The Influence of Contextual Variables on Training Load Prescription in Basketball: An Example of a Professional Australian Men’s Basketball Team
(Jack Patterson, Russell Rayner, David L. Carey, Mathew O’Grady, Scott W. Talpey)

This study aimed to investigate the influence of contextual variables related to team performance, individual performance and scheduling on the external training load placed upon professional basketball players following a won compared to a lost game. Fifteen male professional basketball players from a single club competing in the Australia’s top tier National Basketball League (NBL) during the 2023/2024 season participated in this study. Total player load, peak player load, player load per minute and the work to rest ratio derived from accelerometry were measures of external player load used in the analysis. Linear mixed models with the match outcome (win/loss), expected margin vs. outcome, days between games, and player efficiency as fixed effects, and player ID as a random intercept were employed. A statistically significant (p = 0.001) 62.46 au difference in total player load was observed following a win compared to a loss. However, when considering the random effects of an individual, individual performance, team performance and scheduling as fixed effects, a non-significant (p = 0.086) difference was observed with the individual player being the most influential variable. There were no statistically significant differences in peak player load (p = 0.734), player load per minute (p = 0.281), and the work to rest ratio (p = 0.782) following a win compared to a loss. The external training load prescribed to professional basketball players is highly individualized. Practitioners monitoring the training demands of players should consider the influence of individual factors when designing training.