
Predicting the Home Field Advantage in the NFL
Presenter(s)
Samuel Limbert
Files
Description
Home-field advantage has always been an important talking point used to predict the outcome of NFL games. This project aims to develop a predictive model for forecasting NFL home team victories using different machine learning techniques. By analyzing historical game data, team performance metrics, player statistics, weather conditions, and betting odds, this project seeks to identify the key factors that contribute to predicting NFL games. Various machine learning algorithms including, logistic regression, quadratic discriminant analysis, and linear discriminant analysis are utilized to determine the most accurate predictive approach.
Publication Date
4-23-2025
Project Designation
Capstone Project
Primary Advisor
Gayan J. Warahena Liyanage
Primary Advisor's Department
Mathematics
Keywords
Stander Symposium, College of Arts and Sciences
Institutional Learning Goals
Practical Wisdom
Recommended Citation
"Predicting the Home Field Advantage in the NFL" (2025). Stander Symposium Projects. 3826.
https://ecommons.udayton.edu/stander_posters/3826

Comments
9:00-10:15, Kennedy Union Ballroom