Session 1: Sports Economics

Lee Kennedy-Schafer, Assistant Professor of Biostatistics, Yale University

Lee Kennedy-Shaffer is an assistant professor of biostatistics at the Yale School of Public Health. His primary research interests are in study designs to evaluate vaccines, infectious disease control, and health policies. A lifelong Mets fan, he is also interested in using these methods to understand baseball and sports more generally, identifying what causal inference methods work in sports settings, and using sports to broaden interest in statistics to students and the wider public.

Hashan Peiris, PhD candidate of Statistics and Actuarial Science, Simon Fraser University

Hashan Peiris is a PhD candidate in the Department of Statistics and Actuarial Science of Simon Fraser University, supervised by Dr. Himchan Jeong and Dr. Tim Swartz. His research interests are risk analysis with telematics data in automobile insurance and sports analytics. In 2021, Hashan started pursuing the actuarial pathway through the Society of Actuaries and completed a master's in actuarial science from SFU in 2023. His recent research work with Dr. Jeong and Dr. Swartz has been published in the ASTIN Bulletin and the International Journal of Sports Science & Coaching, respectively. Further, he has collaborated with Dr. Tim Swartz to conduct sports analytics workshops in Canada and Sri Lanka. Hashan is one of the recipients of the James C. Hickman Scholarship from the Society of Actuaries in 2024.

Shane Sanders, TBD

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Alivia Uribe, TBD

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Toby Moskowitz, TBD

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Session 2: Advancements in Sports Analytics and Education

Ben Baumer, Professor of Statistical & Data Sciences, Smith College

Benjamin S. Baumer is a professor in the Statistical & Data Sciences program at Smith College. Ben is a co-author of The Sabermetric Revolution, Modern Data Science with R, and the second and third editions of Analyzing Baseball Data with R. Ben has received the Waller Education Award from the ASA Section on Statistics and Data Science Education, the Significant Contributor Award from the ASA Section on Statistics in Sports, and the Contemporary Baseball Analysis Award from the Society for American Baseball Research. His research interests include sports analytics, data science, statistics and data science education, statistical computing, and network science.

Owen Fiore, TBD

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Ron Yurko, Assistant Teaching Professor of Statistics & Data Science, Carnegie Mellon University

Ron Yurko is an Assistant Teaching Professor in the Department of Statistics & Data Science at Carnegie Mellon University, and is the Director of the Carnegie Mellon Sports Analytics Center. His research focuses on developing methods at the interface of inference and machine learning, oriented towards problems in sports analytics and natural language processing. His work has been featured in popular media outlets such as The Athletic, FiveThirtyEight, The Wall Street Journal, and The Washington Post. He is a three-time degree holder from Carnegie Mellon: with a bachelors, masters, and PhD in Statistics. He also has industry experience in both finance and professional sports.

Elizabeth Upton, Assistant Professor of Mathematics and Statistics, Williams College

Elizabeth Upton is an Assistant Professor in the Mathematics and Statistics Department at Williams College, where she has been since completing her Ph.D. in Statistics at Boston University in 2019. Her research focuses on applied statistics, with a particular interest in regression models for network data. Before graduate school, she taught high school math and worked in finance analyzing currency markets. Liz loves teaching statistics, collaborating with researchers across disciplines, and talking sports data whenever she gets the chance. Outside of work, she’s usually chasing around her three kids or cheering on the New England Patriots (#54 forever).

Keith D’Amelio, Assistant Professor of Mathematics and Statistics, Williams College

Dr. Keith D’Amelio is a leader in the realm of human performance. With a PhD in applied sports science and an extensive background in elite sports, including roles with such organizations as the Boston Celtics, Toronto Raptors and Stanford University as well as Nike. Keith stands squarely at the intersection of performance optimization, technological innovation, and the evolving landscape of human performance.

A pioneer in leveraging technology and data-informed methodologies, Keith has catalyzed industry-wide adoption of cutting-edge approaches. His influence extends beyond one sport, working with athletes, teams, and organizations spanning the NBA, MLB, NBA Players Association, WNBA, NWSL, NFL, EPL, AFL, as well as within the business and start up world, showcasing his ability to drive innovation and progress across diverse sectors.

As the former Director of Athlete Performance at Nike, Keith led transformative initiatives to support Nike’s elite athletes and teams and drive innovation across the organization. His leadership in this role underscored his commitment to pushing the boundaries of human performance through focused exploration. Now as an investor, advisor, and consultant for both spor1ng organizations and companies alike, Keith empowers teams and enterprises with his unique approach and understanding of organizational dynamics.