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.
Keywords: agent-based modeling, sports analytics, hot-hand effect.
- Basketball Agent-based model (needs NetLogo 6.1.0 3D)
- Overview, Design concepts, and Details (ODD) for the model
- Final Paper
Oldham, M and Crooks, A.T. (2019) Drafting Agent-Based Modeling into Basketball Analytics, 2019 Spring Simulation Conference (SpringSim’19), Tucson, AZ. (pdf)
Original model information: [https://www.comses.net/codebase-release/99a0a52a-8d1a-4a7e-bed8-2fb32b9dd7c0/]
Click on the image below to see a movie of model (Source: [https://youtu.be/NhF37rjCgbA])
