Anticipated Date of Graduation
Spring 2024
Document Type
Thesis
Degree Name
Master of Science in Mathematical Sciences
Department
Mathematical Sciences
First Advisor
Doug Darbro
Abstract
This research investigates the predictive power of the changes in spread, over/under betting lines, and home field advantage in determining whether the favored team in a college football betting market will cover the spread. The study examines three key factors: the change in the betting spread, the change in the over/under line, and the home-field advantage of the favored team. Using a comprehensive dataset of betting data from Draft Kings and Bovada, the study uses logistical regression techniques to analyze the relationship between these variables and the favored team’s performance against the spread. Our findings indicate that fluctuations in the betting spread and over/under lines, combined with the home field status of the favored team, do not provide a statistical significant predictive insights. The results demonstrate that these lines can are not effective when utilized to predict the likelihood of the favored team covering the spread, highlighting efficiencies in the betting market. This research contributes to the understanding of sports betting dynamics and offers practical implications for bettors seeking to improve their wagering strategies through data-driven approaches.
Recommended Citation
Reyes, Ethan and Beal, Justin, "Gridiron Insights: Predicting Gameday Outcomes Through Regression Analysis in College Football" (2024). Master of Science in Mathematics. 95.
https://digitalcommons.shawnee.edu/math_etd/95