Team Performance Indicators Explain Outcome during Women's Basketball Matches at the Olympic Games

Quantifying the Effects of Detraining on Female Basketball Players Using Physical Fitness Assessment Sensors

This study leverages physical fitness assessment sensors to investigate the effects of a brief in-season break (detraining period) on the physical performance of female basketball players. Sixty-seven players (Senior (n = 19), U18 (n = 19), and U14 (n = 29)) were evaluated before and after a 3-week break using sensor-derived data from a countermovement jump (CMJ), an Abalakov jump (ABK), a linear speed test (20 m sprint), a seated medicine ball throw test (SMBT), and a Basketball-Specific Agility Test (TEA-Basket). The Total Score of Athleticism (TSA), computed as the mean Z-Score across tests, served as a composite indicator of physical fitness. Data obtained from performance sensors revealed significant interactions between time and category for the CMJ, ABK, 20 m sprint, and SMBT, while TEA-Basket measurements showed no significant changes. Time and baseline fitness level interactions were also significant for the CMJ, ABK, and SMBT but not for sprint time or the TEA-Basket. Despite observed declines in explosive strength, speed, and upper-body power across all groups, TSA scores remained stable. These findings underscore the utility of sensor-based evaluation methods in highlighting the adverse effects of short-term detraining and emphasize the necessity of tailored training strategies during competitive breaks.

Female basketball game performance is influenced by menstrual cycle phase, age, perceived demands and game-related contextual factors

This study evaluated the influence of physical and perceived game demands, menstrual cycle phase, perceived recovery, individual and game-related contextual factors on competitive performance in professional, female basketball players.11 professional female players (age: 20.6 ± 2.7 years) were monitored for game-related statistics (Performance Index Rating, PIR; rebounds, REB; effective field goal %, eFG%; turnovers, TO), objective (PlayerLoad per minute, PL·min-1) and subjective (RPE) game loads, pre-game perceived recovery (Total Quality Recovery, TQRpre), menstrual phase (follicular; luteal) and game-related contextual factors (game location; game outcome; score differential; opponent level) during 12 official games. Separate linear mixed models were used to evaluate the influence of RPE, PL·min-1, TQRpre, menstrual phase, contextual factors, and individual characteristics (age; playing position) on game-related statistics.Higher PIR and eFG% were found for older players and those who reported higher RPE (all p < 0.05). Higher age also led to less TO (p = 0.042). eFG% was higher when players reported higher TQRpre ;(p = 0.010). Better shooting (eFG%) and rebounding (REB) performances were found during the follicular menstrual phase (p < 0.05). More REB were collected in won games (p = 0.002).This study suggests that the co-influences of perceptual, menstrual-related, individual and game-related contextual factors should be considered to optimise female basketball players' performance.

Game-related statistics for distinguishing winning and losing teams in Olympic basketball: The impact of game pace

The pace of play, a critical tactical element in basketball, significantly influences offensive and defensive strategies. This study aimed to identify statistical indicators that differentiate winners from losers across varying game paces using a sample of 90 Olympic men's basketball games from 2016, 2021, and 2024. Games were categorized as fast-paced or slow-paced via clustering algorithms. Stepwise Discriminant Analysis (SDA) identified key performance metrics, while an Exhaustive CHAID decision tree (E-CHAID) simulated outcomes based on game statistics. In fast-paced games, defensive rebounds (SC = 0.403), three-point field goals made (SC = 0.329), and free throws made (SC = 0.305) were crucial for distinguishing winners. In contrast, slow-paced games highlighted the importance of defensive rebounds (SC = 0.513), pick-and-roll ball-handler field goals missed (SC = -0.388), and cut field goals made (SC = 0.325). The decision tree further emphasized the significance of off-screen field goals made and steals as pivotal metrics. These findings offer insights into how game pace shapes performance indicators, providing strategic guidance for optimizing team tactics. By linking game statistics with match outcomes, this study contributes to understanding developmental trends in competitive basketball and enhancing technical and tactical performance.

