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Jimmy's and Joes vs X's and O's: Predicting results in college sports analyzing talent accumulation and on-field success

Reginald Bain, Tung Nguyen, Reid Harris

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Recent legislation has completely changed the landscape of college sports, a multi-billion dollar business with deep roots in American sports culture. With the recent legalization of sports betting in many states and the SCOTUS O’Bannon ruling that allows athletes to be paid through so-called “Name-Image-Likeness (NIL)” deals, evaluating talent and projecting results in college sports, especially for the purpose of sports betting, is an increasingly interesting problem. We are interested in building a model to project on-field results in college football using a variety of features including an assessment of the talent level of teams as well as recent performance statistics. Our data will be scraped from various sources including the College Football Database, 247 Sports, On3, and ESPN.

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