| Title: |
The Complexity in Basketball Performance: Quantifying the Independent Effects of Game Load, Technical–Tactical Approaches, and Contextual Factors on Player Performance. |
| Authors: |
Zhang, Shaoliang; Li, Ming; Sansone, Pierpaolo; Gómez, Miguel Ángel; Garcia, Franc; Calvo, Alberto Lorenzo; Scanlan, Aaron T.; Gonçalves, Bruno |
| Source: |
International Journal of Sports Physiology & Performance; Apr2026, Vol. 21 Issue 4, p563-573, 11p |
| Subject Terms: |
BIOMECHANICS; STATISTICAL models; RESEARCH funding; CLUSTER analysis (Statistics); PREDICTION models; EXERCISE; SCIENTIFIC observation; ACCELERATION (Mechanics); DESCRIPTIVE statistics; EXERCISE intensity; LONGITUDINAL method; INTRACLASS correlation; ATHLETIC ability; BASKETBALL; DATA analysis software; CONFIDENCE intervals; JUMPING; MOTION capture (Human mechanics); PHYSIOLOGICAL effects of acceleration; ALGORITHMS |
| Abstract: |
Purpose: This study aimed to examine effects of game load metrics, technical–tactical approaches, and contextual factors on game performance indicators in male professional basketball players. Methods: Data were collected across 26 official games from a single basketball team competing in a professional men's basketball competition. Game load metrics (rating of perceived exertion, PlayerLoad, accelerations, decelerations, jumps, and changes-of-direction); technical–tactical approaches (closeness, betweenness, and eigenvector centrality); and contextual factors (score differential and opponent level) were inputted into separate linear mixed-effects models to evaluate their relationships with 6 different game performance indicators including score, performance index rating, player total contribution, player impact estimate, game score, and efficiency (EFF). Results: Regarding load metrics, rating of perceived exertion was positively associated with all performance indicators (β = 0.449–0.697, P |
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| Database: |
Complementary Index |