Relationship between Physical Demands and Player Performance in Professional Female Basketball Players Using Inertial Movement Units

Load monitoring has been identified as a valuable tool for optimizing training planning and minimizing injury risk. This study's aim was divided into two main objectives: (1) to describe the physical demands during official competition through IMU (inertial movement unit) metrics and (2) to investigate the relationship between basketball statistics and these physical demands. Twelve female highly trained basketballers (26.5 ± 5.3 years, 180 ± 7.1 cm, and 73.6 ± 10.3 kg) were monitored during four official games. Our results indicate that games with more frequent possession changes, particularly those driven by steals and turnovers, exhibit higher physical demands. Additionally, longer game durations were associated with longer recovery time while maintaining similar active time and physical load. Players who assume prominent shooting roles face greater conditional demands, such as increased jumps and impacts, even with equal playing time. These findings suggest that IMUs provide valuable insights into high-intensity actions and patterns, indicating a direct association between physical load and player performance in professional female basketball. This study also highlights the potential for professionals to better manage workload and understand player demands using these insights, even in the absence of in-game sensor data. Our research underscores the importance of contextual analysis in sports performance studies, encouraging future investigations into game phases and their specific physical demands.

Game schedule, travel demands and contextual factors influence key game-related statistics among the top European male basketball teams

This study examined the effects of game schedule, travel demands and contextual factors on team game-related statistics during a full season. The top 10 teams competing in the 2020-2021 Euroleague basketball season were included where game-related statistics from their respective national competitions and the Euroleague competition were retrieved (761 games). Hierarchical linear regression models were computed to evaluate the effects of distance travelled, game schedule and contextual factors for the previous and current games (league, season phase, opponent level, game outcome, score differential) on key performance indicators (points, shooting, rebounds, assists, turnovers, fouls). Several significant models (p < 0.05) yielded R2 values ranging from 0.05 to 0.22 with small-to-medium effect magnitudes. Analyses revealed significant associations between longer durations separating games and less free-throws being made and between further distances travelled and worse 3-point shooting, more offensive rebounds and more fouls. Regarding contextual factors, favourable outcomes for shooting, assists, steals, fouling and turnovers were significantly associated with team success. Playing higher-level teams and competing in playoffs or finals was associated with several diminished outcomes. These results emphasize the multi-factorial nature of performance in elite European basketball, with game schedule, travel and various contextual factors requiring consideration in developing holistic operational plans for teams.

Differentiating attack-defense performance for starting and bench players during the Tokyo Olympics men's basketball competition

This study aimed to explore the differences in attack-defense performance between the top and bottom teams for starting and bench players during the Tokyo Olympics men's basketball competition, to determine the relationship between the attack-defense performance of starting and bench players and the final competition rankings, as well as with each performance indicator. The rank-sum ratio (RSR) comprehensive evaluation was employed to describe the attack-defense performance of starting and bench players. Additionally, an independent sample t-test, Spearman Rho Correlation, and Pearson Correlation were conducted to test the differences and relationships between the various variables at a 0.05 level of significance, respectively. The results indicated that the top four teams showed significant differences in the attack-defense performance of their starting players compared to the bottom four teams (p = 0.021), mainly in terms of 3-point shooting percentage (p = 0.042) and free throw shooting percentage (p = 0.044). Besides that, the attack-defense ranks of both starting players (p = 0.004, r = 0.757) and bench players (p = 0.020, r = 0.658) had a significant correlation with the final rankings. Points per game, 2-point field goal percentage, and assists had a statistically significant (p<0.01) and strong positive correlation (0.70 Collapse

Key Words Collapse

MESH Headings

• Male
• Humans
• Basketball
• Tokyo
• Athletic Performance

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Grants Collapse

Affiliation(s)

Wenping Sun Department of Sport Studies, Faculty of Educational Studies, Universiti Putra Malaysia, Kuala Lumpur, Malaysia
ChenSoon Chee Department of Sport Studies, Faculty of Educational Studies, Universiti Putra Malaysia, Kuala Lumpur, Malaysia
LianYee Kok Department of Sport Science, Faculty of Applied Sciences, Tunku Abdul Rahman University of Management and Technology, Kuala Lumpur, Malaysia
FongPeng Lim Department of Mathematics and Statistics, Faculty of Science, Universiti Putra Malaysia, Kuala Lumpur, Malaysia
Shamsulariffin Samsudin Department of Sport Studies, Faculty of Educational Studies, Universiti Putra Malaysia, Kuala Lumpur, Malaysia

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A Systematic Review on the Physical, Physiological, Perceptual, and Technical-Tactical Demands of Official 3 × 3 Basketball Games

PURPOSE

To systematically review the physical, physiological, perceptual, and technical-tactical demands of official 3 × 3 basketball games.

METHODS

The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed. Three electronic databases (PubMed, Scopus, and Web of Science) were systematically searched to identify studies assessing physical, physiological, perceptual, and technical-tactical demands of 3 × 3 games. Data were also coded according to player sex and tournament phase. Quality assessment of the included studies was performed using a modified Downs and Black checklist.

