Predicting the Home Field Advantage in the NFL

Authors

Presenter(s)

Samuel Limbert

Comments

9:00-10:15, Kennedy Union Ballroom

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