"Using Machine Learning to Better Evaluate American Football Players"
Dr. Eric Eager
VP of Research and Development at SumerSports
Friday, Oct. 14
4–5 p.m.
Avery 115
Abstract: The game of football is undergoing a significant shift towards the quantitative. Much of the progress made in the analytics space can be attributed to play-by-play data and charting data. However, recent years have given rise to tracking data, which has opened the door for innovation that was not possible before. In this talk I will describe how to gain an edge in player evaluation by building off of traditional charting data with state-of-the-art player tracking data, and foreshadow how such methods will revolutionize the sport of football in the future.
Bio: Eric Eager is the VP of Research and Development at SumerSports, a startup aimed at helping football teams optimize their decision making processes. He was previously at Pro Football Focus, where he built an industry-leading analytics group. Prior to joining PFF, he earned a PhD in mathematical biology at the University of Nebraska - Lincoln, and went on to publish 25 papers in math, biology and the scholarship of teaching and learning while a professor at the University of Wisconsin - La Crosse.