RESULTS

Thirteen articles were finally included, with a mean quality of 8.6 (1.1) out of 11. Three-by-three basketball games have an intermittent profile (1:1 work-rest ratio), with a duration of ∼15 minutes, and are characterized by short (6-8 s) ball possessions and considerable physical (17-33 accelerations, 24-44 decelerations, 62-94 changes of directions, and 17-24 jumps per game) and physiological (lactate: ∼6.2 mmol·L-1) demands. Overall, the game performance profile is similar in males and females, with minor changes happening across tournament phases. Several key technical-tactical indicators were identified as discriminating winning and losing teams, such as better shooting and defensive efficiency, low number of turnovers, and implementing tactical actions involving more players, passing first, and ending possessions with shots from outside of the arch from the top of the key.

CONCLUSIONS

Three-by-three basketball is an intermittent, physically demanding sport characterized by quick plays and specific tactical constraints. This review provides information that should be considered by performance staff to improve training prescription, game tactical plans, and for player selection and talent identification.

Physical Fitness as a Predictor of Performance during Competition in Professional Women's Basketball Players

The evaluation of physical fitness in team sports is enjoying greater importance in the training of professional teams. The objectives of this research were to characterize physical fitness and game indicators based on the game position. This is an empirical study, with a quantitative, descriptive and cross-sectional methodology. In addition, different relationships between the level of physical fitness and the game indicators during the competition were determined. Finally, a predictive analysis of the selected variables was carried out in order to know the importance of the variables in the performance and at what time of the season they had the greatest impact. For this, a professional female basketball team (n = 12) with a mean age of 25.25 ± 7.617 years, height 178.25 ± 9.206 cm and a body mass of 72.33 ± 11.657 kg was analyzed. Each player was equipped with a WIMUPRO inertial device, and all competition statistics were analyzed. The results obtained show that there were no differences among all the skills evaluated and game indicators depending on the game position. Likewise, a relationship was determined between the level of physical fitness and the technical-tactical contribution, being different between different times of the season. Moreover, physical fitness only predicted the player's final performance in the competition for female player centers in the first and second rounds of the championship, and for forwards in the first round. Four physical-physiological profiles with contributions to the different ones during the competition were also determined. Finally, three groups of female players by playing position were identified according to their sport performance, namely PIR, high, medium and low ratings, associated with physical performances. In all groups, there were significant differences between playing positions, PIR and physical performances.

Evaluation of differences in the performance strategies of top and bottom basketball teams utilizing rank-sum ratio comprehensive

Introduction

This study aimed to explore common characteristics among top basketball teams, differentiate attacking and defensive performance between top and bottom teams, and correlate attacking and defensive performance with final competition rankings during the 2019 Men's Basketball World Cup, as well as to determine the relationship between performance indicators and the attacking and defensive performance. In addition, the study aimed to determine the attacking and defensive level of the top and bottom eight teams and find their existing problems and shortcomings, to further improve their competitive basketball strength, and also provided valid and reliable information for coaches to conduct targeted training in the future.

Methods

The rank-sum ratio (RSR) was employed to evaluate the attack, defense, and overall attacking and defensive performance between the top and bottom teams during the 2019 Men's Basketball World Cup. Additionally, an independent sample T-test was conducted to test the difference in performance indicators of attack and defense between the top eight and bottom eight teams. Spearman Rho Correlation was conducted to determine the relationship between the attacking and defensive RSR value and the final competition ranking at the 0.05 confidence level. Pearson Correlation was employed to test the relationship between the performance indicators and the attacking and defensive RSR value at the 0.05 confidence level. According to Spearman and Pearson Correlation, the indicators which contributed most to the attacking and defensive performance, as well as the correlation between attack and defense and the final ranking, can thus be determined.

Results

The results showed that the attacking performance of the top eight teams was far better than the bottom eight teams in terms of average points (p = 0.000), 2-point shoot percentage (p = 0.001), 3-point shoot percentage (p = 0.003), free throw percentage (p = 0.001), turnovers (p = 0.012), and assists (p = 0.000), and there was a significant difference (p < 0.05). However, second attack (p = 0.484), fast-break (p = 0.174), and offensive rebounds (p = 0.261) showed no significant difference between the two cohorts (P > 0.05), and the offensive rebounds of the bottom eight teams were better than the top eight teams. Additionally, there was a large gap between the top eight teams and the bottom eight teams in lost points (p = 0.001) and defensive rebounds (p = 0.000), with a very significant difference (p < 0.01). However, steals (p = 0.760), blocks (p = 0.166), and fouls (p = 0.686) had no significant difference between the two cohorts (P > 0.05). Additionally, there was a very significant difference between attack RSR (p = 0.000), defense RSR (p = 0.006), and the overall attack-defense RSR (p = 0.000) of the top eight and bottom eight teams (p < 0.01), and most top teams focused on developing both attack and defense and paid attention to improve the overall attacking and defensive ability. Moreover, there was a significant relationship between the overall attack-defense performance and assists (p = 0.832), rebounds (p = 0.762), turnovers (p = 0.702), 2-point shoot percentage (p = 0.704), defensive rebounds (p = 0.809), fast-break points (p = 0.577), blocks (p = 0.600), and free throw percentage (p = 0.575).

