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

Abstract 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.

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Publication Details

Journal
Journal of Quantitative Analysis in Sports
Published
2025-09-18
DOI
https://doi.org/10.1515/jqas-2023-0038
Primary Topic
Sports Analytics and Performance
Type
article
Field-Weighted Citation Impact
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article

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

Matthew C. Jewell, Garritt L. Page, C. Shane Reese
Journal of Quantitative Analysis in Sports
Sports Analytics and Performance
article

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

Matthew C. Jewell, Garritt L. Page, C. Shane Reese
article en

Abstract

Abstract 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.

Journal of Quantitative Analysis in SportsVol. 21(4)
Brigham Young University (US), Northrop Grumman (United States) (US)
Openalex Percentile: Top 66%
Sports Analytics and Performance
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