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A0505
Title: Zero-inflated Poisson model with clustered regression coefficients: an application to field goal attempts Authors:  Yishu Xue - University of Connecticut (United States)
Guanyu Hu - The University of Texas Health Science Center at Houston (United States)
Hou-Cheng Yang - Florida State University (United States) [presenting]
Abstract: Although basketball is a dynamic process sport, with 5 plus 5 players competing on both offense and defense simultaneously, learning some static information is predominant for professional players, coaches and team managers. In order to have a deep understanding of field goal attempts among different players, we propose a zero-inflated Poisson model with clustered regression coefficients to learn the shooting habits of different players over the court and the heterogeneity among them. Specifically, the zero-inflated model recovers the large proportion of the court with zero field goal attempts. The mixture of finite mixtures model learns the heterogeneity among different players based on clustered regression coefficients and inflated probabilities. Both theoretical and empirical justification through simulation studies validates the proposed method. We apply the model to the National Basketball Association (NBA) to learn players' shooting habits and heterogeneity among different players over the 20172018 regular season. This illustrates our model as a way of providing insights from different aspects.