bias (ROB) was determined using the Quality Assessment Tool (quantitative studies) or Critical Appraisal Skills Programme (qualitative studies).

The search strategy located 8528 articles, of which, 29 involving adults 18–84 years were included for analysis. Data was extracted for demographics, methodology, and study outcomes, and results presented according to study design. The evidence indicates that participation in sport (community and elite) is related to better mental health, including improved psychological well-being (for example, higher self-esteem and life satisfaction) and lower psychological ill-being (for example, reduced levels of depression, anxiety, and stress), and improved social outcomes (for example, improved self-control, pro-social behavior, interpersonal communication, and fostering a sense of belonging). Overall, adults participating in team sport had more favorable health outcomes than those participating in individual sport, and those participating in sports more often generally report the greatest benefits; however, some evidence suggests that adults in elite sport may experience higher levels of psychological distress. Low ROB was observed for qualitative studies, but quantitative studies demonstrated inconsistencies in methodological quality.

Conclusions

The findings of this review confirm that participation in sport of any form (team or individual) is beneficial for improving mental health and social outcomes amongst adults. Team sports, however, may provide more potent and additional benefits for mental and social outcomes across adulthood. This review also provides preliminary evidence for the Mental Health through Sport model, though further experimental and longitudinal evidence is needed to establish the mechanisms responsible for sports effect on mental health and moderators of intervention effects. Additional qualitative work is also required to gain a better understanding of the relationship between specific elements of the sporting environment and mental health and social outcomes in adult participants.

Peer Review reports

Introduction

The organizational structure of sport and the performance demands characteristic of sport training and competition provide a unique opportunity for participants to engage in health-enhancing physical activity of varied intensity, duration, and mode; and the opportunity to do so with other people as part of a team and/or club. Participation in individual and team sports have shown to be beneficial to physical, social, psychological, and cognitive health outcomes [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]. Often, the social and mental health benefits facilitated through participation in sport exceed those achieved through participation in other leisure-time or recreational activities [ 8 , 9 , 10 ]. Notably, these benefits are observed across different sports and sub-populations (including youth, adults, older adults, males, and females) [ 11 ]. However, the evidence regarding sports participation at the elite level is limited, with available research indicating that elite athletes may be more susceptible to mental health problems, potentially due to the intense mental and physical demands placed on elite athletes [ 12 ].

Participation in sport varies across the lifespan, with children representing the largest cohort to engage in organized community sport [ 13 ]. Across adolescence and into young adulthood, dropout from organized sport is common, and especially for females [ 14 , 15 , 16 ], and adults are shifting from organized sports towards leisure and fitness activities, where individual activities (including swimming, walking, and cycling) are the most popular [ 13 , 17 , 18 , 19 ]. Despite the general decline in sport participation with age [ 13 ], the most recent (pre-COVID) global data highlights that a range of organized team sports (such as, basketball, netball volleyball, and tennis) continue to rank highly amongst adult sport participants, with soccer remaining a popular choice across all regions of the world [ 13 ]. It is encouraging many adults continue to participate in sport and physical activities throughout their lives; however, high rates of dropout in youth sport and non-participation amongst adults means that many individuals may be missing the opportunity to reap the potential health benefits associated with participation in sport.

According to the World Health Organization, mental health refers to a state of well-being and effective functioning in which an individual realizes his or her own abilities, is resilient to the stresses of life, and is able to make a positive contribution to his or her community [ 20 ]. Mental health covers three main components, including psychological, emotional and social health [ 21 ]. Further, psychological health has two distinct indicators, psychological well-being (e.g., self-esteem and quality of life) and psychological ill-being (e.g., pre-clinical psychological states such as psychological difficulties and high levels of stress) [ 22 ]. Emotional well-being describes how an individual feels about themselves (including life satisfaction, interest in life, loneliness, and happiness); and social well–being includes an individual’s contribution to, and integration in society [ 23 ].

Mental illnesses are common among adults and incidence rates have remained consistently high over the past 25 years (~ 10% of people affected globally) [ 24 ]. Recent statistics released by the World Health Organization indicate that depression and anxiety are the most common mental disorders, affecting an estimated 264 million people, ranking as one of the main causes of disability worldwide [ 25 , 26 ]. Specific elements of social health, including high levels of isolation and loneliness among adults, are now also considered a serious public health concern due to the strong connections with ill-health [ 27 ]. Participation in sport has shown to positively impact mental and social health status, with a previous systematic review by Eime et al. (2013) indicated that sports participation was associated with lower levels of perceived stress, and improved vitality, social functioning, mental health, and life satisfaction [ 1 ]. Based on their findings, the authors developed a conceptual model (health through sport) depicting the relationship between determinants of adult sports participation and physical, psychological, and social health benefits of participation. In support of Eime’s review findings, Malm and colleagues (2019) recently described how sport aids in preventing or alleviating mental illness, including depressive symptoms and anxiety or stress-related disease [ 7 ]. Andersen (2019) also highlighted that team sports participation is associated with decreased rates of depression and anxiety [ 11 ]. In general, these reviews report stronger effects for sports participation compared to other types of physical activity, and a dose–response relationship between sports participation and mental health outcomes (i.e., higher volume and/or intensity of participation being associated with greater health benefits) when adults participate in sports they enjoy and choose [ 1 , 7 ]. Sport is typically more social than other forms of physical activity, including enhanced social connectedness, social support, peer bonding, and club support, which may provide some explanation as to why sport appears to be especially beneficial to mental and social health [ 28 ].

Thoits (2011) proposed several potential mechanisms through which social relationships and social support improve physical and psychological well-being [ 29 ]; however, these mechanisms have yet to be explored in the context of sports participation at any level in adults. The identification of the mechanisms responsible for such effects may direct future research in this area and help inform future policy and practice in the delivery of sport to enhance mental health and social outcomes amongst adult participants. Therefore, the primary objective of this review was to examine and synthesize all research findings regarding the relationship between sports participation, mental health and social outcomes at the community and elite level in adults. Based on the review findings, the secondary objective was to develop the ‘Mental Health through Sport’ conceptual model.

This review has been registered in the PROSPERO systematic review database and assigned the identifier: CRD42020185412. The conduct and reporting of this systematic review also follows the Preferred Reporting for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 30 ] (PRISMA flow diagram and PRISMA Checklist available in supplementary files ). This review is an update of a previous review of the same topic [ 31 ], published in 2012.

Identification of studies

Nine electronic databases (CINAHL, Cochrane Library, Google Scholar, Informit, Medline, PsychINFO, Psychology and Behavioural Sciences Collection, Scopus, and SPORTDiscus) were systematically searched for relevant records published from 2012 to March 10, 2020. The following key terms were developed by all members of the research team (and guided by previous reviews) and entered into these databases by author LW: sport* AND health AND value OR benefit* OR effect* OR outcome* OR impact* AND psych* OR depress* OR stress OR anxiety OR happiness OR mood OR ‘quality of life’ OR ‘social health’ OR ‘social relation*’ OR well* OR ‘social connect*’ OR ‘social functioning’ OR ‘life satisfac*’ OR ‘mental health’ OR social OR sociolog* OR affect* OR enjoy* OR fun. Where possible, Medical Subject Headings (MeSH) were also used.

Criteria for inclusion/exclusion

The titles of studies identified using this method were screened by LW. Abstract and full text of the articles were reviewed independently by LW and NE. To be included in the current review, each study needed to meet each of the following criteria: (1) published in English from 2012 to 2020; (2) full-text available online; (3) original research or report published in a peer-reviewed journal; (4) provides data on the psychological or social effects of participation in sport (with sport defined as a subset of exercise that can be undertaken individually or as a part of a team, where participants adhere to a common set of rules or expectations, and a defined goal exists); (5) the population of interest were adults (18 years and older) and were apparently healthy. All papers retrieved in the initial search were assessed for eligibility by title and abstract. In cases where a study could not be included or excluded via their title and abstract, the full text of the article was reviewed independently by two of the authors.

Data extraction

For the included studies, the following data was extracted independently by LW and checked by NE using a customized Google Docs spreadsheet: author name, year of publication, country, study design, aim, type of sport (e.g., tennis, hockey, team, individual), study conditions/comparisons, sample size, where participants were recruited from, mean age of participants, measure of sports participation, measure of physical activity, psychological and/or social outcome/s, measure of psychological and/or social outcome/s, statistical method of analysis, changes in physical activity or sports participation, and the psychological and/or social results.

Risk of bias (ROB) assessment

A risk of bias was performed by LW and AP independently using the ‘Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies’ OR the ‘Quality Assessment of Controlled Intervention Studies’ for the included quantitative studies, and the ‘Critical Appraisal Skills Programme (CASP) Checklist for the included qualitative studies [ 32 , 33 ]. Any discrepancies in the ROB assessments were discussed between the two reviewers, and a consensus reached.

The search yielded 8528 studies, with a total of 29 studies included in the systematic review (Fig.  1 ). Tables  1 and 2 provide a summary of the included studies. The research included adults from 18 to 84 years old, with most of the evidence coming from studies targeting young adults (18–25 years). Study samples ranged from 14 to 131, 962, with the most reported psychological outcomes being self-rated mental health ( n  = 5) and depression ( n  = 5). Most studies did not investigate or report the link between a particular sport and a specific mental health or social outcome; instead, the authors’ focused on comparing the impact of sport to physical activity, and/or individual sports compared to team sports. The results of this review are summarized in the following section, with findings presented by study design (cross-sectional, experimental, and longitudinal).

Flow of studies through the review process

Effects of sports participation on psychological well-being, ill-being, and social outcomes

Cross-sectional evidence.

This review included 14 studies reporting on the cross-sectional relationship between sports participation and psychological and/or social outcomes. Sample sizes range from n  = 414 to n  = 131,962 with a total of n  = 239,394 adults included across the cross-sectional studies.

The cross-sectional evidence generally supports that participation in sport, and especially team sports, is associated with greater mental health and psychological wellbeing in adults compared to non-participants [ 36 , 59 ]; and that higher frequency of sports participation and/or sport played at a higher level of competition, are also linked to lower levels of mental distress in adults . This was not the case for one specific study involving ice hockey players aged 35 and over, with Kitchen and Chowhan (2016) Kitchen and Chowhan (2016) reporting no relationship between participation in ice hockey and either mental health, or perceived life stress [ 54 ]. There is also some evidence to support that previous participation in sports (e.g., during childhood or young adulthood) is linked to better mental health outcomes later in life, including improved mental well-being and lower mental distress [ 59 ], even after controlling for age and current physical activity.

Compared to published community data for adults, elite or high-performance adult athletes demonstrated higher levels of body satisfaction, self-esteem, and overall life satisfaction [ 39 ]; and reported reduced tendency to respond to distress with anger and depression. However, rates of psychological distress were higher in the elite sport cohort (compared to community norms), with nearly 1 in 5 athletes reporting ‘high to very high’ distress, and 1 in 3 reporting poor mental health symptoms at a level warranting treatment by a health professional in one study ( n  = 749) [ 39 ].

Four studies focused on the associations between physical activity and sports participation and mental health outcomes in older adults. Physical activity was associated with greater quality of life [ 56 ], with the relationship strongest for those participating in sport in middle age, and for those who cycled in later life (> 65) [ 56 ]. Group physical activities (e.g., walking groups) and sports (e.g., golf) were also significantly related to excellent self-rated health, low depressive symptoms, high health-related quality of life (HRQoL) and a high frequency of laughter in males and females [ 60 , 61 ]. No participation or irregular participation in sport was associated with symptoms of mild to severe depression in older adults [ 62 ].

Several cross-sectional studies examined whether the effects of physical activity varied by type (e.g., total physical activity vs. sports participation). In an analysis of 1446 young adults (mean age = 18), total physical activity, moderate-to-vigorous physical activity, and team sport were independently associated with mental health [ 46 ]. Relative to individual physical activity, after adjusting for covariates and moderate-to-vigorous physical activity (MVPA), only team sport was significantly associated with improved mental health. Similarly, in a cross-sectional analysis of Australian women, Eime, Harvey, Payne (2014) reported that women who engaged in club and team-based sports (tennis or netball) reported better mental health and life satisfaction than those who engaged in individual types of physical activity [ 47 ]. Interestingly, there was no relationship between the amount of physical activity and either of these outcomes, suggesting that other qualities of sports participation contribute to its relationship to mental health and life satisfaction. There was also some evidence to support a relationship between exercise type (ball sports, aerobic activity, weightlifting, and dancing), and mental health amongst young adults (mean age 22 years) [ 48 ], with ball sports and dancing related to fewer symptoms of depression in students with high stress; and weightlifting related to fewer depressive symptoms in weightlifters exhibiting low stress.

Longitudinal evidence

Eight studies examined the longitudinal relationship between sports participation and either mental health and/or social outcomes. Sample sizes range from n  = 113 to n  = 1679 with a total of n  = 7022 adults included across the longitudinal studies.

Five of the included longitudinal studies focused on the relationship between sports participation in childhood or adolescence and mental health in young adulthood. There is evidence that participation in sport in high-school is protective of future symptoms of anxiety (including panic disorder, generalised anxiety disorder, social phobia, and agoraphobia) [ 42 ]. Specifically, after controlling for covariates (including current physical activity), the number of years of sports participation in high school was shown to be protective of symptoms of panic and agoraphobia in young adulthood, but not protective of symptoms of social phobia or generalized anxiety disorder [ 42 ]. A comparison of individual or team sports participation also revealed that participation in either context was protective of panic disorder symptoms, while only team sport was protective of agoraphobia symptoms, and only individual sport was protective of social phobia symptoms. Furthermore, current and past sports team participation was shown to negatively relate to adult depressive symptoms [ 43 ]; drop out of sport was linked to higher depressive symptoms in adulthood compared to those with maintained participation [ 9 , 22 , 63 ]; and consistent participation in team sports (but not individual sport) in adolescence was linked to higher self-rated mental health, lower perceived stress and depressive symptoms, and lower depression scores in early adulthood [ 53 , 58 ].