Conclusions

This study showed that the top basketball teams focused on developing both attack and defense, and have the common characteristics of strong attack and defense. Whether it was the attack, defense, or overall attacking and defensive ability, there was a significant relationship with the final ranking. Additionally, this study showed that there were very significant differences in both attacking and defensive abilities between the top eight and bottom eight teams, as well as highlighted their respective advantages and disadvantages in attacking and defensive indicators. Besides that, this study found that performance indicators such as assists, defensive rebounds, 2P%, turnovers, FT%, fast-breaks, and blocks were the main factors that distinguish the top and bottom teams, and they had a significant relationship with overall attacking and defensive performance. The above information allows coaches and players to learn the latest developments in competitive basketball, as well as their advantages and disadvantages, to help them organize targeted training in the future.

Effect of Situational and Individual Factors on Training Load and Game Performance in Liga Femenina 2 Basketball Female Players

There is research that has shown how individual characteristics and performance indicators influence the load in basketball; however, studies on the influence of situational variables on performance are lacking. The aim of this study was to determine the influence of certain situational and individual variables on the training load (weekly load, game load and pre-game recovery) and the individual performance (statistical game evaluation) of female basketball players of Liga Femenina 2 during competition. The 28 games played by the 13 players of a group B team of the Liga Femenina 2 of the Spanish Basketball Federation (FEB) during the 2020/2021 season were analyzed. Data on rate of perceived exertion (RPE), perceived performance and recovery were collected through the Quanter mobile application as well as performance statistics from the FEB website. Five mixed linear analyses for repeated measures were performed to evaluate the effect of each situational and individual variable on each dependent variable (weekly load, game load, game RPE, pre-game recovery, and game statistical assessment). The results show how the weekly load increases after playing against a low-level opponent (p < 0.001). In games, the players who play the most minutes and accumulate the most load are also the most valued (p < 0.001). The pre-game recovery worsens as the season progresses (p < 0.001). After playing against a high-level opponent, the pre-game recovery values for the next game are lower (p = 0.031). The results obtained indicate that the situational and individual variables should be taken into account to monitor the workload. These results help coaches and physical trainers to better plan training weeks, taking into account the situational variables studied.

On-Court Activity and Game-Related Statistics during Scoring Streaks in Basketball: Applied Use of Accelerometers

The aim of this observational study was to determine if on-court activity and match statistics differed between periods of scoring streaks and regular play in basketball. Thirty-seven basketballers including professional women, semi-professional women and semi-professional men wore accelerometers during competitive matches throughout a season. Accelerometry-derived live-time individual on-court exercise intensity and team game-related statistics were compared between scoring streaks (periods of play where the teams participating in the study scored at least three times in a row), streaks against (periods of play where the opposition teams scored at least three times in a row) and regular play. Few differences existed in the average exercise intensity between streak types. During streaks against, there was a 5–15% lower proportion of 2-point attempts, 0.8–1.3 fewer defensive rebounds per minute and 0.3–1.6 fewer shot attempts per minute compared to regular play and scoring streaks, and there were 0.3 fewer offensive rebounds per minute compared to regular play. During scoring streaks, there were 0.5 more defensive rebounds per minute, 1.3 more shot attempts per minute, a 43% greater shooting percentage and a 10% lower proportion of 3-point attempts compared to regular play. To reduce the chances of streaks against, teams should focus on facilitating 2-point shot attempts and consider implementing a 3:1 ratio of 2-point to 3-point attempts to maximize scoring success, and they should focus on winning rebounds to facilitate more shot attempts.

