Sport and Big Data

(3 Credit Hours) · Undergraduate

Sport is one of the most enduringly popular and significant cultural activities in the United States. Data has always been a central part of professional sport in the US, from Henry Chadwick's invention of the baseball box score in the 1850s to the National Football League's use of Wonderlic test scores to evaluate players. This course focuses on the intersecting structures of power and identity that shape how we make sense of the "datification" of professional sport. By focusing on the cultural significance of sport data, this course will put the datafication of sport in historical context and trace the ways the datafication of sport has impacted athletes, fans, media, and other stakeholders in the sport industry. The course will also delve into the technology systems used to collect and analyze sport data, from the TrackMan and PITCHf/x systems used in Major League Baseball to the National Football League's Next Gen Stats partnership to emerging computer vision and artificial intelligence research methods. Readings for this course will draw on texts like Christopher Phillips' Scouting and Scoring: How We Know What We Know About Baseball (2019), Ruha Benjamin's Captivating Technology: Race, Carceral Technoscience, and Liberatory Imagination in Everyday Life (2019), Jamie Schultz's Qualifying Times: Points of Change in Women's Sport (2014), and Thomas Oates' Football and Manliness: An Unauthorized Feminist Account of the NFL (2017). Class meetings will be split between discussions of conceptual readings and applied work with sport data and technology systems. Coursework may include response papers, hands-on work with data, and a final project. Familiarity with statistical analysis, data science, or computer science tools and methods is NOT a prerequisite for this course.