Two longitudinal studies [ 35 , 55 ], also investigated the association between team and individual playing context and mental health. Dore and colleagues [ 35 ] reported that compared to individual activities, being active in informal groups (e.g., yoga, running groups) or team sports was associated with better mental health, fewer depressive symptoms and higher social connectedness – and that involvement in team sports was related to better mental health regardless of physical activity volume. Kim and James [ 55 ] discovered that sports participation led to both short and long-term improvements in positive affect and life satisfaction.

A study on social outcomes related to mixed martial-arts (MMA) and Brazilian jiu-jitsu (BJJ) showed that both sports improved practitioners’ self-control and pro-social behavior, with greater improvements seen in the BJJ group [ 62 ]. Notably, while BJJ reduced participants’ reported aggression, there was a slight increase in MMA practitioners, though it is worth mentioning that individuals who sought out MMA had higher levels of baseline aggression.

Experimental evidence

Six of the included studies were experimental or quasi-experimental. Sample sizes ranged from n  = 28 to n  = 55 with a total of n  = 239 adults included across six longitudinal studies. Three studies involved a form of martial arts (such as judo and karate) [ 45 , 51 , 52 ], one involved a variety of team sports (such as netball, soccer, and cricket) [ 34 ], and the remaining two focused on badminton [ 57 ] and handball [ 49 ].

Brinkley and colleagues [ 34 ] reported significant effects on interpersonal communication (but not vitality, social cohesion, quality of life, stress, or interpersonal relationships) for participants ( n  = 40) engaging in a 12-week workplace team sports intervention. Also using a 12-week intervention, Hornstrup et al. [ 49 ] reported a significant improvement in mental energy (but not well-being or anxiety) in young women (mean age = 24; n  = 28) playing in a handball program. Patterns et al. [ 57 ] showed that in comparison to no exercise, participation in an 8-week badminton or running program had no significant improvement on self-esteem, despite improvements in perceived and actual fitness levels.

Three studies examined the effect of martial arts on the mental health of older adults (mean ages 79 [ 52 ], 64 [ 51 ], and 70 [ 45 ] years). Participation in Karate-Do had positive effects on overall mental health, emotional wellbeing, depression and anxiety when compared to other activities (physical, cognitive, mindfulness) and a control group [ 51 , 52 ]. Ciaccioni et al. [ 45 ] found that a Judo program did not affect either the participants’ mental health or their body satisfaction, citing a small sample size, and the limited length of the intervention as possible contributors to the findings.

Qualitative evidence

Three studies interviewed current or former sports players regarding their experiences with sport. Chinkov and Holt [ 41 ] reported that jiu-jitsu practitioners (mean age 35 years) were more self-confident in their lives outside of the gym, including improved self-confidence in their interactions with others because of their training. McGraw and colleagues [ 37 ] interviewed former and current National Football League (NFL) players and their families about its impact on the emotional and mental health of the players. Most of the players reported that their NFL career provided them with social and emotional benefits, as well as improvements to their self-esteem even after retiring. Though, despite these benefits, almost all the players experienced at least one mental health challenge during their career, including depression, anxiety, or difficulty controlling their temper. Some of the players and their families reported that they felt socially isolated from people outside of the national football league.

Through a series of semi-structured interviews and focus groups, Thorpe, Anders [ 40 ] investigated the impact of an Aboriginal male community sporting team on the health of its players. The players reported they felt a sense of belonging when playing in the team, further noting that the social and community aspects were as important as the physical health benefits. Participating in the club strengthened the cultural identity of the players, enhancing their well-being. The players further noted that participation provided them with enjoyment, stress relief, a sense of purpose, peer support, and improved self-esteem. Though they also noted challenges, including the presence of racism, community conflict, and peer-pressure.

Quality of studies

Full details of our risk of bias (ROB) results are provided in Supplementary Material A . Of the three qualitative studies assessed using the Critical Appraisal Skills Program (CASP), all three were deemed to have utilised and reported appropriate methodological standards on at least 8 of the 10 criteria. Twenty studies were assessed using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies, with all studies clearly reporting the research question/s or objective/s and study population. However, only four studies provided a justification for sample size, and less than half of the studies met quality criteria for items 6, 7, 9, or 10 (and items 12 and 13 were largely not applicable). Of concern, only four of the observational or cohort studies were deemed to have used clearly defined, valid, and reliable exposure measures (independent variables) and implemented them consistently across all study participants. Six studies were assessed using the Quality Assessment of Controlled Intervention Studies, with three studies described as a randomized trial (but none of the three reported a suitable method of randomization, concealment of treatment allocation, or blinding to treatment group assignment). Three studies showed evidence that study groups were similar at baseline for important characteristics and an overall drop-out rate from the study < 20%. Four studies reported high adherence to intervention protocols (with two not reporting) and five demonstrated that.study outcomes were assessed using valid and reliable measures and implemented consistently across all study participants. Importantly, researchers did not report or have access to validated instruments for assessing sport participation or physical activity amongst adults, though most studies provided psychometrics for their mental health outcome measure/s. Only one study reported that the sample size was sufficiently powered to detect a difference in the main outcome between groups (with ≥ 80% power) and that all participants were included in the analysis of results (intention-to-treat analysis). In general, the methodological quality of the six randomised studies was deemed low.

Initially, our discussion will focus on the review findings regarding sports participation and well-being, ill-being, and psychological health. However, the heterogeneity and methodological quality of the included research (especially controlled trials) should be considered during the interpretation of our results. Considering our findings, the Mental Health through Sport conceptual model for adults will then be presented and discussed and study limitations outlined.

Sports participation and psychological well-being

In summary, the evidence presented here indicates that for adults, sports participation is associated with better overall mental health [ 36 , 46 , 47 , 59 ], mood [ 56 ], higher life satisfaction [ 39 , 47 ], self-esteem [ 39 ], body satisfaction [ 39 ], HRQoL [ 60 ], self-rated health [ 61 ], and frequency of laughter [ 61 ]. Sports participation has also shown to be predictive of better psychological wellbeing over time [ 35 , 53 ], higher positive affect [ 55 ], and greater life satisfaction [ 55 ]. Furthermore, higher frequency of sports participation and/or sport played at a higher level of competition, have been linked to lower levels of mental distress, higher levels of body satisfaction, self-esteem, and overall life satisfaction in adults [ 39 ].

Despite considerable heterogeneity of sports type, cross-sectional and experimental research indicate that team-based sports participation, compared to individual sports and informal group physical activity, has a more positive effect on mental energy [ 49 ], physical self-perception [ 57 ], and overall psychological health and well-being in adults, regardless of physical activity volume [ 35 , 46 , 47 ]. And, karate-do benefits the subjective well-being of elderly practitioners [ 51 , 52 ]. Qualitative research in this area has queried participants’ experiences of jiu-jitsu, Australian football, and former and current American footballers. Participants in these sports reported that their participation was beneficial for psychological well-being [ 37 , 40 , 41 ], improved self-esteem [ 37 , 40 , 41 ], and enjoyment [ 37 ].

Sports participation and psychological ill-being

Of the included studies, n  = 19 examined the relationship between participating in sport and psychological ill-being. In summary, there is consistent evidence that sports participation is related to lower depression scores [ 43 , 48 , 61 , 62 ]. There were mixed findings regarding psychological stress, where participation in childhood (retrospectively assessed) was related to lower stress in young adulthood [ 41 ], but no relationship was identified between recreational hockey in adulthood and stress [ 54 ]. Concerning the potential impact of competing at an elite level, there is evidence of higher stress in elite athletes compared to community norms [ 39 ]. Further, there is qualitative evidence that many current or former national football league players experienced at least one mental health challenge, including depression, anxiety, difficulty controlling their temper, during their career [ 37 ].

Evidence from longitudinal research provided consistent evidence that participating in sport in adolescence is protective of symptoms of depression in young adulthood [ 43 , 53 , 58 , 63 ], and further evidence that participating in young adulthood is related to lower depressive symptoms over time (6 months) [ 35 ]. Participation in adolescence was also protective of manifestations of anxiety (panic disorder and agoraphobia) and stress in young adulthood [ 42 ], though participation in young adulthood was not related to a more general measure of anxiety [ 35 ] nor to changes in negative affect [ 55 ]). The findings from experimental research were mixed. Two studies examined the effect of karate-do on markers of psychological ill-being, demonstrating its capacity to reduce anxiety [ 52 ], with some evidence of its effectiveness on depression [ 51 ]. The other studies examined small-sided team-based games but showed no effect on stress or anxiety [ 34 , 49 ]. Most studies did not differentiate between team and individual sports, though one study found that adolescents who participated in team sports (not individual sports) in secondary school has lower depression scores in young adulthood [ 58 ].

Sports participation and social outcomes

Seven of the included studies examined the relationship between sports participation and social outcomes. However, very few studies examined social outcomes or tested a social outcome as a potential mediator of the relationship between sport and mental health. It should also be noted that this body of evidence comes from a wide range of sport types, including martial arts, professional football, and workplace team-sport, as well as different methodologies. Taken as a whole, the evidence shows that participating in sport is beneficial for several social outcomes, including self-control [ 50 ], pro-social behavior [ 50 ], interpersonal communication [ 34 ], and fostering a sense of belonging [ 40 ]. Further, there is evidence that group activity, for example team sport or informal group activity, is related to higher social connectedness over time, though analyses showed that social connectedness was not a mediator for mental health [ 35 ].

There were conflicting findings regarding social effects at the elite level, with current and former NFL players reporting that they felt socially isolated during their career [ 37 ], whilst another study reported no relationship between participation at the elite level and social dysfunction [ 39 ]. Conversely, interviews with a group of indigenous men revealed that they felt as though participating in an all-indigenous Australian football team provided them with a sense of purpose, and they felt as though the social aspect of the game was as important as the physical benefits it provides [ 40 ].

Mental health through sport conceptual model for adults

The ‘Health through Sport’ model provides a depiction of the determinants and benefits of sports participation [ 31 ]. The model recognises that the physical, mental, and social benefits of sports participation vary by the context of sport (e.g., individual vs. team, organized vs. informal). To identify the elements of sport which contribute to its effect on mental health outcomes, we describe the ‘Mental Health through Sport’ model (Fig.  2 ). The model proposes that the social and physical elements of sport each provide independent, and likely synergistic contributions to its overall influence on mental health.

The Mental Health through Sport conceptual model

The model describes two key pathways through which sport may influence mental health: physical activity, and social relationships and support. Several likely moderators of this effect are also provided, including sport type, intensity, frequency, context (team vs. individual), environment (e.g., indoor vs. outdoor), as well as the level of competition (e.g., elite vs. amateur).

The means by which the physical activity component of sport may influence mental health stems from the work of Lubans et al., who propose three key groups of mechanisms: neurobiological, psychosocial, and behavioral [ 64 ]. Processes whereby physical activity may enhance psychological outcomes via changes in the structural and functional composition of the brain are referred to as neurobiological mechanisms [ 65 , 66 ]. Processes whereby physical activity provides opportunities for the development of self-efficacy, opportunity for mastery, changes in self-perceptions, the development of independence, and for interaction with the environment are considered psychosocial mechanisms. Lastly, processes by which physical activity may influence behaviors which ultimately affect psychological health, including changes in sleep duration, self-regulation, and coping skills, are described as behavioral mechanisms.

Playing sport offers the opportunity to form relationships and to develop a social support network, both of which are likely to influence mental health. Thoits [ 29 ] describes 7 key mechanisms by which social relationships and support may influence mental health: social influence/social comparison; social control; role-based purpose and meaning (mattering); self-esteem; sense of control; belonging and companionship; and perceived support availability [ 29 ]. These mechanisms and their presence within a sporting context are elaborated below.

Subjective to the attitudes and behaviors of individuals in a group, social influence and comparison may facilitate protective or harmful effects on mental health. Participants in individual or team sport will be influenced and perhaps steered by the behaviors, expectations, and norms of other players and teams. When individual’s compare their capabilities, attitudes, and values to those of other participants, their own behaviors and subsequent health outcomes may be affected. When others attempt to encourage or discourage an individual to adopt or reject certain health practices, social control is displayed [ 29 ]. This may evolve as strategies between players (or between players and coach) are discussion and implemented. Likewise, teammates may try to motivate each another during a match to work harder, or to engage in specific events or routines off-field (fitness programs, after game celebrations, attending club events) which may impact current and future physical and mental health.

Sport may also provide behavioral guidance, purpose, and meaning to its participants. Role identities (positions within a social structure that come with reciprocal obligations), often formed as a consequence of social ties formed through sport. Particularly in team sports, participants come to understand they form an integral part of the larger whole, and consequently, they hold certain responsibility in ensuring the team’s success. They have a commitment to the team to, train and play, communicate with the team and a potential responsibility to maintain a high level of health, perform to their capacity, and support other players. As a source of behavioral guidance and of purpose and meaning in life, these identities are likely to influence mental health outcomes amongst sport participants.

An individual’s level of self-esteem may be affected by the social relationships and social support provided through sport; with improved perceptions of capability (or value within a team) in the sporting domain likely to have positive impact on global self-esteem and sense of worth [ 64 ]. The unique opportunities provided through participation in sport, also allow individuals to develop new skills, overcome challenges, and develop their sense of self-control or mastery . Working towards and finding creative solutions to challenges in sport facilitates a sense of mastery in participants. This sense of mastery may translate to other areas of life, with individual’s developing the confidence to cope with varied life challenges. For example, developing a sense of mastery regarding capacity to formulate new / creative solutions when taking on an opponent in sport may result in greater confidence to be creative at work. Social relationships and social support provided through sport may also provide participants with a source of belonging and companionship. The development of connections (on and off the field) to others who share common interests, can build a sense of belonging that may mediate improvements in mental health outcomes. Social support is often provided emotionally during expressions of trust and care; instrumentally via tangible assistance; through information such as advice and suggestions; or as appraisal such feedback. All forms of social support provided on and off the field contribute to a more generalised sense of perceived support that may mediate the effect of social interaction on mental health outcomes.