Live Multiattribute Data Mining and Penalty Decision-Making in Basketball Games Based on the Apriori Algorithm

The Apriori algorithm is used to conduct an in-depth analysis and research on the relationship between data mining and penalty decision of multiattribute data in the basketball game scene. The technical and tactical features are analyzed using an improved Apriori algorithm for association rule analysis of basketball game data. The algorithm generates association rules based on mining the set of frequent items among basketball technical actions. The improved algorithm can mine the technical moves that are more connected in the game data, and the analysis results are highly instructive. The technical and tactical directed analysis is divided into two parts: technical and tactical directed action analysis and technical and tactical directed cooperation analysis. The key action analysis uses Markov process-based data mining algorithm to analyze the basketball game data for key score transfer steps and key score loss transfer steps. The algorithm can find the key actions of scoring and key actions of conceding points in the game process, and the analysis results can guide basketball training and games, which has high practical value. Using the collated game data as the independent variable and the number of games won and lost as the dependent variable, logistic regression analysis is applied to derive the characteristics that affect winning. Again, the decision tree algorithm is used to select the significant features that affect winning and to make predictions of team performance. Finally, the technical statistics of the main players in the last three seasons are selected, and the association rule algorithm is applied to derive the degree of influence of player performance on the outcome of the game.

The Differences in the Performance Profiles Between Native and Foreign Players in the Chinese Basketball Association

The aim of the study was to (i) use an clustering analysis method to classify and identify native and foreign basketball players into similar groups based on game-related statistics; (ii) use the Pearson's Chi-square test to identify the key clusters that affect whether a team enters the playoffs; and (iii) use the classification tree analysis to stimulate the prediction of team ability and the construction of the team roster. The sample consisted of 422 foreign players and 1,775 native players across 9 seasons from 2011 to 2019. The clustering process allowed for the identification of nine native and six foreign player performance profiles. In addition, two clusters (p < 0.001, ES = 0.33; p < 0.001, ES = 0.28) of native players and one cluster (p < 0.05, ES = 0.16) of foreign players were identified that had a significant impact on team ability. These results provide alternative references for basketball staff concerning the process of evaluating native and foreign player performance in the Chinese Basketball Association.

A Random Forest approach to identify metrics that best predict match outcome and player ranking in the esport Rocket League

Notational analysis is a popular tool for understanding what constitutes optimal performance in traditional sports. However, this approach has been seldom used in esports. The popular esport "Rocket League" is an ideal candidate for notational analysis due to the availability of an online repository containing data from millions of matches. The purpose of this study was to use Random Forest models to identify in-match metrics that predicted match outcome (performance indicators or "PIs") and/or in-game player rank (rank indicators or "RIs"). We evaluated match data from 21,588 Rocket League matches involving players from four different ranks. Upon identifying goal difference (GD) as a suitable outcome measure for Rocket League match performance, Random Forest models were used alongside accompanying variable importance methods to identify metrics that were PIs or RIs. We found shots taken, shots conceded, saves made, and time spent goalside of the ball to be the most important PIs, and time spent at supersonic speed, time spent on the ground, shots conceded and time spent goalside of the ball to be the most important RIs. This work is the first to use Random Forest learning algorithms to highlight the most critical PIs and RIs in a prominent esport.

Shot Distribution and Accuracy in Senior and Youth International Basketball Games: Changes over the Decade of the 2010s

This study aimed to investigate the changes in shot distribution and accuracy in senior and under-17 international basketball tournaments in the 2010s. A retrospective cross-sectional design was employed, and a total of 1055 games from 20 world-level tournaments held between 2010 and 2019 were analyzed. The tournaments held in 2010 were played under the old three-point line (6.25 m), and the rest of the tournaments were played under the new three-point line (6.75 m). The numbers of two- and three-point shot attempts in each game were normalized to 100 possessions. Differences in mean values of two- and three-point shot attempts were analyzed by a two-way (category × year) between-subjects analysis of variance (ANOVA). Differences in the success rates of two- and three-point shots were analyzed by Fisher’s exact test. There was no significant category × year interaction for two-point shot attempts. However, there were significant main effects of category and year for two-point shot attempts. The number of two-point shot attempts increased significantly in 2012 and, in 2016, returned to a level not significantly different from that in 2010, independent of categories. There was a significant category × year interaction for three-point shot attempts. The number of three-point shot attempts decreased significantly in 2012 and, by 2016, returned to a level not significantly different from that in 2010 in senior men and under-17 women. There was no significant change in the number of three-point shot attempts in under-17 men. The effect of the extension of the three-point line on shot accuracy was limited. Differences in shot accuracy were prominent between age categories: the accuracy was lower in under-17 games than in senior games for both sexes. Although under-17 men attempted fewer three-point shots than senior men, under-17 women attempted a similar number of or more three-point shots than senior women. These findings can contribute to a better understanding of age and sex differences in recent trends in international basketball.

