To assess 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 method based on regression trees, aimed to define a partition of the court in rectangles with maximally different scoring probabilities. Each analysed team/player has 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 scoring performance indicators.
(2019). Basketball spatial performance indicators . Retrieved from http://hdl.handle.net/10446/228024
Basketball spatial performance indicators
Manisera, Marica;Metulini, Rodolfo;Zuccolotto, Paola
2019-01-01
Abstract
To assess 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 method based on regression trees, aimed to define a partition of the court in rectangles with maximally different scoring probabilities. Each analysed team/player has 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 scoring performance indicators.| File | Dimensione del file | Formato | |
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24. Spatial performances indicators basketball_DSSR19.pdf
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