Participation in sport may influence mental health via some combination of the social mechanisms identified by Thoits, and the neurobiological, psychosocial, and behavioral mechanisms stemming from physical activity identified by Lubans [ 29 , 64 ]. The exact mechanisms through which sport may confer psychological benefit is likely to vary between sports, as each sport varies in its physical and social requirements. One must also consider the social effects of sports participation both on and off the field. For instance, membership of a sporting team and/or club may provide a sense of identity and belonging—an effect that persists beyond the immediacy of playing the sport and may have a persistent effect on their psychological health. Furthermore, the potential for team-based activity to provide additional benefit to psychological outcomes may not just be attributable to the differences in social interactions, there are also physiological differences in the requirements for sport both within (team vs. team) and between (team vs. individual) categories that may elicit additional improvements in psychological outcomes. For example, evidence supports that exercise intensity moderates the relationship between physical activity and several psychological outcomes—supporting that sports performed at higher intensity will be more beneficial for psychological health.

Limitations and recommendations

There are several limitations of this review worthy of consideration. Firstly, amongst the included studies there was considerable heterogeneity in study outcomes and study methodology, and self-selection bias (especially in non-experimental studies) is likely to influence study findings and reduce the likelihood that study participants and results are representative of the overall population. Secondly, the predominately observational evidence included in this and Eime’s prior review enabled us to identify the positive relationship between sports participation and social and psychological health (and examine directionality)—but more experimental and longitudinal research is required to determine causality and explore potential mechanisms responsible for the effect of sports participation on participant outcomes. Additional qualitative work would also help researchers gain a better understanding of the relationship between specific elements of the sporting environment and mental health and social outcomes in adult participants. Thirdly, there were no studies identified in the literature where sports participation involved animals (such as equestrian sports) or guns (such as shooting sports). Such studies may present novel and important variables in the assessment of mental health benefits for participants when compared to non-participants or participants in sports not involving animals/guns—further research is needed in this area. Our proposed conceptual model also identifies several pathways through which sport may lead to improvements in mental health—but excludes some potentially negative influences (such as poor coaching behaviors and injury). And our model is not designed to capture all possible mechanisms, creating the likelihood that other mechanisms exist but are not included in this review. Additionally, an interrelationship exits between physical activity, mental health, and social relationships, whereby changes in one area may facilitate changes in the other/s; but for the purpose of this study, we have focused on how the physical and social elements of sport may mediate improvements in psychological outcomes. Consequently, our conceptual model is not all-encompassing, but designed to inform and guide future research investigating the impact of sport participation on mental health.

The findings of this review endorse that participation in sport is beneficial for psychological well-being, indicators of psychological ill-being, and social outcomes in adults. Furthermore, participation in team sports is associated with better psychological and social outcomes compared to individual sports or other physical activities. Our findings support and add to previous review findings [ 1 ]; and have informed the development of our ‘Mental Health through Sport’ conceptual model for adults which presents the potential mechanisms by which participation in sport may affect mental health.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

We would like to acknowledge the work of the original systematic review conducted by Eime, R. M., Young, J. A., Harvey, J. T., Charity, M. J., and Payne, W. R. (2013).

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All authors contributed to the conducting of this study and reporting the findings. The titles of studies identified were screened by LW, and abstracts and full text articles reviewed independently by LW and NE. For the included studies, data was extracted independently by LW and checked by NE, and the risk of bias assessment was performed by LW and AP independently. All authors have read and approved the final version of the manuscript and agree with the order of presentation of the authors.

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Eather, N., Wade, L., Pankowiak, A. et al. The impact of sports participation on mental health and social outcomes in adults: a systematic review and the ‘Mental Health through Sport’ conceptual model. Syst Rev 12 , 102 (2023). https://doi.org/10.1186/s13643-023-02264-8

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The bright side of sports: a systematic review on well-being, positive emotions and performance

• David Peris-Delcampo 1 ,
• Antonio Núñez 2 ,
• Paula Ortiz-Marholz 3 ,
• Aurelio Olmedilla 4 ,
• Enrique Cantón 1 ,
• Javier Ponseti 2 &
• Alejandro Garcia-Mas 2  

BMC Psychology volume  12 , Article number:  284 ( 2024 ) Cite this article

Metrics details

The objective of this study is to conduct a systematic review regarding the relationship between positive psychological factors, such as psychological well-being and pleasant emotions, and sports performance.

This study, carried out through a systematic review using PRISMA guidelines considering the Web of Science, PsycINFO, PubMed and SPORT Discus databases, seeks to highlight the relationship between other more ‘positive’ factors, such as well-being, positive emotions and sports performance.

The keywords will be decided by a Delphi Method in two rounds with sport psychology experts.

Participants

There are no participants in the present research.

The main exclusion criteria were: Non-sport thema, sample younger or older than 20–65 years old, qualitative or other methodology studies, COVID-related, journals not exclusively about Psychology.

Main outcomes measures

We obtained a first sample of 238 papers, and finally, this sample was reduced to the final sample of 11 papers.

The results obtained are intended to be a representation of the ‘bright side’ of sports practice, and as a complement or mediator of the negative variables that have an impact on athletes’ and coaches’ performance.

Conclusions

Clear recognition that acting on intrinsic motivation continues to be the best and most effective way to motivate oneself to obtain the highest levels of performance, a good perception of competence and a source of personal satisfaction.

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Introduction

In recent decades, research in the psychology of sport and physical exercise has focused on the analysis of psychological variables that could have a disturbing, unfavourable or detrimental role, including emotions that are considered ‘negative’, such as anxiety/stress, sadness or anger, concentrating on their unfavourable relationship with sports performance [ 1 , 2 , 3 , 4 ], sports injuries [ 5 , 6 , 7 ] or, more generally, damage to the athlete’s health [ 8 , 9 , 10 ]. The study of ‘positive’ emotions such as happiness or, more broadly, psychological well-being, has been postponed at this time, although in recent years this has seen an increase that reveals a field of study of great interest to researchers and professionals [ 11 , 12 , 13 ] including physiological, psychological, moral and social beneficial effects of the physical activity in comic book heroes such as Tintin, a team leader, which can serve as a model for promoting healthy lifestyles, or seeking ‘eternal youth’ [ 14 ].

Emotions in relation to their effects on sports practice and performance rarely go in one direction, being either negative or positive—generally positive and negative emotions do not act alone [ 15 ]. Athletes experience different emotions simultaneously, even if they are in opposition and especially if they are of mild or moderate intensity [ 16 ]. The athlete can feel satisfied and happy and at the same time perceive a high level of stress or anxiety before a specific test or competition. Some studies [ 17 ] have shown how sports participation and the perceived value of elite sports positively affect the subjective well-being of the athlete. This also seems to be the case in non-elite sports practice. The review by Mansfield et al. [ 18 ] showed that the published literature suggests that practising sports and dance, in a group or supported by peers, can improve the subjective well-being of the participants, and also identifies negative feelings towards competence and ability, although the quantity and quality of the evidence published is low, requiring better designed studies. All these investigations are also supported by the development of the concept of eudaimonic well-being [ 19 ], which is linked to the development of intrinsic motivation, not only in its aspect of enjoyment but also in its relationship with the perception of competition and overcoming and achieving goals, even if this is accompanied by other unpleasant hedonic emotions or even physical discomfort. Shortly after a person has practised sports, he will remember those feelings of exhaustion and possibly stiffness, linked to feelings of satisfaction and even enjoyment.

Furthermore, the mediating role of parents, coaches and other psychosocial agents can be significant. In this sense, Lemelin et al. [ 20 ], with the aim of investigating the role of autonomy support from parents and coaches in the prediction of well-being and performance of athletes, found that autonomy support from parents and coaches has positive relationships with the well-being of the athlete, but that only coach autonomy support is associated with sports performance. This research suggests that parents and coaches play important but distinct roles in athlete well-being and that coach autonomy support could help athletes achieve high levels of performance.

On the other hand, an analysis of emotions in the sociocultural environment in which they arise and gain meaning is always interesting, both from an individual perspective and from a sports team perspective. Adler et al. [ 21 ] in a study with military teams showed that teams with a strong emotional culture of optimism were better positioned to recover from poor performance, suggesting that organisations that promote an optimistic culture develop more resilient teams. Pekrun et al. [ 22 ] observed with mathematics students that individual success boosts emotional well-being, while placing people in high-performance groups can undermine it, which is of great interest in investigating the effectiveness and adjustment of the individual in sports teams.

There is still little scientific literature in the field of positive emotions and their relationship with sports practice and athlete performance, although their approach has long had its clear supporters [ 23 , 24 ]. It is comforting to observe the significant increase in studies in this field, since some authors (e.g [ 25 , 26 ]). . , point out the need to overcome certain methodological and conceptual problems, paying special attention to the development of specific instruments for the evaluation of well-being in the sports field and evaluation methodologies.

As McCarthy [ 15 ] indicates, positive emotions (hedonically pleasant) can be the catalysts for excellence in sport and deserve a space in our research and in professional intervention to raise the level of athletes’ performance. From a holistic perspective, positive emotions are permanently linked to psychological well-being and research in this field is necessary: firstly because of the leading role they play in human behaviour, cognition and affection, and secondly, because after a few years of international uncertainty due to the COVID-19 pandemic and wars, it seems ‘healthy and intelligent’ to encourage positive emotions for our athletes. An additional reason is that they are known to improve motivational processes, reducing abandonment and negative emotional costs [ 11 ]. In this vein, concepts such as emotional intelligence make sense and can help to identify and properly manage emotions in the sports field and determine their relationship with performance [ 27 ] that facilitates the inclusion of emotional training programmes based on the ‘bright side’ of sports practice [ 28 ].

Based on all of the above, one might wonder how these positive emotions are related to a given event and what role each one of them plays in the athlete’s performance. Do they directly affect performance, or do they affect other psychological variables such as concentration, motivation and self-efficacy? Do they favour the availability and competent performance of the athlete in a competition? How can they be regulated, controlled for their own benefit? How can other psychosocial agents, such as parents or coaches, help to increase the well-being of their athletes?

This work aims to enhance the leading role, not the secondary, of the ‘good and pleasant side’ of sports practice, either with its own entity, or as a complement or mediator of the negative variables that have an impact on the performance of athletes and coaches. Therefore, the objective of this study is to conduct a systematic review regarding the relationship between positive psychological factors, such as psychological well-being and pleasant emotions, and sports performance. For this, the methodological criteria that constitute the systematic review procedure will be followed.

Materials and methods

This study was carried out through a systematic review using PRISMA (Preferred Reporting Items for Systematic Reviews) guidelines considering the Web of Science (WoS) and Psycinfo databases. These two databases were selected using the Delphi method [ 29 ]. It does not include a meta-analysis because there is great data dispersion due to the different methodologies used [ 30 ].

The keywords will be decided by the Delphi Method in two rounds with sport psychology experts. The results obtained are intended to be a representation of the ‘bright side’ of sports practice, and as a complement or mediator of the negative variables that have an impact on athletes’ and coaches’ performance.

It was determined that the main construct was to be psychological well-being, and that it was to be paired with optimism, healthy practice, realisation, positive mood, and performance and sport. The search period was limited to papers published between 2000 and 2023, and the final list of papers was obtained on February 13 , 2023. This research was conducted in two languages—English and Spanish—and was limited to psychological journals and specifically those articles where the sample was formed by athletes.

Each word was searched for in each database, followed by searches involving combinations of the same in pairs and then in trios. In relation to the results obtained, it was decided that the best approach was to group the words connected to positive psychology on the one hand, and on the other, those related to self-realisation/performance/health. In this way, it used parentheses to group words (psychological well-being; or optimism; or positive mood) with the Boolean ‘or’ between them (all three refer to positive psychology); and on the other hand, it grouped those related to performance/health/realisation (realisation; or healthy practice or performance), separating both sets of parentheses by the Boolean ‘and’’. To further filter the search, a keyword included in the title and in the inclusion criteria was added, which was ‘sport’ with the Boolean ‘and’’. In this way, the search achieved results that combined at least one of the three positive psychology terms and one of the other three.

Results (first phase)

The mentioned keywords were cross-matched, obtaining the combination with a sufficient number of papers. From the first research phase, the total number of papers obtained was 238. Then screening was carried out by 4 well-differentiated phases that are summarised in Fig.  1 . These phases helped to reduce the original sample to a more accurate one.

Phases of the selection process for the final sample. Four phases were carried out to select the final sample of articles. The first phase allowed the elimination of duplicates. In the second stage, those that, by title or abstract, did not fit the objectives of the article were eliminated. Previously selected exclusion criteria were applied to the remaining sample. Thus, in phase 4, the final sample of 11 selected articles was obtained

Results (second phase)

The first screening examined the title, and the abstract if needed, excluding the papers that were duplicated, contained errors or someone with formal problems, low N or case studies. This screening allowed the initial sample to be reduced to a more accurate one with 109 papers selected.

Results (third phase)

This was followed by the second screening to examine the abstract and full texts, excluding if necessary papers related to non-sports themes, samples that were too old or too young for our interests, papers using qualitative methodologies, articles related to the COVID period, or others published in non-psychological journals. Furthermore, papers related to ‘negative psychological variables’’ were also excluded.

Results (fourth phase)

At the end of this second screening the remaining number of papers was 11. In this final phase we tried to organise the main characteristics and their main conclusions/results in a comprehensible list (Table  1 ). Moreover, in order to enrich our sample of papers, we decided to include some articles from other sources, mainly those presented in the introduction to sustain the conceptual framework of the concept ‘bright side’ of sports.

The usual position of the researcher of psychological variables that affect sports performance is to look for relationships between ‘negative’ variables, first in the form of basic psychological processes, or distorting cognitive behavioural, unpleasant or evaluable as deficiencies or problems, in a psychology for the ‘risk’ society, which emphasises the rehabilitation that stems from overcoming personal and social pathologies [ 31 ], and, lately, regarding the affectation of the athlete’s mental health [ 32 ]. This fact seems to be true in many cases and situations and to openly contradict the proclaimed psychological benefits of practising sports (among others: Cantón [ 33 ], ; Froment and González [ 34 ]; Jürgens [ 35 ]).

