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Measuring sport performances under pressure by classification trees with application to basketball shooting

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  • Rodolfo Metulini
  • Mael Le Carre

Abstract

Measuring players' performance in team sports is fundamental since managers need to evaluate players with respect to the ability to score during crucial moments of the game. Using Classification and Regression Trees (CART) and play-by-play basketball data, we estimate the probabilities to score the shot with respect to a selection of game covariates related to game pressure. We use scoring probabilities to develop a player-specific shooting performance index that takes into account for the difficulty associated to score different types of shots. By applying this procedure to a large sample of 2016–2017 Basketball Champions League (BCL) and 2017–2018 National Basketball Association (NBA) games, we compare the factors affecting shooting performance in Europe and in the United States and we evaluate a selection of players in terms of the proposed shooting performance index with the final aim of providing useful guidelines for the team strategy.

Suggested Citation

  • Rodolfo Metulini & Mael Le Carre, 2020. "Measuring sport performances under pressure by classification trees with application to basketball shooting," Journal of Applied Statistics, Taylor & Francis Journals, vol. 47(12), pages 2120-2135, September.
    • Handle: RePEc:taf:japsta:v:47:y:2020:i:12:p:2120-2135
    DOI: 10.1080/02664763.2019.1704702
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    Cited by:

    1. Rodolfo Metulini & Giorgio Gnecco, 2023. "Measuring players’ importance in basketball using the generalized Shapley value," Annals of Operations Research, Springer, vol. 325(1), pages 441-465, June.

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