Relative Age Effects in Basketball: Exploring the Selection into and Successful Transition Out of a National Talent Pathway

Relative age effects (RAEs) appear consistently prevalent throughout the youth basketball literature. However, the selection into and successful transition out of a national talent pathway in basketball is yet to be explored. Thus, the primary aim of this study was to explore the influence of relative age, gender, and playing time based on the selection into the Regional Talent Hubs and Basketball England youth teams (U16, U18, and U20) and the successful transition into the England National Senior Teams. Participants who were selected into the male (n = 450) and female (n = 314) Basketball England Talent Pathway were allocated into one of three cohorts: (a) Regional Talent Hubs (U12 to U15; n = 183), (b) England National Youth Teams (U16, U18, and U20; n = 537), and (c) England National Senior Teams (n = 44). A chi-square test was used to compare the birth quarter (BQ) distributions of each cohort against the expected distributions, with a Cramer’s V (Vc) used to interpret effect sizes. Odds ratios (OR) and 95% confidence intervals were also calculated to compare the likelihood of each BQ being represented. Males revealed significant RAEs across both the Regional Talent Hubs (p < 0.001, Vc > 0.29, OR = 10) and England National Youth Teams (p < 0.001, Vc > 0.17, OR = 3.1). In comparison, females only had significant RAEs in the Regional Talent Hubs (p < 0.001, Vc > 0.29, OR = 2.3). Despite RAEs being prevalent throughout youth levels, there were no significant differences in the BQ distribution based on playing time and those who made the successful transition to the England National Senior Teams. These findings demonstrate the potential mechanisms of RAEs in basketball, as well as the impetus to explore more equitable competition structures within the England Basketball Talent Pathway.

Modeling the Keys to Team's Success in the Women's Chinese Basketball Association

The technical characteristics of women’s basketball may differ from men’s basketball, and there is a need to identify the key performance indicators (KPIs) that contribute to the success of women’s teams. The aim of the current study was to examine and quantify the relationships between technical performance indicators and match outcome in elite women’s basketball using both linear and non-linear statistical methods, the effectiveness of the two methods was compared as well. A total of 136 matches (n = 272 teams’ observations) in the regular season of Women’s Chinese Basketball Association (WCBA; season 2020–2021) were analyzed using multiple linear regression (MLR) and quantile regression (QR). Results showed that two-point percentage, offensive rebounds, assists and turnovers had significant effects on the match outcome for both MLR and QR analysis. No significant relationships were observed between match outcome and three-point percentage, steals, and fouls. The results between MLR and QR analysis were different in free-throw percentage, defensive rebounds and blocks. Current results highlighted QR analysis is an advanced statistical model more powerful than the traditional linear method for the identification of KPIs. The identified KPIs may help coaches to develop more specific training interventions and match strategies during match play.

Explaining Positional Differences of Performance Profiles for the Elite Female Basketball Players

The aim of the present study was to explore the differences in technical performances of players considering playing positions by controlling the effect of situational variables in each FIBA female continental basketball competition. Samples of 9,208 observations from 471 games in the America, Africa, Asia, and Europe Championships during 2013-2017 were collected and analyzed by generalized mixed linear modeling. The results showed that Centers from Europe had more 2-point made (ES = 0.69), 2-point attempted (ES = 0.79), and offensive (ES = 0.64) and defensive (ES = 0.48) rebounds than forward. Asian and European guards performed a fewer number of 2-point made (ES = 0.90; 0.91), 2-point attempted (ES = 1.06; 0.98), and offensive (ES = 1.30; 1.23) and defensive (ES = 0.93; 0.94) rebounds than Asian and European centers. African and Asian forward had more 2-point made (ES = 0.48; 0.50), 2-point attempted (ES = 0.50; 0.56) than guards. This study helps to better understand the technical demands of female basketball among different international competitions, which could pave a new way to analyze the development trend of female basketball and promoting specific training plans and game strategies for coaches and players.

