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.

Entropy of Badminton Strike Positions

The aim of the current study was twofold: (i) to investigate the distribution of the strike positions of badminton players while quantifying the corresponding standard entropy and using an alternative metric (spatial entropy) related to winning and losing points and random positions; and (ii) to evaluate the standard entropy of the receiving positions. With the datasets of 259 badminton matches, we focused on the positions of players’ strokes and the outcome of each point. First, we identified those regions of the court from which hits were most likely to be struck. Second, we computed the standard entropy of stroke positions, and then the spatial entropy, which also considers the order and clustering of the hitting locations in a two-dimensional Euclidean space. Both entropy quantifiers revealed high uncertainty in the striking position; however, specific court locations (i.e., the four corners) are preferred over the rest. When the outcome of each point was taken into account, we observed that the hitting patterns with lower entropy were associated with higher probabilities of winning points. On the contrary, players striking from more random positions were more prone to losing the points.

Influence of Match Congestion on Performances in the National Basketball Association

The ability to recover from official match-play across a single and multiple matches is often considered a key factor in subsequent performance for modern professional basketball. The aims of this study were to: (i) explore the differences in match performances between different match congestion cycles (i.e., matches separated by zero, one, or two or greater days of rest); and (ii) identify the key performance indicators (KPIs) discriminating between winning and losing during different match congestion cycles. The current study indicated that scoring close to (i.e., within the paint) (ES = 0.08) or very far away (i.e., Three-point, ES = 0.05) was significantly greater for winning matches separated by 1- and 2-days of rest compared to consecutive matches (i.e., 0 rest days between matches). Additionally, shooting efficiency (P < 0.001), and attaining Defensive Rebounds (P < 0.001) and Steals (P < 0.001), were significant offensive and defensive KPIs that differentiated winning and losing teams. Similarly, opponent quality and match pace were important situational variables that affected match outcome during different match congestion cycles. While match location had an impact on winning following 1- and 2-days of rest, it had no impact for back-to-back matches (i.e., 0 days between matches). The current results will support coaches' offensive, defensive and recovery strategies during various match congestion cycles for a greater probability of winning NBA matches.

Performance Differences of Temporal Parameters and Point Outcome between Elite Men's and Women's Badminton Players According to Match-Related Contexts

Background: the aim of the present study was to identify the temporal and notational performance differences between elite men’s and women’s badminton players according to match type and set. Methods: the sample was composed of 60 men’s and 60 women’s matches classified by match type or duration: short (lower quartile), long (upper quartile) and regular matches (interquartile range). Temporal and notational variables were analysed for each match and compared between sexes accounting for match duration. Results: greater intensity for most variables (i.e., rally time, rest time, density, and strokes per match/rally) was exhibited in men’s matches compared with women’s matches (i.e., higher frequency between strokes). In addition, the greater intensity for men compared to women was more pertinent during long matches (13 significant variables) and less evident during short matches (six significant variables). Point outcome displayed similar trends for each sex during matches with more winners for men’s players when serving and more unforced errors for women’s players. Lastly, based on each match type, fewer sex differences were noted during sets 2 and 3, as the match progressed. Conclusion: men’s players performed at a greater intensity than women’s players for different match and set contexts, with this sex difference enhanced when controlling for match type and set. The development of sex- and match-specific scenarios will assist coaches and trainers in the design of specific training drills to enhance the athletic performance of elite badminton players.

Comparison of the movement patterns between small- and large-sided game training and competition in professional soccer players

BACKGROUND

The purpose of this investigation was to compare the movement patterns of professional soccer players during a small-sided game (SSG), a large-sided game (LSG), and a competitive friendly match (FM).

METHODS

Fourteen professional players participated in three training routines with a similar relative pitch area per player. The SSG and LSG consisted of 8 repetitions of 4-min game play, interspersed by 2 minutes of active recovery, and their data were compared to the first 32 minutes of a FM. All movement patterns from walking to sprint running were recorded using 10-Hz GPS devices while player perception of exertion was recorded via visual analogue scale, post-trial.

RESULTS

Total running distance (3852±405 vs. 3359±429 and 3088±414 m), running distance at 5-6.9 m/s (222±98 vs. 75±53 and 49±35 m) and maximal running speed (7.0±0.7 vs. 6.1±0.4 and 6.0±0.7 m/s) were significantly greater during FM than for SSG and LSG. However, the number of accelerations (462±16 vs. 458±12 vs. 422±15) and decelerations (733±31 vs. 692±24 vs. 609±27), and the rating of perceived exertion (8±1 vs. 7±1 vs. 5±1) were significantly greater during SSG compared to LSG and FM.

CONCLUSIONS

Although smaller game-based training routines do not replicate exactly the movement patterns of a competitive match, they can increase the execution of short-term and high-intensity movements for specialized training in professional soccer players.

Match statistics related to winning in the group stage of 2014 Brazil FIFA World Cup

Identifying match statistics that strongly contribute to winning in football matches is a very important step towards a more predictive and prescriptive performance analysis. The current study aimed to determine relationships between 24 match statistics and the match outcome (win, loss and draw) in all games and close games of the group stage of FIFA World Cup (2014, Brazil) by employing the generalised linear model. The cumulative logistic regression was run in the model taking the value of each match statistic as independent variable to predict the logarithm of the odds of winning. Relationships were assessed as effects of a two-standard-deviation increase in the value of each variable on the change in the probability of a team winning a match. Non-clinical magnitude-based inferences were employed and were evaluated by using the smallest worthwhile change. Results showed that for all the games, nine match statistics had clearly positive effects on the probability of winning (Shot, Shot on Target, Shot from Counter Attack, Shot from Inside Area, Ball Possession, Short Pass, Average Pass Streak, Aerial Advantage and Tackle), four had clearly negative effects (Shot Blocked, Cross, Dribble and Red Card), other 12 statistics had either trivial or unclear effects. While for the close games, the effects of Aerial Advantage and Yellow Card turned to trivial and clearly negative, respectively. Information from the tactical modelling can provide a more thorough and objective match understanding to coaches and performance analysts for evaluating post-match performances and for scouting upcoming oppositions.