However, it is possible to adopt another approach focused on the ‘positive’ variables, also in relation to the athlete’s performance. This has been the main objective of this systematic review of the existing literature and far from being a novel approach, although a minority one, it fits perfectly with the definition of our area of knowledge in the broad field of health, as has been pointed out for some time [ 36 , 37 ].

After carrying out the aforementioned systematic review, a relatively low number of articles were identified by experts that met the established conditions—according to the PRISMA method [ 37 , 38 , 39 , 40 ]—regarding databases, keywords, and exclusion and inclusion criteria. These precautions were taken to obtain the most accurate results possible, and thus guarantee the quality of the conclusions.

The first clear result that stands out is the great difficulty in finding articles in which sports ‘performance’ is treated as a well-defined study variable adapted to the situation and the athletes studied. In fact, among the results (11 papers), only 3 associate one or several positive psychological variables with performance (which is evaluated in very different ways, combining objective measures with other subjective ones). This result is not surprising, since in several previous studies (e.g. Nuñez et al. [ 41 ]) using a systematic review, this relationship is found to be very weak and nuanced by the role of different mediating factors, such as previous sports experience or the competitive level (e.g. Rascado, et al. [ 42 ]; Reche, Cepero & Rojas [ 43 ]), despite the belief—even among professional and academic circles—that there is a strong relationship between negative variables and poor performance, and vice versa, with respect to the positive variables.

Regarding what has been evidenced in relation to the latter, even with these restrictions in the inclusion and exclusion criteria, and the filters applied to the first findings, a true ‘galaxy’ of variables is obtained, which also belong to different categories and levels of psychological complexity.

A preliminary consideration regarding the current paradigm of sport psychology: although it is true that some recent works have already announced the swing of the pendulum on the objects of study of PD, by returning to the study of traits and dispositions, and even to the personality of athletes [ 43 , 44 , 45 , 46 ], our results fully corroborate this trend. Faced with five variables present in the studies selected at the end of the systematic review, a total of three traits/dispositions were found, which were also the most repeated—optimism being present in four articles, mental toughness present in three, and finally, perfectionism—as the representative concepts of this field of psychology, which lately, as has already been indicated, is significantly represented in the field of research in this area [ 46 , 47 , 48 , 49 , 50 , 51 , 52 ]. In short, the psychological variables that finally appear in the selected articles are: psychological well-being (PWB) [ 53 ]; self-compassion, which has recently been gaining much relevance with respect to the positive attributional resolution of personal behaviours [ 54 ], satisfaction with life (balance between sports practice, its results, and life and personal fulfilment [ 55 ], the existence of approach-achievement goals [ 56 ], and perceived social support [ 57 ]). This last concept is maintained transversally in several theoretical frameworks, such as Sports Commitment [ 58 ].

The most relevant concept, both quantitatively and qualitatively, supported by the fact that it is found in combination with different variables and situations, is not a basic psychological process, but a high-level cognitive construct: psychological well-being, in its eudaimonic aspect, first defined in the general population by Carol Ryff [ 59 , 60 ] and introduced at the beginning of this century in sport (e.g., Romero, Brustad & García-Mas [ 13 ], ; Romero, García-Mas & Brustad [ 61 ]). It is important to note that this concept understands psychological well-being as multifactorial, including autonomy, control of the environment in which the activity takes place, social relationships, etc.), meaning personal fulfilment through a determined activity and the achievement or progress towards goals and one’s own objectives, without having any direct relationship with simpler concepts, such as vitality or fun. In the selected studies, PWB appears in five of them, and is related to several of the other variables/traits.

The most relevant result regarding this variable is its link with motivational aspects, as a central axis that relates to different concepts, hence its connection to sports performance, as a goal of constant improvement that requires resistance, perseverance, management of errors and great confidence in the possibility that achievements can be attained, that is, associated with ideas of optimism, which is reflected in expectations of effectiveness.

If we detail the relationships more specifically, we can first review this relationship with the ‘way of being’, understood as personality traits or behavioural tendencies, depending on whether more or less emphasis is placed on their possibilities for change and learning. In these cases, well-being derives from satisfaction with progress towards the desired goal, for which resistance (mental toughness) and confidence (optimism) are needed. When, in addition, the search for improvement is constant and aiming for excellence, its relationship with perfectionism is clear, although it is a factor that should be explored further due to its potential negative effect, at least in the long term.

The relationship between well-being and satisfaction with life is almost tautological, in the precise sense that what produces well-being is the perception of a relationship or positive balance between effort (or the perception of control, if we use stricter terminology) and the results thereof (or the effectiveness of such control). This direct link is especially important when assessing achievement in personally relevant activities, which, in the case of the subjects evaluated in the papers, specifically concern athletes of a certain level of performance, which makes it a more valuable objective than would surely be found in the general population. And precisely because of this effect of the value of performance for athletes of a certain level, it also allows us to understand how well-being is linked to self-compassion, since as a psychological concept it is very close to that of self-esteem, but with a lower ‘demand’ or a greater ‘generosity’, when we encounter failures, mistakes or even defeats along the way, which offers us greater protection from the risk of abandonment and therefore reinforces persistence, a key element for any successful sports career [ 62 ].

It also has a very direct relationship with approach-achievement goals, since precisely one of the central aspects characterising this eudaimonic well-being and differentiating it from hedonic well-being is specifically its relationship with self-determined and persistent progress towards goals or achievements with incentive value for the person, as is sports performance evidently [ 63 ].

Finally, it is interesting to see how we can also find a facet or link relating to the aspects that are more closely-related to the need for human affiliation, with feeling part of a group or human collective, where we can recognise others and recognise ourselves in the achievements obtained and the social reinforcement of those themselves, as indicated by their relationship with perceived social support. This construct is very labile, in fact it is common to find results in which the pressure of social support is hardly differentiated, for example, from the parents of athletes and/or their coaches [ 64 ]. However, its relevance within this set of psychological variables and traits is proof of its possible conceptual validity.

Analysing the results obtained, the first conclusion is that in no case is an integrated model based solely on ‘positive’ variables or traits obtained, since some ‘negative’ ones appear (anxiety, stress, irrational thoughts), affecting the former.

The second conclusion is that among the positive elements the variable coping strategies (their use, or the perception of their effectiveness) and the traits of optimism, perfectionism and self-compassion prevail, since mental strength or psychological well-being (which also appear as important, but with a more complex nature) are seen to be participated in by the aforementioned traits.

Finally, it must be taken into account that the generation of positive elements, such as resilience, or the learning of coping strategies, are directly affected by the educational style received, or by the culture in which the athlete is immersed. Thus, the applied potential of these findings is great, but it must be calibrated according to the educational and/or cultural features of the specific setting.

Limitations

The limitations of this study are those evident and common in SR methodology using the PRISMA system, since the selection of keywords (and their logical connections used in the search), the databases, and the inclusion/exclusion criteria bias the work in its entirety and, therefore, constrain the generalisation of the results obtained.

Likewise, the conclusions must—based on the above and the results obtained—be made with the greatest concreteness and simplicity possible. Although we have tried to reduce these limitations as much as possible through the use of experts in the first steps of the method, they remain and must be considered in terms of the use of the results.

Future developments

Undoubtedly, progress is needed in research to more precisely elucidate the role of well-being, as it has been proposed here, from a bidirectional perspective: as a motivational element to push towards improvement and the achievement of goals, and as a product or effect of the self-determined and competent behaviour of the person, in relation to different factors, such as that indicated here of ‘perfectionism’ or the potential interference of material and social rewards, which are linked to sports performance—in our case—and that could act as a risk factor so that our achievements, far from being a source of well-being and satisfaction, become an insatiable demand in the search to obtain more and more frequent rewards.

From a practical point of view, an empirical investigation should be conducted to see if these relationships hold from a statistical point of view, either in the classical (correlational) or in the probabilistic (Bayesian Networks) plane.

The results obtained in this study, exclusively researched from the desk, force the authors to develop subsequent empirical and/or experimental studies in two senses: (1) what interrelationships exist between the so called ‘positive’ and ‘negative’ psychological variables and traits in sport, and in what sense are each of them produced; and, (2) from a global, motivational point of view, can currently accepted theoretical frameworks, such as SDT, easily accommodate this duality, which is becoming increasingly evident in applied work?

Finally, these studies should lead to proposals applied to the two fields that have appeared to be relevant: educational and cultural.

Application/transfer of results

A clear application of these results is aimed at guiding the training of sports and physical exercise practitioners, directing it towards strategies for assessing achievements, improvements and failure management, which keep them in line with well-being enhancement, eudaimonic, intrinsic and self-determined, which enhances the quality of their learning and their results and also favours personal health and social relationships.

Data availability

There are no further external data.

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Article Contents

Introduction, literature search, physeal injuries and growth disturbance, residual problems after injury in athletes, outcomes of operative management of common sports injuries, conclusions.

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Sport injuries: a review of outcomes

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Nicola Maffulli, Umile Giuseppe Longo, Nikolaos Gougoulias, Dennis Caine, Vincenzo Denaro, Sport injuries: a review of outcomes, British Medical Bulletin , Volume 97, Issue 1, March 2011, Pages 47–80, https://doi.org/10.1093/bmb/ldq026

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Injuries can counter the beneficial aspects related to sports activities if an athlete is unable to continue to participate because of residual effects of injury. We provide an updated synthesis of existing clinical evidence of long-term follow-up outcome of sports injuries. A systematic computerized literature search was conducted on following databases were accessed: PubMed, Medline, Cochrane, CINAHL and Embase databases. At a young age, injury to the physis can result in limb deformities and leg-length discrepancy. Weight-bearing joints including the hip, knee and ankle are at risk of developing osteoarthritis (OA) in former athletes, after injury or in the presence of malalignment, especially in association with high impact sport. Knee injury is a risk factor for OA. Ankle ligament injuries in athletes result in incomplete recovery (up to 40% at 6 months), and OA in the long term (latency period more than 25 years). Spine pathologies are associated more commonly with certain sports (e.g. wresting, heavy-weight lifting, gymnastics, tennis, soccer). Evolution in arthroscopy allows more accurate assessment of hip, ankle, shoulder, elbow and wrist intra-articular post-traumatic pathologies, and possibly more successful management. Few well-conducted studies are available to establish the long-term follow-up of former athletes. To assess whether benefits from sports participation outweigh the risks, future research should involve questionnaires regarding the health-related quality of life in former athletes, to be compared with the general population.

Participation in sports is widespread all over the world, 1 with well-described physical, psychological and social consequences for involved athletes. 2–5 The benefits associated with physical activity in both youth and elderly are well documented. 2 , 6–8 Regular participation in sports is associated with a better quality of life and reduced risk of several diseases, 1 , 9 allowing people involved to improve cardiovascular health. 10 , 11 Both individual and team sports are associated with favourable physical and physiological changes consisting of decreased percentage of body fat 12 and increased muscular strength, endurance and power. 13 , 14 Moreover, regular participation in high-volume impact-loading and running-based sports (such as basketball, gymnastics, tennis, soccer and distance running) is associated with enhanced whole-body and regional bone mineral content and density, 14 , 15 whereas physical inactivity is associated with obesity and coronary heart disease. 16 Sports are associated with several psychological and emotional benefits. 7 , 17 , 18 First of all, there is a strong relationship between the development of positive self-esteem, due to testing of self in a context of sport competition, 19 reduced stress, anxiety and depression. 20 Physical activities also contribute to social development of athletes, prosocial behaviour, fair play and sportspersonship 21 and personal responsibility. 22

Engaging in sports activities has numerous health benefits, but also carries the risk of injury. 7 , 23 , 24 At every age, competitive and recreational athletes sustain a wide variety of soft tissue, bone, ligament, tendon and nerve injuries, caused by direct trauma or repetitive stress. 25–35 Different sports are associated with different patterns and types of injuries, whereas age, gender and type of activity (e.g. competitive versus practice) influence the prevalence of injuries. 7 , 36 , 37

Injuries in children and adolescents, who often tend to focus on high performance in certain disciplines and sports, 24 include susceptibility to growth plate injury, nonlinearity of growth, limited thermoregulatory capacity and maturity-associated variation. 9 In the immature skeleton, growth plate injury is possible 38 and apophysitis is common. The most common sites are at the knee (Osgood-Schlatter lesion), the heel (Sever's lesion) and the elbow. 39 Certain contact sports, such as rugby, for example, are associated with 5.2 injuries per 1000 total athletic exposures in high school children (usually boys). These were more common during competition compared with training and fractures accounted for 16% of these injuries, whereas concussions (15.8%) and ligament sprains (15.7%) were almost as common. 40

Sports trauma commonly affects joints of the extremities (knee, ankle, hip, shoulder, elbow, wrist) or the spine. Knee injuries are among the most common. Knee trauma can result in meniscal and chondral lesions, sometimes in combination with cruciate ligament injuries. 37 Ankle injuries constitute 21% of all sports injuries. 41 Ankle ligament injuries are more commonly (83%) diagnosed as ligament sprains (incomplete tears), and are common in sports such as basketball and volleyball. Ankle injuries occur usually during competition and in the majority of cases, athletes can return to sports within a week. 42 Hip labral injuries have drawn attention in recent years with the advent of hip arthroscopy. 43 , 44 Upper extremity syndromes caused by a single stress or by repetitive microtrauma occur in a variety of sports. Overhead throwing, long-distance swimming, bowling, golf, gymnastics, basketball, volleyball and field events can repetitively stress the hand, wrist, elbow and shoulder. Shoulder and elbow problems are common in the overhead throwing athlete whereas elbow injuries remain often unrecognized in certain sports. 45 Hand and wrist trauma accounts for 3–9% of all athletic injuries. 46 Wrist trauma can affect the triangular fibrocartilage complex 47 or cause scaphoid fractures, 48 whereas overuse problems (e.g. tenosynovitis) are not uncommon. 49 Spinal problems can range from lumbar disc herniation, 39–42 to fatigue fractures of the pars interarticularis, 50 and ‘catastrophic’ cervical spine injuries. 51

Thus, in addition to the beneficial aspects related to sports activities, injuries can counter these if an athlete is unable to continue to participate because of residual effects of injury. Do injuries in children, adolescents and young adults have long-term consequences? What are the outcomes of the most commonly performed surgical procedures? The aim of this review is to provide an updated synthesis of existing clinical evidence of long-term follow-up outcome of sports injuries.