Impact of the Relative Age Effect on Competition Performance in Basketball: A Qualitative Systematic Review

Performance in basketball is multifactorial. One of the modifying factors is the "Relative Age Effect-RAE". However, its impact depends on the sample characteristics and sport context. The purpose of this study was to examine the influence of the RAE on basketball competition performance by analysing peer-reviewed articles published until July 2020. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses systematic search guidelines, nine studies were identified in four databases: Sport Discus, PubMed, Web of Science, and Scopus. Moreover, a study quality analysis using "Strengthening the Reporting of Observational Studies in Epidemiology" guidelines was carried out. The results confirmed an impact of the RAE on competition performance in basketball (56% measurements) and a higher influence of the RAE on short-term collective performance (54% measurements). Statistical parameters were affected, especially in men and U14-U18 categories. No impact of the RAE reversal and no influence of the RAE on long-term collective performance were found. There was a higher impact of the RAE in men (71%), the U14-U18 categories (44%), and at the national level (40%) was identified. The RAE has a variable influence on basketball performance according to developmental constraints. Nevertheless, the findings should be considered based on the sport context due to the heterogeneity and variability of the identified results.

The Regional Differences in Game-Play Styles Considering Playing Position in the FIBA Female Continental Basketball Competitions

The aim of this study was to identify regional differences based on playing position in terms of the technical performances among FIBA Female Continental Basketball Championships by controlling the influence of situational variables including the game outcome, game type, teams and opponent quality. The samples comprised of 9208 performance records from 471 games in the America, Africa, Asia and Europe Championships during 2013-2017 and were collected and analyzed by generalized mixed linear modeling. Our study highlighted that, although positional differences were clear among different continental championships, it is worth noting that African guards, forwards, and centers made more turnovers (TOV) compared with the corresponding positional players from other continental championships. In addition, European guards presented the lowest number of steals (STL) compared with African (ES = 0.28), Asian (ES = 0.21), and American guards (ES = 0.24). The results provide coaches to have a better understanding of game-play styles among FIBA Female Continental Basketball Competitions, which could optimize the development of female basketball and the selection and recruitment of female players at the international level.

Modelling the Relationship between Match Outcome and Match Performances during the 2019 FIBA Basketball World Cup: A Quantile Regression Analysis

The FIBA Basketball World Cup is one of the most prominent sporting competitions for men’s basketball, with coaches interested in key performance indicators (KPIs) that give a better understanding of basketball competitions. The aims of the study were to (1) examine the relationship between match KPIs and outcome in elite men’s basketball; and (2) identify the most suitable analysis (multiple linear regression (MLR) vs. quantile regression (QR)) to model this relationship during the men’s basketball tournament. A total of 184 performance records from 92 games were selected and analyzed via MLR and QR, using 10th, 25th, 50th, 75th and 90th quantiles. Several offensive (Paint Score, Mid-Range Score, Three-Point Score, Offensive Rebounds and Turnovers) and defensive (Defensive Rebounds, Steals and Personal Fouls) KPIs were associated with match outcome. The QR model identified additional KPIs that influenced match outcome than the MLR model, with these being Mid-Range Score at the 10th quantile and Offensive Rebounds at the 90th quantile. In terms of contextual variables, the quality of opponent had no impact on match outcome across the entire range of quantiles. Our results highlight QR modelling as a potentially superior tool for performance analysts and coaches to design and monitor technical–tactical plans during match-play. Our study has identified the KPIs contributing to match success at the 2019 FIBA Basketball World Cup with QR modelling assisting with a more detailed performance analysis, to support coaches with the optimization of training and match-play styles.

Game Related Statistics Discriminate National and Foreign Players According to Playing Position and Team Ability in the Women's Basketball EuroLeague

The aim of the present study was to examine the differences in game-related statistics between national and foreign female basketball players in the Women’s EuroLeague, according to playing positions and team ability. The official box-scores of 112 games from the 2016–2017 season of the Women’s EuroLeague (FIBA) were examined. Players were categorised based upon country of nationality versus competition (i.e., foreign or national), playing positions (i.e., Guards, Forwards, Centers), and team ability (i.e., four groups using a cluster of k-means analysis according to the winning percentage of each team during the competition). A structural coefficient (SC) above |0.30| was used to identify the variables that best differentiated the national and foreign players. Results showed that foreign players had a better performance according to team ability and playing position for most of the performance indicators, with higher values for minutes played, percentage of successful 2-point field-goals, percentage of successful free-throws, and percentage of assists. Moreover, foreign players performed better in variables associated with offensive situations, while national players were prevailing with indicators associated with defensive actions. These results have highlighted the unique contributions of foreign and national players, based upon playing position and team ability, to team success in the Euroleague. This information will assist the recruitment process of national and foreign athletes for coaches to develop successful elite female basketball teams.

