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Spatial Performance Indicators and Graphs in Basketball

Author

Listed:
  • Paola Zuccolotto

    (University of Brescia)

  • Marco Sandri

    (University of Brescia)

  • Marica Manisera

    (University of Brescia)

Abstract

Assessing the scoring probability of teams and players in different areas of a court map is an important topic in basketball analytics, in order to define both game strategies and training programmes. In this contribution we propose a spatial statistical method based on classification trees, aimed to define a partition of the court in rectangles with maximally different shooting performances. Each analyzed team/player is characterized by its/his own partition, so comparisons can be made among different teams/players. In addition, shooting efficiency measures computed within the rectangles can be used to define spatial shooting performance indicators.

Suggested Citation

  • Paola Zuccolotto & Marco Sandri & Marica Manisera, 2021. "Spatial Performance Indicators and Graphs in Basketball," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 725-738, August.
    • Handle: RePEc:spr:soinre:v:156:y:2021:i:2:d:10.1007_s11205-019-02237-2
    DOI: 10.1007/s11205-019-02237-2
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    References listed on IDEAS

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    Cited by:

    1. Paola Zuccolotto & Marco Sandri & Marica Manisera, 2023. "Spatial performance analysis in basketball with CART, random forest and extremely randomized trees," Annals of Operations Research, Springer, vol. 325(1), pages 495-519, June.

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