An initial pilot Pubmed search using the keywords ‘sports’, ‘injury’, ‘injuries’, ‘athletes’, ‘outcome’, ‘long term’, was performed. From 1467 abstracts that were retrieved and scanned we identified the thematic topics (types of injury, management, area of the body involved) of the current review, listed below:

Then a more detailed search of PubMed, Medline, Cochrane, CINAHL and Embase databases followed. We used combinations of the keywords: ‘sport’, ‘sports’, ‘youth sports’, ‘young athletes’, ‘former athletes’, ‘children’, ‘skeletally immature’, ‘adolescent’, ‘paediatric’, ‘pediatric’, ‘physeal’, ‘epiphysis’, ‘epiphyseal injuries’, ‘hip’, ‘knee’, ‘ankle’, ‘spine’, ‘spinal’, ‘shoulder’, ‘elbow’, ‘wrist’, ‘football players’, ‘football’, ‘soccer’, ‘tennis’, ‘swimmers’, ‘swimming’, ‘divers’, ‘wrestlers’, ‘wrestling’, ‘cricket’, ‘gymnastics’, ‘skiers’, ‘baseball’, ‘basketball’, ‘osteoarthritis’, ‘former athletes’, ‘strain’, ‘contusion’, ‘distortion’, ‘injury’, ‘injuries’, ‘trauma’, ‘drop out’, ‘dropping out’, ‘attrition’, ‘young’, ‘ youth’, ‘sprain’, ‘ligament’, ‘ACL’, ‘cruciate ligament’, ‘meniscus’, ‘meniscal’, ‘chondral’, ‘labrum’, ‘labral’, ‘reconstruction’, ‘arthroscopy’, ‘throwing’, ‘overhead’, ‘rotator cuff’, ‘TFCC’, ‘scaphoid’, ‘osteoarthritis’, ‘arthritis’, ‘long term’, ‘follow-up’ and ‘athlete’. The most recent search was performed during the second week of November 2009.

Osteoarthritis (OA) in former athletes

Spine problems in former athletes

Knee injury and OA

Ankle ligament injury and OA

Residual upper limb symptoms in the ‘overhead’ athlete

Meniscectomy and oa, meniscal repair in athletes.

Anterior cruciate ligament (ACL) reconstruction and OA

ACL reconstruction in children

Ankle arthroscopy in athletes, hip arthroscopy in athletes.

Operative management of shoulder injuries in athletes (focusing on surgery for instability and labral tears)

Operative management of wrist injuries in athletes (focusing on triquetral fibrocartilage complex, TFCC, injuries and scaphoid fractures)

Given the different types of sports injuries in terms of location in the body, several searches were carried out. The search was limited to articles published in peer-reviewed journals.

From a total of 2596 abstracts that were scanned, 1247 studies were irrelevant to the subject and were excluded. The remaining studies were categorized in the topics identified earlier. We excluded from our investigation case reports, letter to editors and articles not specifically reporting outcomes, as well as ‘kin’ studies (studies reporting on the same patients' population). The most recent study or the study with the longest follow-up was included. In some topics of particular importance, such as the effect of knee injuries (given their frequency), we included long-term studies reporting not only on athletes, but also on the general population (usually in these studies a very high proportion on sports injuries is included). Regarding knee injuries in adults, we included articles with follow-up more than 10 years.

Given the linguistic capabilities of the research team, we considered publications in English, Italian, French, German, Spanish and Portuguese.

A concern regarding children's participation in sports is that the tolerance limits of the physis may be exceeded by the mechanical stresses of sports such as football and hockey or by the repetitive physical loading required in sports such as baseball, gymnastics and distance running. 52 Unfortunately, what is known about the frequency of acute sport-related physeal injuries is derived primarily from case reports and case series data. In a previous systematic review on the frequency and characteristics of sports-related growth plate injuries affecting children and youth, we found that 38.3% of 2157 acute cases were sport related and among these 14.9% were associated with growth disturbance. 24 These injuries were incurred in a variety of sports, although football is the sport most often reported. 53

There are accumulating reports of stress-related physeal injuries affecting young athletes in a variety of sports, including baseball, basketball, climbing, cricket, distance running, American football, soccer, gymnastics, rugby, swimming, tennis. 24 Although most of these stress-related conditions resolved without growth complication during short-term follow-up, there are several reports of stress-related premature partial or complete distal radius physeal closure of young gymnasts. 25–29 These data indicate that sport training, if of sufficient duration and intensity, may precipitate pathological changes of the growth plate and, in extreme cases, produce growth disturbance. 24 , 32

Disturbed physeal growth as a result of injury can result in length discrepancy, angular deformity or altered joint mechanics and may cause significant long-term disability. 33 However, the incidence of long-term health outcome of physeal injuries in children's and youth sports is largely unknown.

Based on the previously selection criteria, 20 studies 54–73 were retained for analysis (Table  1 ). Injury to the physis can result in limb deformities and leg-length discrepancy, the latter being more common after motor vehicle accidents, rather than sports participation.

Evidence on acute physeal injury with subsequent adverse affects on growth.

OA in former athletes

Two studies investigated former top-level female gymnasts for residual symptoms (back pain) and radiographical changes. 74 , 75 Both studies reported no significant differences in back pain between gymnast and control groups; however, the prevalence of radiographical abnormalities was greater in gymnasts than controls in one study. 74

Lower limb weight-bearing joints such as the hip and the knee are at risk of developing OA after injury or in the presence of malalignment, especially in association with high impact sport. 76 Varus alignment was present in 65 knees (81%) in 81 former professional footballers (age 44–70 years), whereas radiographic OA in 45 (56%). 77 Others showed that prevalence of knee OA in soccer players and weight lifters was 26% (eight athletes) and 31% (nine athletes), respectively, whereas it was only 14% in runners (four athletes). 78 By stepwise logistic regression analysis, the increased risk is explained by knee injuries in soccer players and by high body mass in weight lifters. A survey in English former professional soccer players revealed that 47% retired because of an injury. The knee was most commonly involved (46%), followed by the ankle (21%). Of all respondents, 32% had OA in at least one lower limb joint and 80% reported joint pain. 79 Another study examined the incidence of knee and ankle arthritis in injured and uninjured elite football players. The mean time from injury was 25 years. 80 Arthritis was present in 63% of the injured knees and in 33% of the injured ankles, whereas the incidence of arthritis in uninjured players was 26% in the knee and 18% in the ankle. Obviously, it should be kept in mind that radiographic studies can only ascertain the presence of degenerative joint disease, which is just one of the features of OA. Clinical examination is always necessary to clarify the diagnosis, and formulate a management plan.

Ex-footballers also had high prevalence of hip OA (odds ratio: 10.2), 81 whereas in another study the incidence of hip arthritis was 5.6% among former soccer players (mean age: 55 years) compared with 2.8% in an age-matched control group. In 71 elite players it was higher (14%). Female ex-elite athletes (runners, tennis players) were compared with an age-matched population of women, and were found to have higher rates (2–3 fold increase) of radiographic OA (particularly the presence of osteophytes) of the hip and knee. 82 The risk was similar in ex-elite athletes and in a subgroup from the general population who reported long-term sports activity, suggesting that duration rather than frequency of training is important. An older study 83 is runners associated degenerative changes with genu varum and history of injury. A cohort of 27 Swiss long-distance runners was at increased risk of developing ankle arthritis compared with a control group. 84 Similarly elite tennis players were at risk of developing glenohumeral OA, 85 whereas handball players of developing premature hip OA, 86 and former elite volleyball players had marginally increased risk for ankle OA. 87 Interestingly a study that investigated the health-related quality of life (HRQL) in 284 former professional players in the UK found that medical treatment for football-related injuries was a common feature, as was arthritis, with the knee being most commonly affected. Respondents with arthritis reported poorer outcomes in all aspects of HRQL. 88

In summary, OA is more common among former athletes, compared with the general population. The lower limb joints are commonly affected, in association with high impact and injury.

Evidence from follow-up studies on spine of former athletes

Heavy physical work and activity lead to degenerative changes in the spine. Studies on different athletic disciplines and heavy workers have given variable degenerative changes and abnormalities in the lumbar spine. Even though sporting activity is regarded as an important predisposing factor in the development of spinal pathologies, 89–99 there are few studies on the late spinal sequelae of competitive youth sport. Any comparison in terms of back pain between top athletes and the general population is difficult. Experience of pain may be influenced by factors such as susceptibility, motivation and physical activity. Minor pain may be provoked by vigorous body movements that hamper athletic performance, thereby ascribing the pain a greater impact than in the general population. On the other hand, a well-motivated athlete may ignore even severe pain to maintain or improve his/her athletic performance. Also, varying rate/prevalence of osteophytosis has been reported in players associated with various disciplines of sports.

Efforts should be made to understand the aetiology of injuries to the intervertebral discs during athletic performance and thereby prevent them. 74

Based on the previously selection criteria, seven studies 74 , 89 , 98 , 100–103 were retained for analysis (Table  2 ). In summary, spine pathologies are associated more commonly with certain sports (e.g. wresting, heavy-weight lifting, gymnastics, tennis, soccer). Degenerative changes in the athlete's spine can occur, but they are not necessarily associated with clinically relevant symptoms of OA. Therefore, it cannot be determined whether it threatens the athlete's career, or whether it has a worse impact on athletes compared with the general population.

Evidence from follow-up studies on spine of former athletes.

Knee injury and OA in athletes

A population-based case-control study investigated the risk of knee OA with respect to sports activity and previous knee injuries of 825 athletes competing in different sports. They were matched with 825 controls. After confounding factors were adjusted, the sports-related increase risk of OA was explained by knee injuries. 104 Another study leads to the same conclusion: 23 American football high-school players were compared with 11 age-matched controls, 20 years after high-school competition. No significant increase in OA could be demonstrated clinically or radiographically. However, a significant increase in knee joint OA was found in the subgroup of football players who had sustained a knee injury. 105

A cohort of 286 former soccer players (71 elite, 215 non-elite) with a mean age of 55 years was compared with 572 age-matched controls, regarding the prevalence of radiographic features of knee arthritis. Arthritis in elite players, non-elite players and controls was 15%, 4.2% and 1.6%, respectively. In non-elite players, absence of history of knee injury was associated with arthritis prevalence similar to the controls. 106

An interesting study involved a cohort of 19 high-level athletes of the Olympic program of former East Germany. They sustained an ACL tear between 1963 and 1965. None were reconstructed, and all were able to return to sports within 14 weeks. Subsequent meniscectomies were necessary in 15/19 (79%) athletes at 10 years and 18/19 (95%) at 20 years, when in 18 of the 19 knees, arthroscopy was performed, 13 patients (68%) had a grade four chondral lesion. By year 2000 (more than 35 years after ACL rupture), 10/19 knees required a joint replacement. 107

The incidence of radiographic advanced degeneration (Kellgren–Lawrence grade 2 or higher) was 41% in a cohort of 122 Swedish male soccer players (from a total of 154) who consented to radiographic follow-up, 14 years after an ACL rupture. No difference was found between players treated with or without surgery for their ACL rupture. The prevalence of Kellgren–Lawrence grade 2 or higher knee OA was 4% in the uninjured knees. 108

Similar results were evident among Swedish female soccer players who were injured before the age of 20. The prevalence of radiographic OA was 51%, compared with 8% only in the uninjured knee, 12 years later. The presence of symptoms was documented in 63 of 84 (75%) athletes who answered the questionnaire, and was similar ( P = 0.2) in the two management groups (operative versus non-operative). The presence of symptoms did not necessarily correlate with radiographic OA ( P = 0.4). 109

In summary, knee injury is a recognized risk factor for OA. Injured athletes develop OA more commonly than the general population in the long term. Approximately half of the injured knees could have radiographic changes 10–15 years later. It is not clear whether radiographic changes correspond to presence of symptoms.

Ankle ligament injuries and OA in athletes

Ankle sprains are common sporting injuries generally believed to be benign and self-limiting. However, some studies report a significant proportion of patients with ankle sprains having persistent symptoms for months or even years. Nineteen patients with a mean age of 20 years (range: 13–28), who were referred to a sports medicine clinic after an ankle inversion injury, were followed for 29 months (average), and compared with matched controls. Only five (26%) injured patients had recovered fully, whereas 74% had symptoms 1.5–4 years after the injury. Assessments of quality of life using the short form-36 questionnaires revealed a difference in the general health subscale between the two groups, favouring the controls ( P < 0.05). 110

Similar conclusions were drawn from another study, regarding ankle injuries in a young (age range: 17–24 years) athletic population. 111 There were 104 ankle injuries (96 sprains, 7 fractures and 1 contusion), accounting for 23% of all injuries seen. Of the 96 sprains, 4 were predominately medial injuries, 76 lateral and 16 syndesmosis sprains. Although 95% had returned to sports at 6 weeks, 55% reported pain or loss of function. At 6 months, 40% had not fully recovered, reporting residual symptoms. Syndesmosis injuries were associated with prolonged recovery.

The association between ligamentous ankle injuries has been highlighted in a study that, retrospectively, reviewed data from 30 patients (mean age: 59 years, 33 ankles) with ankle osteoarthritis. 112 They found that 55% had a history of sports injuries (33% from soccer), and 85% had a lateral ankle ligament injury. The mean latency time between injury and OA was 34.3 years. The latency period for acute severe injuries was significantly lower (25.7 years), compared with chronic instability (38 years). Varus malalignment and persistent instability were present in 52% of those patients.

