Scoring probability maps on the basketball court through Spatial Point Pattern ana

Measuring shooting performances on the basketball court is crucial for understanding game dynamics and enhancing strategic decision-making. Accurate scoring probability evaluation offers insights that directly impact coaching decisions and players development. Spatial statistics and, in particular, point process analyses provide an ideal framework to accomplish these tasks. In this paper, we model the spatially-varying intensity of shots using classical point pattern methods, taking into account the outcome of each shot (i.e., made or missed). This approach lets us capture the spatial nature of shooting, going beyond traditional binary outcome models. By estimating the shot intensity at different locations, we derive scoring probabilities that reflect shooting performances across the court. Then, we create scoring probability maps, offering a clear visualization of shooting efficiency by location. These maps enable the coaching staff to better understand shooting dynamics and enhance their strategic planning. Our approach is validated through a case study using data from the Italian Basketball First League (LBA), provided by a professional club, ensuring high data quality and real-world relevance.