Estimating positional plus-minus in the NBA

Gong Hua () and Chen Su
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Gong Hua: Department of Sport Management, 3990 Rice University , Houston, TX, USA
Chen Su: Department of Statistics, 3990 Rice University , Houston, TX, USA

Journal of Quantitative Analysis in Sports, 2024, vol. 20, issue 3, 193-217

Abstract: Plus-minus is a widely used performance metric in sports. Players with high plus-minus ratings are often considered more efficient than others. While numerous plus-minus models have emerged since the introduction of adjusted plus-minus in 2004, most of these metrics focus on evaluating player performance at the individual level. In the present study, we follow the plus-minus framework and adopt a hierarchical Bayesian linear model to estimate plus-minus at the position level in the NBA from 2015–16 to 2021–22. Results show that players with versatile offensive skills and big players who defend the paint area are the most valuable offensive and defensive contributors respectively. We also find that the gaps in offensive plus-minus between offensive position groups have decreased over time. Overall, our analysis offers valuable information regarding average positional values in the NBA, allowing more objective player comparisons within position groups. We also show improved prediction accuracy in player plus-minus when factoring in player positions.

Keywords: basketball; Bayesian analysis; player positions; player evaluation (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1515/jqas-2022-0120

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