Analysis of the efficacy of possessions in boys' 16-and-under basketball teams: differences between winning and losing teams

The Comparison of Psychological Characteristics between Korean and Japanese Women Pro-Basketball Players

OBJECTIVE

Korea (ranked 16th) and Japan (ranked 13th) show similar rankings, skills, and performance in basketball. However, the countries differ in size and the number of players in the national women's basketball system. The current study aimed to compare the psychological factors (anxiety, and temperament and character) and the national teams' players' characteristics between 80 Korean (WKBL players) and 76 Japanese (WJBL players) female basketball players in six professional teams each.

METHODS

All players were asked to complete demographic characteristics including age, career years, position, number of past and presents positions, and clinical scales, including sports anxiety, state anxiety, trait anxiety, and the Temperament and Character Inventory (TCI). Hierarchical logistic regression analyses among individual factors, physical factors, basketball status, anxiety factors, and temperamental conditions were conducted.

RESULTS

In all basketball players, all five models were significantly associated with national team players. The TCI factors were the strongest predictive factors for Korean national team players, while the anxiety factors were the strongest predictive factors for Japanese national team players. WKBL players in all positions showed higher sports anxiety and harm avoidance than WJBL players. WJBL players scored higher on self-directedness and cooperativeness than WKBL players.

CONCLUSION

For predicting national team players, temperament and character were crucial factors in WKBL players where anxiety was the most important one for WJBL players.

Successful and Unsuccessful Offensive Sequences Ending in a Shot in Professional and Elite Under-16 Basketball

Following observational methodology, we analyzed successful and unsuccessful offensive attacks by professional and elite under-16 (U16) basketball players in Spain using an adapted ad hoc observation instrument designed to study efficiency in basketball. We identified both similarities and differences between how players from both categories built their attacks. The synchronic statistical analysis based on frequency counts showed that shots were more efficient in professional basketball and that U16 basketball was less static and had a higher frequency of fast breaks. Diachronic analysis, which consisted of T-pattern detection using Theme software, allowed us to identify characteristic successful and unsuccessful offensive sequences in professional and elite U16 basketball. These results have practical implications as they can be used to design training drills and prepare for competitions in U16 and professional basketball.

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.

Investigating the game-related statistics and tactical profile in NCAA division I men's basketball games

The aim of this study was to analyze the game-related statistics and tactical profile in winning and losing teams in NCAA division I men’s basketball games. Twenty NCAA division I men’s basketball close (score difference: 1-9 points) games were analyzed during the 2013/14 season. For each game, the game-related statistics were collected from the official teams’ box scores. Number of ball possessions, offensive and defensive ratings and the Four Factors (effective field goal percentage; offensive rebounding percentage, recovered balls per ball possession, free throw rate) were also calculated. The tactical parameters evaluated were: ball reversal, dribble in key area, post entry, on-ball screen, off-ball screen, and hand off. Differences between winning and losing teams were calculated using a magnitude-based approach. Winning teams showed a likely higher percentage of 3-point goals made, number of defensive rebounds and steals and a very likely higher number of free throws made and free throws attempted. Furthermore, winning teams showed a likely higher team offensive rating and effective field goal percentage and a very likely higher free throw rate compared to losing teams. Finally, the results revealed a likely higher number of ball reversals and post entries in winning teams compared to losing teams. This study highlighted the game-related statistics and the tactical actions differentiating between winning and losing teams in NCAA Division I men’s basketball close games. Coaches should use these results to optimize their training sessions, focusing on those variables that might increase the possibility to win close games.

Determinants of the effectiveness of fast break actions in elite and sub-elite Italian men's basketball games

The aim of this study was to examine the determinants of successful and unsuccessful fast-break (FB) actions in elite and sub-elite basketball games. Fifteen 1^st-division (elite) and fifteen 3^rd-division (sub-elite) Italian men's championship games were analysed across two seasons (2012/2013 and 2013/2014). A binary logistic regression analysis was performed, and the fast-break outcome (successful vs. unsuccessful) was adopted as the dependent variable separately in both elite and sub-elite games. FB execution (initiation, advance and completion phases), typology (primary and secondary break) and the number of players involved (equal number or superiority) were used as independent variables. The results showed that the rate of success of FB actions was 63.5% and 59.7% in elite and sub-elite games, respectively. Moreover, successful FBs were more likely to be completed in the lane in relation to unsuccessful ones in both elite and sub-elite games (p<0.05). Finally, descriptive statistics showed that both elite and sub-elite teams executed FBs similarly. This study highlighted that completion zone was the only predictor of a successful fast break in basketball, while the typology and number of players involved did not predict fast break effectiveness. Moreover, elite and sub-elite teams executed fast break actions similarly. These findings might be useful for basketball coaches to optimize the training of FB actions.

Discriminatory Power of Game-Related Statistics in 14–15 Year Age Group Male Volleyball, According to Set

This study compared volleyball game-related statistics by outcome (winners and losers of sets) and set number (total, initial, and last) to identify characteristics that discriminated game performance. Game-related statistics from 314 sets (44 matches) played by teams of male 14- to 15-year-olds in a regional volleyball championship were analysed (2011). Differences between contexts (winning or losing teams) and “set number” (total, initial, and last) were assessed. A discriminant analysis was then performed according to outcome (winners and losers of sets) and “set number” (total, initial, and last). The results showed differences (winning or losing sets) in several variables of Complexes I (attack point and error reception) and II (serve and aces). Game-related statistics which discriminate performance in the sets index the serve, positive reception, and attack point. The predictors of performance at these ages when players are still learning could help coaches plan their training.

Number of players who gain ball possession as a function of basketball mass among 9-11-year-old male players

This study analyzed whether a ball with a higher (540-g) or lower (440-g) mass than the regulation ball (485-g) resulted in a larger number of participants gaining ball possession during games. Prior studies have indicated that ball handling is facilitated by decreasing the mass of the ball. It was assumed that a greater number of children gaining possession of the ball indicated greater ease of use and more control. Thus, the hypothesis was that the number of participants who gained ball possession would increase when using a ball of lower mass. The participants were 54 boys from six youth basketball teams. Participants played four games with each one of the three different balls and the number of possessions was calculated using videos of each game. The hypothesis was only partially supported: the number of participants who gained possession with the regular ball was similar to that with the 440-g ball and with the 540-g ball, but a greater number of participants gained possession with the 440-g ball in comparison to the 540-g ball. This result suggests balls that differ by more than 65 g may affect actual game outcomes.