Current Approaches to the Use of Artificial Intelligence for Injury Risk Assessment and Performance Prediction in Team Sports: a Systematic Review

Background

The application of artificial intelligence (AI) opens an interesting perspective for predicting injury risk and performance in team sports. A better understanding of the techniques of AI employed and of the sports that are using AI is clearly warranted. The purpose of this study is to identify which AI approaches have been applied to investigate sport performance and injury risk and to find out which AI techniques each sport has been using.

Methods

Systematic searches through the PubMed, Scopus, and Web of Science online databases were conducted for articles reporting AI techniques or methods applied to team sports athletes.

Results

Fifty-eight studies were included in the review with 11 AI techniques or methods being applied in 12 team sports. Pooled sample consisted of 6456 participants (97% male, 25 ± 8 years old; 3% female, 21 ± 10 years old) with 76% of them being professional athletes. The AI techniques or methods most frequently used were artificial neural networks, decision tree classifier, support vector machine, and Markov process with good performance metrics for all of them. Soccer, basketball, handball, and volleyball were the team sports with more applications of AI.

Conclusions

The results of this review suggest a prevalent application of AI methods in team sports based on the number of published studies. The current state of development in the area proposes a promising future with regard to AI use in team sports. Further evaluation research based on prospective methods is warranted to establish the predictive performance of specific AI techniques and methods.

Electronic supplementary material

The online version of this article (10.1186/s40798-019-0202-3) contains supplementary material, which is available to authorized users.

Basketball Game-Related Statistics that Discriminate among Continental Championships for Under-18 Women

The purposes of this study were (a) to evaluate differences in basketball game-related statistics among continental championships for under-18 (U18) women, and (b) to identify game-related statistics that discriminate among the continents. The analysis was performed on all matches (n = 136) in the four continental championships (Africa, America, Asia, Europe) of 2016. Differences in game-related statistics among the continents were analyzed by an analysis of variance (ANOVA) with effect size statistics. Game-related statistics that discriminate among the continents were assessed by discriminant analysis. The ANOVA yielded significant F-values for 13 of 16 variables and large effect size differences for 10 of 16 variables. The discriminant analysis yielded three significant functions. The Asian championship was discriminated from the other continental championships by ball possessions, defensive rebounds, assists, and fouls. The African championship was discriminated from the European championship by ball possessions, successful 3-point field goals, unsuccessful free throws, and turnovers, and from the American championship by ball possessions, unsuccessful 2-point field goals, successful 3-point field goals, successful free throws, and assists. The results of this study suggest that U18 women's basketball games are played differently in each continent.

Regional Differences in Women's Basketball: A Comparison among Continental Championships

The aims of this study were (i) to compare basketball game-related statistics in women by region (Africa, America, Asia, Europe), and (ii) to identify characteristics that discriminate performances for each region. A total of 134 games from each continental championship held in 2017 were analyzed. A one-way ANOVA followed by a Bonferroni-adjusted pairwise comparison was performed to evaluate differences in each variable between the continents. A discriminant analysis was performed to identify game-related statistics that discriminate among the continents. The Asian and European championships overall showed similar performance profiles: Low numbers of possessions and turnovers, and high numbers of successful field goals and assists. However, the European championship was more closely contested than the Asian championship. The African championship was characterized by high numbers of possessions, free throws, and turnovers. The homogeneity of the American championship was low, and some of the cases have similarities with the African championship, whereas other cases have similarities with the European championship. On average, the American championship was characterized by low numbers of successful field goals and assists, and high numbers of steals and turnovers. It is suggested that women's basketball games are played in a different manner in each region of the world.

Scoring Strategies Differentiating between Winning and Losing Teams during FIBA EuroBasket Women 2017

This study aimed to examine the scoring strategies differentiating between winning and losing teams during FIBA EuroBasket Women 2017 in relation to different game scores. Data were gathered for all games of FIBA EuroBasket Women 2017 from the official website. The investigated scoring strategies were fast break points (FBP); points in the paint (PP); points from turnover (PT); second chance points (SCP); and points from the bench (PB). Games were classified with cluster analysis based on their score difference as close, balanced, and unbalanced and the differences in the scoring strategies between winning and losing teams were assessed using magnitude-based statistics. Results revealed no substantial differences in FBP in any investigated cluster. Furthermore, winning teams showed a substantially higher number of PP and PT (in close and unbalanced games) and SCP (in balanced and unbalanced games) compared to losing teams. Finally, winning teams scored substantially lower and higher number of BPs in close games and unbalanced games, respectively, compared to losing teams. In conclusion, all the investigated scoring strategies discriminate between winning and losing teams in elite women’s basketball except for FBP. These results provide useful information for basketball coaches to optimize their training sessions and game strategies.