Spring 2024 Graduate Student Thesis Defense

Monday, April 1, 2024
2:00 PM - 3:00 PM
WH room 288a

Optimizing Salary Cap Allocation in the NFL

Speaker: Lucas Bukowski

Abstract: Every season, each NFL team must decide how to allocate the funds available to them within the salary cap. The goal of this paper is to use regression techniques to model team success based on team spending, and then use those models to determine optimal spending under the cap. Inefficient spending at one position can leave teams lacking at others, causing a domino effect that can drastically harm a team’s success. This project will look at using beta regression, Poisson regression, and logistic regression to fit predictive models, and then optimize them using the Improved Stochastic Ranking Evolution Strategy (ISRES) and Constrained Optimization By Linear Approximations (COBYLA). These regression techniques and optimization methods used will be introduced and a brief overview given. The optimal spending allocation found from modeling different forms of success in the NFL will then be compared to see which positions are worth spending on to win the most games and provide the highest probability of making the playoffs. Finally, this study will conclude with some discussion of how to interpret the results and potential further research.

Thesis Advisor: Dr. Namyong Lee