In summary, ankle ligamentous injuries in athletes can result in considerable morbidity, residual symptoms and arthritis 25–30 years later.

Shoulder injuries account for 7% of sports injuries and often limit the athlete in his or her ability to continue with their chosen sport. 113 Repetitive overhead throwing imparts high valgus and extension loads to the athlete's shoulder and elbow, often leading to either acute or chronic injury or progressive structural change and long-term problems in the overhead athlete. 45

Schmitt et al . 102 examined 21 elite javelin throwing athletes at an average of 19 years after the end of their high-performance phase (mean age at follow-up was 50 years). Five athletes (24%) complained about transient shoulder pain and three (16%) about elbow pain in their throwing arm affecting activities of daily living. All dominant elbows had advanced degeneration (osteophytes).

Elbow intra-articular lesions are recognized as consequences of repetitive stress and overuse. Shanmugam and Maffulli 9 reported follow-up (mean 3.6 years) of lesions of the articular surface of the elbow joint in a group of 12 gymnasts (six females and six males). This group showed a high frequency of osteochondritic lesions, intra-articular loose bodies and precocious signs of joint ageing. Residual mild pain in the elbow at full extension occurring after activity was present in 10 patients and all patients showed marked loss of elbow extension compared with their first visit.

Glenoid labral tears require repair, and shoulder instability is currently approached operatively more often. A review article found that conservative management of traumatic shoulder dislocations in adolescents was associated with high rates of recurrent instability (up to 100%). Therefore, surgical shoulder stabilization is recommended. The outcomes of surgical management are presented in the next section.

A distinct clinical entity is the ‘little league shoulder’, which is characterized by progressive upper arm pain with throwing and is more commonly seen in male baseball pitchers between ages 11 and 14 years. It is thought to be Salter-Harris type I stress fracture. Activity modification, education to improve throwing mechanics and core muscle training are recommended. It is not known how this condition behaves in the long term, regarding structural damage and development of degenerative changes.

Overhead athletes are plagued by shoulder and elbow injuries or overuse syndromes that can affect their performance and cause degeneration and pain in the long term.

The association between knee OA and meniscectomy has been well documented. In former athletes 114 – 116 it is associated with OA (Table  3 ). Meniscectomy in children and adolescents 117 – 123 has been associated with unfavourable results and radiographic arthritic changes in the long term (Table  4 ). However, radiographic criteria were not always clearly defined. To assess the long-term outcomes of meniscectomy, we also evaluated studies with a minimum follow-up of 10 years in the adult general population 106 , 124 – 129 (Table  5 ). Many of the ‘older’ studies providing the long-term outcomes represent results of open total meniscectomies. The overall message is that radiographic degeneration is common in meniscectomized knees, and patients are at risk of developing OA. The condition of the articular cartilage is a prognostic factor. However, clinical and radiographic findings do not always correlate. Resection should be limited to the torn part of the meniscus.

Menicectomy and osteoarthritis in athletes.

Menicectomy in children and adolescents.

Meniscectomy in adults / general popaltion—long-term outcomes.

Given the long-term problems associated with meniscectomies, preservation of the substance of the meniscus after injury is currently advocated. Based on this concept, arthroscopic meniscal repair techniques have been developed. 125 In the general population, encouraging clinical results with failure rates of 27–30% at 6–7 years follow-up have been reported. 130–132 One study 133 evaluated 45 meniscal repairs in 42 elite athletes followed for an average of 8.5 years. In 83% of them an ACL reconstruction was performed as well. Return to their sport was possible in 81% at an average of 10 months after surgery. They identified 11 failures (24%), seven of which were associated with a new injury. The medial meniscus re-ruptured more frequently compared with the lateral (36.4 versus 5.6%, respectively).

Mintzer et al . 134 retrospectively reviewed the outcome of meniscal repair in 26 young athletes involved in several sports at an average follow-up of 5 years (range: 2–13.5). No failures were reported, with 85% of patients performing high level of sports activities.

In general, the results of meniscal repairs in the general population, as well as in athletes, are encouraging.

ACL reconstruction and OA

Knee injuries can result in ligament ruptures and/or meniscal tears and are recognized as a risk factor of OA. A systematic review on studies published until 2006 135 reported on the prognosis of conservatively managed ACL injuries showed that there was an average reduction of 21% at the level of activities (Tegner score evaluation). ACL reconstruction is therefore a procedure frequently performed in athletic individuals, as they desire to maintain a high level of activities. However, does ACL reconstruction affect the incidence of knee degeneration and symptoms in the long term? We identified three studies 108 , 109 , 136 comparing operative versus non-operative management of ACL ruptures specifically in athletes, in regard to OA.

Two studies from Sweden investigating the prevalence of OA after ACL rupture in male 108 and female 109 soccer players were discussed earlier. Both found no difference in the incidence of radiographic arthritis between surgically and conservatively treated players, more than 10 years after their injury.

A comparative study 136 on high-level athletes with ACL injury showed no statistical difference between the patients treated conservatively or operatively (patella tendon graft) with respect to OA or meniscal lesions of the knee, as well as activity level, objective and subjective functional outcome. The patients who were treated operatively had a significantly better stability of the knee at examination.

Several studies present outcomes of ACL injuries in the general population. A recent systematic review included 31 studies (seven were prospective) reporting radiographic outcomes regarding OA, with more than 10 years follow-up after ACL injury. 137 The prevalence of OA in the injured knee varied from 1 to 100%, whereas in the contralateral knee it was 0–38%. Isolated ACL tears were associated with low OA incidence between 0 and 13%, whereas in the presence of additional meniscal injury, it was 21–48%. Meniscal injury and meniscectomy were the most frequently reported risk factors for OA. The authors scored the quality of the studies and found that studies scoring high reported low incidence of OA. Data extraction indicated that ACL reconstruction as a single factor did not prevent the development of knee OA. 137

There is lack of evidence to support a protective role of reconstructive surgery of the ACL against OA, both in athletes as well as in the general population.

ACL reconstruction in skeletally immature patients is a relatively new trend. 138 The concern is intra-operative epiphysis damage and growth disturbance, a complication which has been avoided in several studies. 139–143

The earliest published study 144 compared non-operative versus operative management of ACL ruptures in 42 skeletally immature athletes (age range: 4–17 years) followed for a mean of 5.3 years. They used a composite knee score based on clinical examination and a patient questionnaire and found superior results in the operatively treated patients. Age and growth plate maturity did not influence results. They recommended ACL reconstruction for active athletic children.

One of the early reports showed that there were no growth disturbances at a mean of 3.3 years after surgery in 9 children, however, with two re-ruptures. Those children could not return to athletic activities. 139

In a series of 57 ACL reconstructions, 15 patients had reached completion of growth when examined at follow-up, none had signs of growth disturbance, whereas clinical scoring was good or excellent in all patients. 142

Another study compared the outcomes of two management strategies in 56 children with ACL ruptures, namely ligament reconstruction in the presence of open physis, or delayed reconstruction after skeletal maturity. The ‘early’ reconstruction group had evidence of less medial meniscal tears (16 versus 41%), and no evidence of growth disturbances, at 27 months mean follow-up. 140

After 1.5–7.5 years follow-up of 19 ACL reconstructions in 20 athletic teenagers (age range: 11.8–15.6 years), all but one had returned to sports, none had tibiofemoral malalignment or a leg-length discrepancy of more than 1 cm, and the modified Lysholm score was 93 out of 95. 143

Finally, 55 children (ages 8 to 16 years, mean 13 years) were followed for a mean of 3.2 years (range: 1–7.5 years) after ACL reconstruction, with no evidence of growth disturbances. Clinical scores showed normal or almost normal values (higher than 90 out of 100 possible points) and 88% of the patients went back to normal or almost normal sports according to the Tegner score. 141

Overall, the clinical results are encouraging and iatrogenic epiphysis damage does not seem to be a problem, possibly because physeal sparing procedures were used. The study designs, however, are inadequate to answer the question of whether early or delayed ACL reconstruction results in the best possible outcome in skeletally immature patients.

Anterior impingement syndrome is a generally accepted diagnosis for a condition characterized by anterior ankle pain with limited and painful dorsiflexion. The cause can be either soft tissue or bony obstruction. Arthroscopic debridement is currently considered a routine procedure, and chondral lesions are now more frequently identified as causes of ankle pain. Few reports specifically in athletes are available 145–149 (Table  6 ). Short-term outcomes only are available. It is not known whether arthritis is a long-term consequence.

Ankle arthroscopy in athletes.

Only recently has the hip received attention as a recognized site of sports injuries, possibly as a result of the evolution of hip arthroscopy which allowed recognition of intra-articular pathology. 150 Acetabular labrum and chondral lesions can be addressed arthroscopically, and patients' satisfaction rates up to 75% have been reported. 44 One study evaluated the outcome of hip arthroscopy in 15 athletes (mean age: 32 years, range: 14–70) followed for 10 years. Nine were recreational athletes, four high school and two intercollegiate athletes. Diagnoses included cartilage lesion (8), labral tear (7), arthritis (5), avascular necrosis (1), loose body (1) and synovitis (1). The median improvement in the modified Harris hip score was 45 points (from 51 preoperatively to 96, on the 100-point scale), with 13 patients (87%) returning to their sport. All five athletes with arthritis eventually underwent total hip arthroplasty at an average of 6 years. 43 Long-term outcomes regarding progression of joint degeneration after traumatic chondral or labral damage are not available.

Operative management of shoulder injuries in athletes

Labral tears require repair, whereas shoulder instability is currently approached operatively more often. Conservative management of traumatic shoulder dislocations in adolescents is associated with high rates of recurrent instability (up to 100%), whereas recurrent dislocations were reported in up to 12%, at an average of 3 years after arthroscopic stabilization. Shoulder dislocations are particularly common in rugby, the characteristic mechanism of injury being tackling, whereas labral tears are common in the ‘overhead’ athlete'. Published results in athletes 151 – 162 (Table  7 ) show that operative stabilization of the shoulder is initially successful, but instability and pain can recur in the long term. Results of arthroscopic techniques in the management of intra-articular pathologies are promising, but long-term outcomes are unknown (Table  7 ).

RCT, randomized controlled trial; VAS, visual analogue scale.

Operative management of elbow injuries in athletes

Elbow ulnar collateral ligament (UCL) insufficiency is one of the frequently recognized injuries in the overhead athlete, as a result of excessive valgus stress. It constitutes a potentially career threatening injury and requires surgical repair. 163 The use of a muscle-splitting approach, avoiding handling of the ulnar nerve, and the use of the docking technique for stabilization is recommended 164 , 165 (Table  8 ). Recent advantages in arthroscopic surgical techniques and ligament reconstruction in the elbow have improved the prognosis for return to competition for highly motivated athletes. The results of arthroscopic debridement 150 , 166 (Table  7 ) need to be evaluated in the long term.

Operative management of elbow injuries in athletes.

UCL, ulnar collateral ligament.

Operative management of wrist injuries in athletes

A review of the literature shows that 3–9% of all athletic injuries occur in the hand or wrist, and are more common in adolescent athletes than adults. 46 In this article, we focused on TFCC injuries and acute scaphoid fractures in athletes.

TFCC injuries are an increasingly recognized cause of ulnar-sided wrist pain, and can be particularly disabling in the competitive athlete. Advances in wrist arthroscopy made endoscopic debridement and repair of the TFCC possible. McAdams et al . 47 treated arthroscopically TFCC tears in 16 competitive athletes (mean age: 23.4 years). Repair of unstable tears was performed in 11 (69%) and debridement only in 5 (31%). Return to play averaged 3.3 months (range: 3–7 months). The mean duration of follow-up was 2.8 years (range: 2–4.2 years). Clinical scores (mini-DASH and mini-DASH sports module) improved significantly. No long-term outcomes are available.

Operative management of scaphoid fractures in athletes, even if undisplaced, is recommended if early return to sports is desired. One study followed 12 athletes treated operatively for a scaphoid fracture. They were able to return to sports at 6 weeks. At an average follow-up of 2.9 years, 9 of 12 athletes had range of motion equal to the uninjured side, and grip strength was equal to the unaffected side in 10 of 12 athletes. 49

Participation in sports offers potential benefits for individuals of all ages, such as combating obesity and enhancing cardiovascular fitness. 1 On the other hand, negative consequences of musculoskeletal injuries sustained during sports may compromise function in later life, limiting the ability to experience pain-free mobility and engage in fitness-enhancing activity. 167 Increasingly, successful management of sports-related injuries has allowed more athletes to return to participation. The knee is the joint most commonly associated with sports injuries, and therefore is most at risk of developing degenerative changes. It is not clear whether radiographic OA always correlates with symptoms and reduced quality of life. Furthermore, even effective management of meniscal or ACL injury does not reduce the risk of developing subsequent OA. 137 , 168 OA in an injured joint is caused by intra-articular pathogenic processes initiated at the time of injury, combined with long-term changes in dynamic joint loading. Variation in outcomes involves not only the exact type of injury (e.g. ACL rupture with or without meniscal damage), 137 but also additional variables associated with the individual such as age, sex, genetics, obesity, muscle strength, activity and reinjury. A better understanding of these variables may improve future prevention and treatment strategies. 169

In many of the long-term studies (the majority being retrospective case series), several methodological flaws have to be highlighted. A recent systematic review on OA after ACL injuries 137 suggested that some studies may overestimate the prevalence of long-term OA. The authors in several studies mention that a proportion of the index group of injured athletes were available for follow-up or consented for radiographic examination. One can argue that these patients were the ones with symptoms, therefore the prevalence of OA (after ACL rupture for example) may appear higher than it really is. Presentation of outcomes was not always based on robust criteria. Different clinical scores and radiographic classifications have been used, and therefore results between studies are not directly comparable. In the majority of the studies, it was not clarified whether radiographic appearance correlated with symptoms, and how important these were for the quality of life of the patients. Disabling arthritis requiring intervention may actually be delayed for more than 20–30 years. 107 , 112 Furthermore, long-term studies present outcomes of older techniques, not used any more in clinical practice (e.g. primary ACL repair or total meniscectomy). Evolution in surgical or rehabilitation techniques might have improved outcomes of certain injuries. Therefore, currently known ‘long-term outcomes’ may only reflect the results of techniques used in the past and not what we should expect in the future. Increasing awareness of athletes and trainers, new diagnostic and musculoskeletal imaging modalities, improved surgical and rehabilitation methods, but also analysis of injury patterns in different sports and development of injury prevention strategies might be beneficial to minimize the effects of sports injuries in the years to come.

