Presenter(s)

    Samuel Limbert

    Comments

    9:00-10:15, Kennedy Union Ballroom

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    Download Project (274 KB)

    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

    Predicting the Home Field Advantage in the NFL

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