Developing analytical tools to impact U.Va. football performance

Data analytics has permeated the sports world, but the funds needed to employ data scientists dedicated exclusively to programs at the collegiate level are hard to come by. As a result, Division I football programs are currently not using data analytics and technology to their full potential. This project aims to use technology and data analytics to enhance the performance of the University of Virginia Football program and serves as a continuation of the efforts of previous U.Va. Systems Engineers to bring U.Va.'s program to the technological forefront of college programs. This paper outlines ongoing efforts involving supplementation to analyses currently being done by the program while also introducing new methods to aid the U.Va. coaching staff. Building upon the previously identified “Three Pillars of Data Analytics” for U.Va. Football, this multi-faceted project includes an analysis of how players' practice performance corresponds to in-game performance, the validation of a previously built 4th down decision tool delivered last year as a means to aid in difficult in-game decision making, and the development of an automated tool to classify offensive play formations using computer vision. These efforts aim to help the coaching staff optimize practice schedules, provide them with data-driven decision-making aids to be used in-game, and increase opponent scouting capabilities while also saving the labor required to do so.