Purpose: This study aimed to explore the relationships of game load, recovery status, and well-being with performance efficiency in basketball players across different performance levels. Methods: Data from 16 professional male basketball players across 18 official basketball games were analyzed utilizing principal component analysis to reduce dimensionality and identify key factors related to game load, perceived recovery, and well-being associated with performance. Quantile regression was employed to assess the impact of these factors on performance efficiency at different quantiles (10th, 50th, and 90th). Results: Six factors were extracted. The first factor, composite load (a combined measure of the external physical loads and session rating of perceived exertion experienced by players), explained 42% of the variance, followed by well-being (15%), composite jump load (focused on jump-related movements, 11%), PlayerLoad per minute (5%), muscle soreness (4%), and recovery status (4%). Quantile regression analyses revealed that composite load had a significant positive effect in the ordinary least-squares estimate (P < .001) and at the 10th (P = .044) and 50th quantiles (P < .001). Composite jump load had significant effects in the ordinary least-squares estimate (P < .001) and the 50th quantile (P = .003). PlayerLoad per minute had significant effects in the ordinary least-squares estimate (P < .001) and in both the 10th (P < .001) and the 50th quantiles (P < .001). In addition, well-being was significant at the 50th quantile (P < .001), whereas muscle soreness and recovery showed no significant effects. Conclusion: Composite load and PlayerLoad per minute consistently had positive associations with game performance, particularly for players at low and medium performance levels.
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