Management mathematics in sport—moneyball and soccer

Abstract Accepted by: Aris Syntetos The data revolution has not passed soccer by as an industry. However, it has not transformed the sport in the same way it has in, say, baseball. In this article, we first describe the current landscape of analytics in soccer, using England as the focus of our attention. We document the extent to which academic contributions from management mathematics and across a range of disciplines have shaped the development of analytic methods in the sport to date and consider the extent to which they will be essential as analytics continues to advance in the sport, most notably via the use of causal inference methods. We then propose an approach to analytics in soccer that builds both on the nature of soccer as an industry and the academic advances to date in the analysis of observational data. We note that such an approach can and should be consistent, with a system of ranking players and teams at its core, and must rely on causal methods of inference.