Great Lakes Analytics in Sports Conference
Carnegie Mellon University
NFL Player Evaluation Using
Expected Points Added with nflscrapR
This talk will introduce a reproducible method for calculating expected points added (EPA) using the nflscrapR package, as well as different scoring event probability added measures based on the presenting team's novel multinomial logistic regression expected points model. Next, Ronald will examine the repeatability and predictive value of player-level EPA using NFL play-by-play data from 2009-2016. Finally, he will propose new metrics for player evaluation based on these measures, such as EPA weighted completion percentage for quarterbacks, and compare rankings with more traditional football statistics.
Ronald Yurko is an incoming statistics Ph.D. student at Carnegie Mellon University. He received his B.S. in statistics at Carnegie Mellon in December 2015. At CMU he co-founded with Maksim Horowitz the Tartan Sports Analytics Club. Ron previously worked as a baseball operations data and analytics intern for the Pittsburgh Pirates during the 2014 season, as well as a quantitative analyst in the financial services industry.
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Watch a video of Ron's GLASC presentation
Listen to a podcast interview with Ron and GLASC director Scott Tappa
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