What is the true incidence of arthritis in the long term? Will it be a disabling condition for the former athlete, in the coming decades? Currently, joint preserving procedures (e.g. microfractures, 145 mosaicplaty, 170 autologous chondrocyte implantation, 171 , 172 realignment osteotomies 173 and implant arthroplasties 174 ) have evolved and allow middle aged or older patients to live without pain and maintain an active life style. Meniscal transplantation shows encouraging results. 175 Should therefore an increased risk for developing musculoskeletal problems prevent children and adults from being active in sports? 176 Do the benefits of participating in sports outweigh the risks?

A survey in Sweden showed that 80% of former track and field athletes with an age range of 50–80 years felt they were in good health, compared with 61% of the referents, despite higher prevalence of hip arthritis in former athletes. Low back disorders were similar in the two groups, shoulder and neck problems were lower in former athletes, and knee arthritis was similar in the two groups. 177

No definite answer can be given to the previously addressed questions, based on available evidence. Future research should involve questionnaires assessing the HRQL in former athletes, to be compared with the general population. 27 , 178–181

Physical injury is an inherent risk in sports participation and, to a certain extent, must be considered an inevitable cost of athletic training and competition. Injury may lead to incomplete recovery and residual symptoms, drop out from sports, and can cause joint degeneration in the long term. Few well-conducted studies are available on the long-term follow-up of former athletes, and, in general, we lack studies reporting on the HRQL to be compared with the general population. Advances in arthroscopic techniques allow operative management of most intra-articular post-traumatic pathologies in the lower and upper limb joints, but long-term outcomes are not available yet. It is important to balance the negative effects of sports injuries with the many social, psychological and health benefits that a serious commitment to sport brings. 9

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Sports are supposed to be for all – but new research reveals just how few LGBTQI+ people play sport

Research fellow, Swinburne University of Technology

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Disclosure statement

Ryan Storr consults to Proud2Play. He receives funding from VicHealth. He is affiliated with Proud2Play.

Carleigh Yeomans consults to and conducts research for a number of organisation across Australia. Her research has received funding from organisations including VicHealth.

Kath Albury receives funding from the Australian Research Council, FORTE (the Swedish Research Council for Health, Working Life and Welfare, and VicHealth.

Swinburne University of Technology provides funding as a member of The Conversation AU.

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The topic of homophobia in sport has recently made headlines in Australia, with a series of homophobic incidents involving men’s AFL players.

These homophobic incidents are usually well-reported in news media, but research has rarely explored the impact on participation for LGBTQI+ people.

Fresh research into the problem

Our new research is one of the first pieces of academic research in Australia to document how many LGBTQI+ people play and engage with sport. We also explored current levels of discrimination across sport in Australia, and the barriers and enablers of participation for young LGBTQI+ people.

Our research focused specifically on LGBTQI+ people aged 16-25 across community sport and movement settings (including gyms and leisure spaces), and was funded by VicHealth.

Previous research has shown young LGBTQI+ people are targeted with homophobia and transphobia in school and youth sport environments, and this affects them in several ways.

Specifically, it affects their mental health , with an increased risk of depression and anxiety, and forces them to drop out of sport – with many choosing to not play sport as adults.

The decline of LGBTQI+ youth participation

Our research showed 47% of LGBTQI+ youth were registered to a sports club between 2019 and 2022. Then, in 2023, just 33% of our sample said they currently participate in some form of competitive sport.

Comparable data from AusPlay show around 60% of young people across the broader population play sport.

Within different segments of the LGBTQI+ community, our data show just 31% of gay men and 29% lesbians play competitive sport, and even fewer within trans and gender diverse groups.

Therefore, our data support previous research from the United States that show young LGBTQI+ people engage with sport at half the rate of non-LGBTQI+ youth.

Trying to find a reason why

There is often much discussion within media about why there are very few openly gay men in professional sport. Our data highlight one of the reasons – gay men are less likely to play sport in the first place.

Some of the key barriers identified by participants were a lack of safe spaces, negative or traumatic early experiences, and discrimination.

Of those participants who do play sport, only 49% openly share their LGBTQI+ identity with teammates and coaches.

Ongoing discrimination is a key driver of why LGBTQI+ youth disengage from playing sport, and a reason why young people reported little-to-no sense of belonging within sports environments.

Some improvements seen but not for gay men

Overall, our research showed 53% of LGBTQI+ youth have witnessed discrimination (through homophobia, biphobia or other transphobia), and 40% have experienced discrimination.

These levels of discrimination show some marked improvement since the last major study in 2014 exploring homophobia in Australian sport, in which about 80% of respondents reported witnessing homophobia.

This suggests increased efforts to promote inclusion for LGBTQI+ people in sport is having a positive impact.

However, our data showed 76% of gay men have witnessed homophobia in sport, which shows little marked improvement in a decade.

Across our focus groups, young people spoke of negative early experiences in school sport, and the negative effects of ongoing debates related to LGBTQI+ issues in sport (such as trans athlete bans , or participation in pride games ).

Most striking across our focus groups was the desire for young people to be able to be themselves when playing sport and “just exist”.

The notion of having freedom and to not have their identity challenged, questioned, ridiculed or invalidated while navigating sporting spaces was discussed extensively.

Hopes for the future

Young people discussed the ways in which sport organisations could work towards making them feel safer and included.

They also had strong views towards pride efforts, raising issues with “ rainbow washing ”, a lack of engagement with LGBTQI+ communities, and minimal commitment to addressing discrimination.

One young person in our study expressed:

“I would like to see a little bit more effort, instead of chucking us in a box saying ‘it’s too difficult to work out’. ‘We’re going to include you’ would be a good next step. But I think a lot of work needs to be done to feel welcomed again.”

Our data show targeted efforts and programs are urgently needed to ensure sport and movement settings do not continue to cause harm and force LGBTQI+ youth to drop out from sport.

Additionally, the data raise significant challenges for the broader sport sector and its ongoing sustainability.

Every sport wants new players and fans, but the sport sector risks losing a whole generation of young people unless it fully commits to reducing and eradicating discrimination towards LGBTQI+ people.

This work should also complement and sit alongside other important work addressing gender-based violence , and work addressing backlash to feminism and gender equity among teenage boys in schools.

Sport organisations must take immediate steps to ensure their environments are fully inclusive of LGBTQI+ people.

This can be done through good policy development and effective implementation, anti-homophobia initiatives and campaigns, and engaging LGBTQI+ sport communities.

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Humanities scholars research free speech, AI, sports culture and the Supreme Court

5/21/2024 By | Kathy Hovis , A&S Communications

Elizabeth Rene ’24 has had an interest in the court system since her high school days watching “Law and Order,” but she became particularly attentive to what was going on in the Supreme Court when Donald Trump became president.

“It was the greatest attack on our democracy and a lot of students my age felt this,” she said. “We started seeing invalidations of landmark precedents, such as Roe vs. Wade, and you don’t see that happening very often in democracies, where you establish a constitutional precedent and then get rid of it.”

That curiosity to understand what was going on in the court, an institution that is supposed to be impartial, sparked Rene to focus on the court for her senior thesis in the Humanities Scholars Program (HSP). She presented her work, along with 34 other students at the HSP Spring Research Conference May 3 at the A.D. White House.

“This year’s HSP conference was spectacular. The range of topics covered, the diversity of approaches, and the level of mastery demonstrated by the students were inspiring,” said Lawrence B. Glickman , Stephen and Evalyn Milman Professor of American Studies in the Department of History and interim director of the Humanities Scholars Program. “So too was the support that their friends, classmates, and teachers demonstrated with their presence and their questions. It was a marvelous demonstration that humanistic scholarship at Cornell is thriving.” 

VerityPlatt , professor of classics, will take over as HSP director this fall. 

“It has been very exciting to see the HSP develop under the inspired leadership of Durba Ghosh and Larry Glickman into a dynamic program that nurtures undergraduate research in the humanities,” she said. “I am honored to be taking on this new role and look forward to working closely with the dedicated, creative, and inspiring students of the HSP.”

At the May event, students covered topics focused on countries around the globe and ranging from immigration, home care workers and female sports culture to the U.S.-China relationship, the repatriation of cultural objects and AI and literature.

Victoria Rinn ’24 used the resources of the Cornell Law Library, as well as an interview with her grandmother, as she compared the way legal language impacts identity politics and freedom of expression in China and Hong Kong.

“I've always been interested in the history of Hong Kong because my family escaped communist China—when Mao Zedong began persecuting the land-owning members of society—to Hong Kong not only because of the economic freedoms but also due to the larger degree of individual autonomy due to its colonial status,” she said. “Following the 2019 National Security Law protests in Hong Kong, I began to question the intersection between legislation and individual expression.”

Rinn, who plans to attend law school, said the research methods course offered to HSP students, as well as many of her classes in the China and Asia-Pacific Studies Program, were instrumental as she worked on her project.

“My government major seminar focused on China, Tibet and Xinjiang, thereby granting me the research tools necessary for my Humanities Scholars research topic,” she said. “Moreover, the Humanities Scholars Program granted me a cohort of intellectually-alike students who share a passion for the arts as I do.”

Ethan Kovnat ’24, a philosophy major, centered his work on autism and moral psychology, responding to a paper by philosopher Jeanette Kennett, who argued that since people with autism experience empathy in a different way, they cannot be considered “moral agents” under the traditional philosophical definition put forth by philosopher David Hume.

“I read this paper and thought ‘something doesn’t seem quite right,’ “ Kovnat said. “One of the things that I appreciate about Kennett is that she cites myriad psychological evidence to support her conception, but I encountered more recent literature and found empirical evidence that better reflected the actual experiences of autistic people. 

“I’m arguing that Hume’s conception of agency, slightly amended, is able to accommodate autistic moral agents.”

Kovnat said his HSP cohort provided a valuable network for peer review. “Whenever I wrote something, I had this community I could go to for advice and feedback,” he said.

Rene’s research project focused on two justices, Clarence Thomas and Antonin Scalia, and their different understandings of “originalism,” a way of interpreting the U.S. Constitution following how it would have been understood at the time it was written.

“Originalism rose as a theory after the conservative backlash following the Warren court,” Rene said, referring to the period between 1953-1969 when Earl Warren served as chief justice of the court and the court handled such landmark cases as Brown v. Board of Education, Plessy v. Ferguson and Miranda v. Arizona.

Rene studied five major cases that set precedent during the Warren court, including 15 others to better understand the actions and motivations of Thomas and Scalia.

“Clarence Thomas has a tendency to encourage the court to reverse a whole bunch of precedents set decades and decades ago,” she said. “My analysis consisted of looking back and forth at moments in history to see why that precedent was so important to be established in the first place and then looking at the modern era to see how it’s been threatened by the conservative supermajority on the court today.”

The conservatives on the court, Rene argues, claim that their opinions are neutral using originalism at their defense, but the numerous inconsistencies in the way these interpretations happen allow strong polarizations to impact the court’s decisions.

“Justices are always going to possess some degree of political bias, but the degree to which the supreme court is intertwined with other branches is a recent development,” she said. 

Her classes in constitutional law, along with a class taught by Alexander Livingston , associate professor of government and a member of the HSP Faculty Advisory Board, focused on W.E.B. DuBois and Martin Luther King, helped her craft her work, as they “taught me how to extrapolate someone’s writing, but also the background of the life they lived before writing that,” she said.

Rene said she also appreciated the close relationship she developed with her advisors because of HSP. 

“As HSP students, we were actively seeing our advisors, who were really making sure we were using all of the resources available to us,” she said.

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Enlightening today’s church with relevant research and insights

Travel Sports Create Issues and Opportunities for Families and Churches

Pastor Views | Lifeway Research | Churchgoer Views and Practice | May 21, 2024

Based on their perspective on missing services for travel sports, many churchgoers see the potential impact differently than their pastors.

By Aaron Earls

Growing up, Aaron Bryant may have dreamed of playing in the NFL, but his family would’ve never dreamed of skipping church.

Bryant was part of the Tennessee Titans when they made the Super Bowl in 1999. Despite playing multiple sports in high school, he says he rarely missed church services because of it. “Primarily, my parents prioritized corporate worship for our family and established a precedent that our time with our church family on Sunday mornings was more important than anything else,” he said.

Today Bryant is the teaching pastor at the Church at Avenue South in Nashville, and like many pastors, sees some families missing because of sports.

A Lifeway Research study of both U.S. Protestant pastors and churchgoers found most in both groups believe it’s OK to miss church occasionally for a kid’s game or travel sporting event, but those in the pews are laxer on the issue than those behind the pulpit.

“Our culture no longer expects large numbers of people to be in church each week, so increasingly other events are also scheduled on Sundays,” said Scott McConnell, executive director of Lifeway Research. “Families whose kids play sports often have to choose between attending church or being with their team.”

Pastoral perspective

More than 1 in 3 U.S. Protestant pastors (36%) say it’s never OK to skip a weekly worship service for kid’s games or travel sporting events, but almost 3 in 5 (58%) see at least some allowance for missing in those circumstances. Around 3 in 10 (29%) believe it’s acceptable once or twice a year. A quarter (26%) say a few times a year, while 3% say many times a year. Another 6% say they aren’t sure.

Pastors 65 and older (43%) are among the most likely to say it’s never acceptable. Evangelical pastors are more likely than mainline pastors to say never (40% v. 28%). Those at the smallest churches, less than 50 in attendance, are also more likely than pastors at the largest churches, 250 or more, to believe skipping for sports is never OK (38% v. 24%).

