BrandoPolistirolo/Tennis-Betting-ML
Machine Learning model(specifically log-regression with stochastic gradient descent) for tennis matches prediction. Achieves accuracy of 66% on approx. 125000 matches
This project helps sports bettors and tennis enthusiasts predict the outcome of professional men's singles tennis matches. By analyzing historical match data, including player statistics and betting odds, it generates a prediction for which player is more likely to win. This tool is designed for individuals who place pre-game bets on tennis matches and want data-driven insights.
No commits in the last 6 months.
Use this if you are interested in predicting the winner of ATP and ITF singles tennis matches to inform your pre-game betting decisions.
Not ideal if you are looking for in-game betting predictions or predictions for doubles matches or other sports.
Stars
48
Forks
11
Language
Python
License
MIT
Category
Last pushed
Feb 18, 2022
Commits (30d)
0
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