Measuring players’ and teams’ shooting performance in the basketball court can give important information aimed to the definition of both game strategies and personalized training programs. From a methodological point of view, the estimation of the scoring probability can be faced by resorting to different tools in the field of statistical or algorithmic modelling. As a matter of fact, the most natural theoretical framework for this problem is that of spatial statistics, with the particularity that the analysis is based on the binary measurement variable informing about whether a shot is made or missed. In this paper we propose the use of spatial statistics tools suited to this specific context, namely lorelograms to investigate the spatial correlation and Indicator Kriging to draw scoring probability maps. A structured case study is presented, dealing with all the teams of the Italian Basketball First League, based on a non-public dataset containing substantive additional information, that allows interesting insights about assisted and uncontested shots.

Carlesso, M. L., Cappozzo, A., Manisera, M., Zuccolotto, P., Scoring probability maps in the basketball court with Indicator Kriging estimation, <<COMPUTATIONAL STATISTICS>>, 2024; (00): 1-21. [doi:10.1007/s00180-024-01564-4] [https://hdl.handle.net/10807/304039]

Scoring probability maps in the basketball court with Indicator Kriging estimation

Cappozzo, Andrea;
2024

Abstract

Measuring players’ and teams’ shooting performance in the basketball court can give important information aimed to the definition of both game strategies and personalized training programs. From a methodological point of view, the estimation of the scoring probability can be faced by resorting to different tools in the field of statistical or algorithmic modelling. As a matter of fact, the most natural theoretical framework for this problem is that of spatial statistics, with the particularity that the analysis is based on the binary measurement variable informing about whether a shot is made or missed. In this paper we propose the use of spatial statistics tools suited to this specific context, namely lorelograms to investigate the spatial correlation and Indicator Kriging to draw scoring probability maps. A structured case study is presented, dealing with all the teams of the Italian Basketball First League, based on a non-public dataset containing substantive additional information, that allows interesting insights about assisted and uncontested shots.
2024
Inglese
Carlesso, M. L., Cappozzo, A., Manisera, M., Zuccolotto, P., Scoring probability maps in the basketball court with Indicator Kriging estimation, <<COMPUTATIONAL STATISTICS>>, 2024; (00): 1-21. [doi:10.1007/s00180-024-01564-4] [https://hdl.handle.net/10807/304039]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/304039
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