<i>Homo certus</i>in professional basketball? Empirical evidence from the 2011 NBA Playoffs

Wallace, Scott; Caudill, Steven B.; Mixon, Franklin G.

doi:10.1080/13504851.2012.727965

Cited by 11 publications

(9 citation statements)

References 3 publications

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“…Studies have found that abundant sleep ( Mah et al, 2011 ), positive emotional state ( Uphill, Groom & Jones, 2014 ), and better physical fitness ( Fort-Vanmeerhaeghe et al, 2016 ) promote match performance. In addition, the ability to handle pressure at the critical moment ( Wallace, Caudill & Mixon, 2013 ), belief in “hot hands” ( Attali, 2013 ), imagery training, self-relaxation and self-talk ( Kendall et al, 1990 ) all impact sports performance. Although researchers have ascertained some key factors influencing sports performance, only a few studies have explored the relationship between visual attention processing and match performance among basketball players.…”

Section: Introductionmentioning

confidence: 99%

Dynamic visual attention characteristics and their relationship to match performance in skilled basketball players

Jin

et al. 2020

PeerJ

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Background Dynamic visual attention is important in basketball because it may affect the performance of players and thus the match outcome. The goals of this study were to investigate the difference in dynamic visual attention characteristics between highly skilled basketball players and nonathletic college students and to explore the relationship between visual attention and game-related performance among the basketball players. Methods In total, 24 highly skilled basketball players and 24 nonathletic college students participated in a multiple object tracking task. The task was conducted so that either the number of targets that were visually tracked or the speed at which a given number of tracked targets moved was altered to examine the difference in dynamic visual attention characteristics between the basketball players and nonathletic college students. The relationship between visual tracking speed (VTS) and game-related statistics, including assists, steals, mistakes, fouls and points scored recorded for every match during the season, was assessed among the basketball players by using Pearson correlations. Results A significant main effect of target tracking load was observed (P < 0.001), with visual tracking performance significantly decreased as target number increased. In addition, the speed at which the targets moved had a significant effect on visual tracking performance (P < 0.001), with tracking performance significantly decreased as target speed increased. However, no significant difference was observed in the abilities of basketball players and nonathletic college students to simultaneously track up to six targets. By contrast, a significant interaction between group and target speed was found (P < 0.001), with the visual tracking accuracy of basketball players significantly greater than that of college students at the higher target speeds examined (P < 0.001). Among basketball players, there were positive, large, and statistically significant correlations in the accuracy in VTS trials and the number of assists (P < 0.001) and between the accuracy in VTS trials and the number of steals (P < 0.001). Conclusion The advantage of skilled basketball players to handle dynamic visual information in a multiple object tracking task was not attributable to the target number but to the target speed. Those athletes with greater dynamic visual attention were more likely to successfully assist or to steal the ball, enhancing performance of the athlete as well as contributing to a more successful team match. These findings may inform basketball training programs to improve player and team performances during matches.

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Section: Introductionmentioning

confidence: 99%

Dynamic visual attention characteristics and their relationship to match performance in skilled basketball players

Jin

et al. 2020

PeerJ

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“…Another possible explanation could be that these players take longer to appear in the game, because they need more time to get familiar with the different environmental game constraints . Their improvements in performance in the fourth quarter were also very relevant, because NBA players usually drop in higher pressure moments, such as the last game quarter of the playoffs games (Wallace, Caudill, & Mixon Jr., 2013).…”

Section: Playoffsmentioning

confidence: 99%

Key game indicators in NBA players’ performance profiles

Dehesa

Vaquera

Gonçalves³

et al. 2019

Kinesiology (Zagreb, Online)

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The aim of the present study was to identify and describe players’ performances in NBA games using individual and team-based game variables. The sample was composed by 535 balanced games (score differences below or equal to eight points) from the regular season (n=502) and the playoffs (n=33). A total of 472 players were analysed. The individual-based variables were: minutes on court, effective field-goal percentage, free-throws/field-goals ratio, offensive rebound percentage, turnover percentage and playing position. The team-based variables were: team points minus opponent’s points (on and off court), NET score (player’s on values minus his/her off values), maximum negative and positive point difference, team’s winning percentage, game pace, defensive and offensive ratings. A two-step cluster analysis was performed to identify the player’s profiles during regular season and playoff games. The results identified five performance profiles during regular season games and four performance profiles during playoff games. The profiles identified were mainly characterized by the game quarter and the negative NET indicator (players’ performance on court minus their performance off court) in regular season games and the positive NET indicator during playoff games and second and third game-quarters. Coaching staffs can fine-tune these profiles to develop more team-specific models and, conversely, use the results to monitor and rebuild team formation under the constrained dynamics of the game and competition stages.

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“…Under pressure, some players tend to take fewer shots to the basket (Wallace, Caudill, & Mixon, 2013). Therefore, with the exception of cluster 3, players shot more in the first game of the playoff series.…”

Section: Comparing Performances Between the First And The Last Game Omentioning

confidence: 99%

Exploring game performance in NBA playoffs

Mateus¹,

Gonçalves²,

Abade

et al. 2018

Kinesiology (Zagreb, Online)

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This study aimed to identify performance profiles in NBA playoffs and describe performances in the first and the last games of the series. Thirty games from the official box-scores and player-tracking data of the 2014/15 NBA playoffs were considered. A k-means cluster analysis was performed to group the players according to their game performance profiles and a discriminant analysis was conducted to identify the game-related statistics that best discriminated the groups. The first function correctly classified 64.2% of the cases and the second function classified 29.9% of the cases. The cluster analysis identified four different performance profiles and from the discriminant analysis emerged several offensive and defensive variables to classify the players in the clusters. The identified trends help to improve understanding of the game during different stages of playoffs. Coaches may use this information to better prepare their teams for different game scenarios.

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Homo certusin professional basketball? Empirical evidence from the 2011 NBA Playoffs

Cited by 11 publications

References 3 publications

Dynamic visual attention characteristics and their relationship to match performance in skilled basketball players

Dynamic visual attention characteristics and their relationship to match performance in skilled basketball players

Key game indicators in NBA players’ performance profiles

Exploring game performance in NBA playoffs

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