A trained ML model that analyzes NBA and MLB games to predict winners. See daily predictions, historical accuracy, and confidence calibration.
Trained on 10+ seasons of historical game data. Uses features like team stats, injuries, rest days, and momentum to understand game outcomes.
Outputs a win probability for each team (0–100%). Higher confidence means stronger prediction strength based on model certainty.
All predictions are logged and compared against actual results. Historical accuracy is tracked and displayed in real-time.
All predictions are generated algorithmically based on historical model training. This site shows what the model predicts for upcoming games and tracks its actual performance over time. Past accuracy is provided for reference, but does not guarantee future results. This is an educational tool for understanding ML prediction models applied to sports.