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Predicting College Basketball Games with Machine Learning

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College Basketball Game Predictions

Machine learning that predicts the outcome of any Division I college basketball game. Data are from 2010 - 2024 seasons.

Data are from SportsReference.com

Usage

python cbb_classification.py tune or python cbb_classification.py notune
Removed features (>=0.9 correlation): ['fta', 'fta_per_fga_pct', 'fg3a_per_fga_pct', 'ts_pct', 'stl_pct', 'blk_pct', 'efg_pct', 'tov_pct', 'orb_pct', 'ft_rate']
dataset shape: (27973 samples, 55 features)

### Current prediction accuracies - XGBoost
# After 5 fold cross validation and pre-processing
Current XGBoost Classifier - best params:  {'colsample_bytree': 1.0, 'gamma': 0, 'learning_rate': 0.1, 'max_depth': 2, 'min_child_weight': 1, 'n_estimators': 200, 'reg_alpha': 0.01, 'reg_lambda': 0.01, 'scale_pos_weight': 1, 'subsample': 1.0}


#Classification - XGBoost
Confusion Matrix:[[1316   46]
                  [  31 1404]]
Model accuracy on test data: 0.9688952449052556

#Classificatino - DNN Keras
Final model test loss 0.07359004765748978 and accuracy 0.9760457873344421

Correlation Matrix

Feature Importances Classification

XGBoost Deep Neural Network

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.