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Since the National Basketball Association (NBA) fined the San Antonio Spurs in 2012 for their decision to rest their best players during a nationally televised game, there has been much discussion surrounding player “load” management. In fact, more teams in the NBA have begun to adopt the Spurs approach of strategically resting players in an effort to avoid injury and ensure players are at peak performance towards the end of the season. Although there is general agreement that load management is important for some players to avoid injury, it isn’t clear that managing minutes during the beginning of a season results in peak performance towards the end. In this paper we attempt to address this. We do this by formulating a Bayesian hierarchical model that borrows strength among players to estimate a league-wide effect that average minutes played has on end-of-season performance based on 14 modern performance metrics. Generally speaking, it appears that end-of-season offensive and defensive performance tends be above average as average minutes played is increased.

Assessing end-of-season performance as a function of average minutes played for NBA players