Beyond Moneyball: The Role of Data Science in Baseball Operations

Beyond Moneyball: The Role of Data Science in Baseball Operations

Chris Fonnesbeck 

The use of data to inform baseball decisions has evolved greatly in the past decade. At the outset, some teams had been able to gain a competitive edge by using statistical analysis to identify undervalued players and optimize in-game strategies. In the intervening years, new streams of data, innovative statistical and machine learning methodologies, and significant investment in baseball research and development have led to a massive expansion of data science applications within the sport, including player evaluation, player development, pitch design, defensive positioning, and more. I will provide an overview of the role of data science in modern baseball and the ways in which it is shaping the future of the sport.

Chris Fonnesbeck is the Principal Quantitative Analyst in Baseball Research & Development for the Philadelphia Phillies and an Adjoint Associate Professor in the Department of Biostatistics at the Vanderbilt University Medical Center. His research interests include computational statistics, machine learning, Bayesian methods, and applied decision analysis. He hails from Vancouver, Canada and received his PhD from the University of Georgia.