Research Papers

Min-hwan Oh
Suraj Keshri
Garud Iyengar

‍

‍

Abstract: Conventional approaches to simulate matches have ignored that in basketball the dynamics of ball movement is very sensitive to the lineups on the court and unique identities of players on both offense and defense sides. In this paper, we propose the simulation infrastructure that can bridge the gap between player identity and team level network. We model the progression of a basketball match using a probabilistic graphical model. We model every touch and event in a game as a sequence of transitions between discrete states. We treat the progression of a match as a graph, where each node is a network structure of players on the court, their actions, events, etc., and edges denote possible moves in the game flow. Our results show that either changes in the team lineup or changes in the opponent team lineup significantly affects the dynamics of a match progression. Evaluation on the match data for the 2013-14 NBA season suggests that the graphical model approach is appropriate for modeling a basketball match.