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Changing the Game: The Statistical Analysis of Sports
June 10,7:00 pm - 8:00 pm
Winning in team sports has always been a function of superior ownership, front offices, and players and coaches. But the emergence of sabermetrics in baseball during the 1990s not only revolutionized that sport’s modern era, but professional sports leagues as a whole. Today, every major professional sports team either has an analytics department or an analytics expert on staff. Join a panel of analytics professionals from the NFL, NBA, and MLB for a roundtable discussion on the impact of math and science in sports and what the future holds for our data-driven pastimes.
A life-long sports fan, Dr. Jeremy Abramson has always been fascinated by the impact and importance quantitative information has on athletic competition. He is interested in the acquisition, processing, analysis, and visualization of sports-related data, as well as how to construct narratives around the entire process. Jeremy teaches “Introduction to Sports Analytics” at the University of Southern California, where he is a Research Computer Scientist in USC’s Information Sciences Institute, and a lecturer in USC’s Data Science Program. The course acquaints students with the multidisciplinary aspect of sports analysis, through examples and guest speakers in the fields of statistics, economics, operations research, and computer science.
Recently, Jeremy has become involved with the development of quantitative sports analysis curriculums, from K-12 STEM programs to potential specialized graduate degrees. At the collegiate level, his focus is on developing curriculum that gives students a broader base of skills and domain knowledge than traditional existing programs. As this exciting field evolves, he is dedicated to answering the question “How do we prepare the next generation of students for a career in sports analysis?” Jeremy holds a BS in computer science from the University of California, Davis, and PhD in computer science from the USC. Follow him on Twitter @JeremyAbramson.
Dr. Eric Eager is Vice President of Research and Development at Pro Football Focus (PFF), where he uses his training as an applied mathematician to produce solutions to quantitative problems for 32 NFL clients, over 85 NCAA football clients, and numerous media clients and contacts. He also co-hosts the PFF Forecast podcast, which can be found on PodcastOne and iTunes. Before joining PFF in 2018, he was a professor in the Department of Mathematics and Statistics at the University of Wisconsin–La Crosse, where he published over 20 papers in mathematical biology and the scholarship of teaching and learning while securing more than $300,000 in National Science Foundation funding for undergraduate mentorship. Dr. Eager studied applied mathematics and mathematical biology at the University of Nebraska, where he wrote his PhD thesis on how stochasticity and nonlinear processes affect population dynamics. Follow him on Twitter @PFF_Eric.
Diana Ma is a data scientist with the Los Angeles Lakers, where she she works for the front office in basketball operations and does analyses involving player evaluation, roster construction, and in-game strategy. Prior to joining the Lakers, she worked as a data scientist in digital marketing analytics at Digitas in Boston. She earned a BS in statistics from Queen’s University and an MS in applied statistics from New York University.
Dr. Daniel Mack is in his second season as Assistant General Manager-Research & Development and his eighth season with the Royals overall. He previously served as the Senior Director-Quantitative Analysis/Amateur Scouting and Director-Baseball Analytics/Research Science. Dr. Mack oversees the Quantitative Analysis staff to assist with research and development across all areas of Baseball Operations with a focus on amateur scouting. Prior to accepting the job with Kansas City, Mack obtained a doctorate in computer science from Vanderbilt University, where his dissertation research focused on machine learning and anomaly detection. While pursuing his doctorate, he worked as a research assistant at the Institute for Software Integrated Systems where he and his research group won the NASA Associate Administrator Award for Technology and Innovation for work combining machine learning with fault diagnosis. Dr. Mack earned a master’s degree in computer science with a concentration in machine learning at Columbia University and a bachelor’s degree in computer science from the University of Notre Dame.
Accessing the Program
This free, online program will take place via Zoom. Registration is currently open and will remain open until the event has ended. Your link to join the program will be included in the confirmation email and on the confirmation screen after you complete your registration.
The Linda Hall Library encourages people of all backgrounds and abilities to enjoy our public programs. Closed captions are provided. If you require additional reasonable accommodations in order to participate, please contact email@example.com or call 816.926.8753 at least 24 hours in advance of the program.
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The program will also be livestreamed on the Library’s Facebook page.
This program is funded by the Ewing Marion Kauffman Foundation. Its content is solely the responsibility of the Linda Hall Library.