Regardless of how accepting their pastor may be, Bryant said families often feel overwhelmed by all their tasks and events and feel as if they need to make a choice. “Unfortunately, for the children, when they choose to eliminate something from their schedules, it’s often corporate worship involvement so they can continue to remain involved with team sports,” he said.

RELATED: Weather Most Likely Reason for Churchgoers Skipping Services

Nate Walter, pastor at Goshen Christian Church in Goshen, Indiana, says the impact of travel sports on his congregation grew after COVID-19 restrictions were lifted. “There are many families with kids that we won’t see for the entire summer because they are constantly traveling to a different tournament,” he said.

Recent research agrees. A report published by the Aspen Institute found children ages 6-18 spent an average of 13.6 hours per week playing sports, including 4.6 hours of practice and 3.7 hours of competition, before COVID-19. While those all dropped during the pandemic, by September 2022, children were involved in sports for 16.6 hours per week, with 8.1 hours of practice and 3.7 hours of competition. According to Wintergreen Research , travel sports has grown into a $39 billion-a-year industry and is projected to reach $72 billion by 2029.

Walter also noted school sports and activities have crept into Sundays. “As many schools are limited to one gymnasium, they have to find time for all the athletic programs to practice, and Sunday evening is becoming a very common time,” he said. “This drastically affected our Sunday evening youth activities.”

Still, Bryant said he and his wife encourage their children to be involved in sports and extra-curricular activities, but they discuss together how it might affect their family. When advising other parents, Bryant said he encourages them to affirm their child’s desire to be involved in sports even if it involves some travel. “Sports mirror the game of life, and our kids can learn perseverance, accountability, hard work, humility, teamwork and much more from sports,” he said. “However, I would caution all parents to count the cost and the impact sports will have on their child’s spiritual development, the impact it will have on their marriage, finances, etc.”

View from the pews

Based on their perspective on missing services, many churchgoers see the potential impact differently than their pastors. Fewer than 1 in 5 U.S. Protestant churchgoers (18%) say it is never OK to skip church for kid’s sports. Around 3 in 4 (74%) believe it’s acceptable at least occasionally, including 22% who say once or twice a year, 39% a few times a year and 13% many times a year. Another 9% say they aren’t sure.

As with pastors, age is a factor for how likely a churchgoer is to see missing church for sports as OK. Those 50 and older are more likely than adults under 35 to say it’s never acceptable (20% v. 12%). Churchgoers 65 and older (7%) are the least likely to believe it’s OK to skip many times a year, while those under 35 (26%) are the most likely.

Additionally, churchgoers who attend more frequently are less accepting of skipping because of sporting events. Those who attend one to three times a month (45%) are more likely than those who attend four or more times (35%) to say missing a few times a year is OK. Meanwhile, those less frequent attenders (12%) are less likely than those who attend more often (22%) to say it’s never acceptable to miss because of a child’s game.

For churchgoers who do decide to miss because of sports, Bryant encourages the whole family to capitalize on the opportunity. “Perhaps you will be able to share the gospel with someone on the team, or another parent, who would otherwise never attend a worship service,” he said. “But those gospel engagements won’t happen accidentally, so you’ll have to be proactive and intentional.”

RELATED: Churchgoers Still Watch Livestream Services, at Least Occasionally

When he’s coaching sports, Frankie Creel says this is his mindset. Creel, an elder at CrossLife Church in Spartanburg, South Carolina, coaches high school sports and used to coach a travel softball team. His daughter is still part of a travel team. “If I am coaching, I use it as an opportunity to talk to the ladies about their identity in Christ and use it as a time of study and discipleship,” he said.

They try to avoid Sunday games but there are occasional major tournaments that lead to them missing four to five Sundays during the summer. “As long as it is not an absurd amount of time, I am OK,” he said.

Creel encouraged parents to ask themselves why they want to be involved in sports before committing. He said for younger players, he would avoid travel as much as possible. Camps and one-day tournaments can help those athletes continue to develop. Once the child reaches 10th grade and wants to play beyond high school, he said those larger tournaments become more necessary.

For Creel, churches can serve parents of travel sports athletes by creating “resources that encourage parents to have Christ-centered conversations with their kids, whether its online sermons, books or just tools to help disciple the child.”

Bryant says they are working to equip and encourage parents at the Church at Avenue South, and they’ve seen some results. “Some parents are now embracing more than ever that all 168 hours in a week are important for reinforcing biblical truths, not just taking their children to church for one hour of corporate worship on Sundays,” he said. “Some are repurposing the time they have with their children, whether in the car during the trip or around the team hotel to invest the gospel in their children.”

Lifeway Research studies can be used and referenced in news articles freely. This news release can also be republished in its entirety on other websites and in other publications without obtaining permission.

Aaron Earls

@WardrobeDoor

Aaron is the senior writer at Lifeway Research.

For more information, view the pastors’ report and the churchgoers’ report .

Methodology

The phone survey of 1,004 Protestant pastors was conducted Aug. 29, 2023 – Sept. 20, 2023. The calling list was a stratified random sample, drawn from a list of all Protestant churches. Quotas were used for church size. Each interview was conducted with the senior pastor, minister or priest at the church. Responses were weighted by region and church size to reflect the population more accurately. The completed sample is 1,004 surveys. The sample provides 95% confidence that the sampling error does not exceed plus or minus 3.2%. This margin of error accounts for the effect of weighting. Margins of error are higher in sub-groups.

The online survey of 1,008 American Protestant churchgoers was conducted Sept. 19-29, 2023, using a national pre-recruited panel. Respondents were screened to include those who identified as Protestant/non-denominational and attend religious services at least once a month. Quotas and slight weights were used to balance gender, age, region, ethnicity, education and religion to reflect the population more accurately. The completed sample is 1,008 surveys. The sample provides 95% confidence that the sampling error from the panel does not exceed plus or minus 3.2%. This margin of error accounts for the effect of weighting. Margins of error are higher in sub-groups.

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• J Appl Behav Anal
• v.44(4); Winter 2011

REVIEW OF SPORTS PERFORMANCE RESEARCH WITH YOUTH, COLLEGIATE, AND ELITE ATHLETES

This brief review summarizes translational and intervention research in the area of sports performance. We describe studies with youth, collegiate, and elite athletes; identify recent trends; and propose recommendations for future research.

Behavior analysts have studied sports performance for over three decades ( Martin & Tkachuk, 2000 ), including applications with youth, collegiate, and elite athletes participating in baseball ( Osborne, Rudrud, & Zezoney, 1990 ), basketball ( Kladopoulos & McComas, 2001 ), figure skating ( Ming & Martin, 1996 ), football ( Ward & Carnes, 2002 ), ice hockey ( Rogerson & Hrycaiko, 2002 ), soccer ( Brobst & Ward, 2002 ), swimming ( Hume & Crossman, 1992 ), and tennis ( Allison & Ayllon, 1980 ). This research has focused primarily on interventions that were implemented directly with performers and through consultation with coaches and trainers. Interest in behavioral sport psychology has grown ( Luiselli & Reed, 2011 ; Martin, 2011 ), producing refined methods and an expanded research focus. Behavior analysts continue to examine the merits of applying basic learning principles to evaluate and predict competitive sports outcomes. Our purpose in this review is to highlight (a) the types of sports performance research published in the Journal of Applied Behavior Analysis during the past 5 years, (b) the implications of these research findings for sports performance professionals, and (c) the increase in translational approaches to the athletic arena.

Recent intervention studies designed to enhance athletic performance have targeted previously researched sports (e.g., football) as well as relatively new ones such as rugby and gymnastics. In research with high school football players, Stokes, Luiselli, and Reed (2010) developed a 10-step task analysis of tackling skills based on recommendations by the American Football Coaches Association (1995) . During practice sessions, coach- and teammate-delivered positive reinforcement (praise and helmet stickers) increased correct execution of tackling skills by two linebackers. Similarly, Stokes, Luiselli, Reed, and Fleming (2010) increased offensive line blocking proficiency of high school football athletes when the coach implemented descriptive feedback (praise and correction) combined with video feedback (viewing practice videotapes) and performance feedback provided by an audible stimulus (teaching with acoustical guidance [TAG]; Pryor, 1999 ). Both studies by Stokes and colleagues found that the skills practiced and acquired during intervention were displayed successfully in games.

Also studying football, Smith and Ward (2006) reported that three intervention procedures improved wide receiver skills (blocks, routes, releases) of collegiate players: (a) public posting plus verbal feedback: display of a daily performance chart with praise and error correction from the coach; (b) goal setting plus verbal feedback: players set a minimum of 90% correct performance criterion before practice with praise and error correction from the coach; and (c) public posting plus verbal feedback plus goal setting: reintroduction of the daily performance chart with the two previous intervention procedures. Notably, the coaches and players rated public posting plus verbal feedback plus goal setting as the most preferred combination. In a related example, Mellalieu, Hanton, and O'Brien (2006) found that goal setting in the form of a three-stage intervention enhanced multiple skills of college rugby players over an entire competitive season. Each player selected a performance improvement objective, scored performance according to a goal-attainment scaling formula, and reviewed performance outcomes with the researchers 48 hr before each match.

Finally, Boyer, Miltenberger, Batsche, and Fogel (2009) instructed young, competitive female gymnasts to watch video modeling of an expert gymnast perform skills, followed by their own performance of the same skills, concluding with freeze-framed and side-by-side video clips of both performers at five different points. The video modeling by experts with corresponding feedback improved skill performance more quickly than regular practice and coaching alone.

In both earlier and more recent intervention studies, coaches were integrally involved in defining target behaviors, collecting data, and implementing procedures. Specific coaching behaviors addressed proper technique to prevent potential injuries and preparing athletes for successful game play and individual competitions. Regarding social validation, coaches and athletes rated the methods employed in these studies favorably ( Stokes, Luiselli, Reed, et al., 2010 ; Mellalieu et al., 2006 ). Going forward, behavior analysts who concentrate on sports performance research should continue to assess strategies for assessing and promoting generalization. For example, does intervention for some athletic skills produce similar effects on nontargeted skills? Also, it is critically important that skills acquired during practice are displayed fluently during competition ( Martin, Vause, & Schwartzman, 2005 ). Concerning maintenance, the skills learned through intervention may diminish over time ( Stokes, Luiselli, Reed, et al., 2010 ), indicating the need for follow-up or booster training.

In translational approaches to behavioral research, behavior analysts are interested in demonstrating the generalizability of nonhuman studies on basic behavioral processes to everyday human events (see Mace & Critchfield, 2010 ). This has been the case with recent sports performance research, due to the clear quantification of responses and reinforcers (e.g., two- and three-point shot attempts and points made in basketball) and the wide availability of such data on sports Web sites (see Reed, 2011 ). In a seminal example of the applicability of behavioral processes to sports performance, Vollmer and Bourret (2000) demonstrated that the matching law (i.e., relative rates of behavior match relative rates of reinforcement) could explain and predict college basketball players' field goal shot selections. Subsequently, Romanowich, Bourret, and Vollmer (2007) replicated these findings in professional basketball. In a recent extension of these findings, Alferink, Critchfield, Hitt, and Higgins (2009) demonstrated that basketball players' degree of conformance to the matching law varied as a function of skill or ability.

In a similar series of analyses, Reed, Critchfield, and Martens (2006) suggested that offensive play selection (passing and rushing) across various levels (e.g., college, professional, etc.) of American-rules football could be explained and accurately predicted via the matching law. In these analyses, Reed and colleagues found that play-calling patterns varied systematically as a function of down (i.e., there was a relative bias for passing on third down) and turnover risk (i.e., there was a relative bias for passing as fumble risks increased). In a subsequent study, Stilling and Critchfield (2010) more thoroughly examined the role of situation-specific variables on offensive play calling in football, demonstrating that the matching law provides both an accurate and operant explanation of play-calling strategies across situation-specific variables (e.g., time left in the half, yards needed for a first down, distance from the goal line, score, and down).

Beyond the matching law, sports performance has served as a translational conduit to understanding the role of behavioral momentum in natural settings (see Roane, 2011 ). For example, Mace, Lalli, Shea, and Nevin (1992) and Roane, Kelley, Trosclair, and Hauer (2004) demonstrated that college basketball teams' resistance to adversity increased as a function of relatively higher reinforcement rates. These researchers also documented that a strategic use of time-outs could disrupt opponents' rates of reinforcement, providing an applied example of how the principles of behavioral momentum could be adapted to improve coaching success. Such translational studies of sports are important to understanding the operant relations associated with game play and performance, but also speak to the explanatory flexibility of behavioral models to describe and predict behavior–reinforcement relations in both laboratory and natural environments.

The studies we reviewed illustrate the current status of sports performance research in applied behavior analysis. As for intervention, positive reinforcement, goal setting, modeling, and graphic feedback have been effective with athletes of all ages, at different skill levels, and in many sports. Other methods, like TAG, appear to be promising but require further evaluation. The tone set by prior research in assessing the acceptability of and satisfaction with sports performance intervention objectives and procedures also should be emphasized. We suggest further that applied behavior-analytic research should compare different intervention procedures, targeting both early skill development in youth athletes and refinement of skills among proficient performers. Although the small body of translational research has concentrated primarily on quantitative analyses of collegiate and elite basketball and football players, there are certainly extensions possible to other sports, as well as further development of quantitative models derived from behavioral momentum and the matching law ( Reed, 2011 ). On a practical level, this line of research should alert athletes and coaches to the benefits of analyzing statistics that are tied directly to performance, decision making (e.g., situational play calling), and competition strategy. Finally, following a functional analysis that manipulated coach and peer social consequences during attention and escape conditions, Stokes and Luiselli (2010) implemented a delayed, written performance feedback intervention that improved tackling skills of a high school football player. Functional analysis methodology, in fact, may be valuable in formulating athlete-specific intervention and training plans that can be adopted by coaches for a variety of individual and team sports.

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