Description
In this study, models will be introduced which are developed from historical UFC data and aim to predict the fight outcomes between mixed martial arts fighters within the UFC. The paper will explore multivariate linear probability regression analysis using variables which were provided and developed from a large dataset to effectively predict the probability of a fighter winning a given fight. It will analyze several multivariate regression models and compare, internally, the accuracy of each model and account for limitations within the models. Then, the model’s efficacy will be tested by recent UFC fights and adjusted to find a more accurate equation that maximizes profit in sports betting using implied probability from betting odds and comparing them to the model’s predicted probabilities.
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Details
Title
- ANALYSIS OF FIGHT OUTCOMES IN THE UFC AND THE EFFICACY OF PREDICTING FIGHT OUTCOMES ESPECIALLY IN RELATION TO SPORTS BETTING
Contributors
- Tufte, Nicholas (Author)
- Hill, Alexander (Thesis director)
- Broatch, Jennifer (Committee member)
- Barrett, The Honors College (Contributor)
- School of Mathematical and Natural Sciences (Contributor)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2022-12
Resource Type
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