Case—Moneyball for Murderball: Using Analytics to Construct Lineups in Wheelchair Rugby

Motivated by the problem of lineup optimization in wheelchair rugby (WCR), this case study covers descriptive, predictive, and prescriptive analytics. The case is presented from the perspective of a new assistant coach of Canada’s national WCR team, who has been tasked by the head coach to use various analytics techniques to improve their lineups. Whereas the data and actors are fictitious, they are based on real data and discussions with the national team coach and sport scientists. To solve the case, students must conduct data analysis, regression modeling, and optimization modeling. These three steps are tightly linked, as the data analysis is needed to prepare the data for regression, and the regression outputs are used as parameters in the optimization. As such, students build proficiency in developing an end-to-end solution approach for a complex real-world problem. The primary learning objectives for the students are to understand the differences between descriptive, predictive, and prescriptive analytics, to build proficiency in implementing the models using appropriate software, and to identify how these techniques can be applied to solve problems in other sports or other application areas. Supplemental Material: The Teaching Note and data files are available at https://www.informs.org/Publications/Subscribe/Access-Restricted-Materials .