The Complexity in Basketball Performance: Quantifying the Independent Effects of Game Load, Technical-Tactical...

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.

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).

Regarding load metrics, rating of perceived exertion was positively associated with all performance indicators (β = 0.449-0.697, P < .001), while high-intensity jumps were positively associated with player total contribution (β = 0.184, P = .003), player impact estimate (β = 0.322, P = .002), performance index rating (β = 0.241, P < .001), and EFF (β = 0.150, P = .007). For technical-tactical approaches, closeness centrality was positively associated with EFF (β = 0.411, P = .012). For contextual factors, greater score differential was associated with higher player total contribution (β = 0.206, P = .038), player impact estimate (β = 0.416, P = .033), performance index rating (β = 0.262, P = .003), and EFF (β = 0.225, P = .011).

Rating of perceived exertion and high-intensity jumping loads may be key factors to prioritize in preparing and monitoring players. Given player performance was influenced by score differential but not opponent level, players were able to sustain consistent performance outputs regardless of opponent strength.