Selecting the Best Compositions of a Wheelchair Basketball Team: A Data-Driven Approach

Abstract

Wheelchair basketball, regulated by the International Wheelchair Basketball Federation, is a sport designed for individuals with physical disabilities. This article presents a data-driven tool that effectively determines optimal team lineups based on past performance data and metrics for player effectiveness. Our proposed methodology involves combining a Bayesian longitudinal model with an integer linear problem to optimize the lineup of a wheelchair basketball team. To illustrate our approach, we use real data from a team competing in the Rollstuhlbasketball Bundesliga, namely the Doneck Dolphins Trier. We consider three distinct performance metrics for each player and incorporate uncertainty from the posterior predictive distribution of the longitudinal model into the optimization process. The results demonstrate the tool’s ability to select the most suitable team compositions and to calculate posterior probabilities of several players playing together in the best composition.