Drafting Agent-Based Modeling Into Basketball Analytics

摘要

The growth of sports analytics (SA) has raised numerous research topics across a variety of sports, including basketball. Agent-based modeling (ABM) has great potential to assist and inform SA, but to date it has not been utilized. To support the use of ABM in SA, a model of a basketball game, which considers most fundamentals of play, is presented. Additionally, player behavior is partially predicated on assessing the length of a player's shooting streak (testing the “hot-hand” effect) and the consideration a team gives to a streak and their franchise player. The model's output is used to calibrate and validate it against statistics from the National Basketball Association (NBA). Via a set of experiments, the model indicates that an increased belief in the franchise player leads to increased scoring action, but a belief in the hot-hand a minor effect. Thereby, demonstrating the utility of ABM to SA, thus opening a new research field.