Machine learning that predicts the outcomes of any MLB game. Data are from 2014 - 2023 seasons. Current accuracy on test data:
- Teams that I have a >70% prediction probability: 'KCR', 'ATL'
- Regression DNN has a validation RMSE of 1.15 runs
python mlb_ml_classify_deep_learn.py tune or python mlb_ml_classify_deep_learn.py notune
#check accuracy of running averages
python mlb_ml_classify_deep_learn.py test
Correlated features >= 0.90: ['RBI', 'onbase_plus_slugging', 'ER', 'strikes_total']
Number of samples: 62718
### Current prediction accuracies - DNN
Validation Accuracy: 0.985
Train Accuracy: 0.986
Validation Loss: 0.03
Train Loss: 0.037
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.