Data Analytics in Professional Sports

With the constant need to compete at high levels, sports organizations are increasingly embracing analytics-driven decision making to gain a competitive advantage over their opponents. From developing game strategy to drafting players, teams leveraging data-driven decisions using sophisticated analytics models. Apart from the sport, analytics has also become essential for the success of “non-sports” related functions of a sports organization, which include revenue management, sponsorship, fan engagement, and event operations. Despite the significant impact of sports from both societal and economic perspectives, analytics research in the domain of sports is limited. To address this gap in our literature, we provide a broad framework to navigate through these complex operations of a sports organization. The framework is based on two major functions within the realm of a sports organization – sports operations and business operations. Building on this functional framework, we outline the current analytics literature and potential avenues for analytics research. Beyond identifying future research areas, we specifically identify important and relevant open-ended research questions, discuss related trade-offs, and identify data sources to answer the research questions. This paper provides a basis for future analytics research that addresses the unique challenges that sports organizations face.