How the models think
Our ensemble of machine-learning models blends gradient-boosted trees, neural networks, and Bayesian inference to estimate the true probability of every outcome. Each model is continuously retrained as new results land, so projections sharpen over the course of a season rather than going stale.
- Predictive win probabilities on every money line, spread, and total
- Confidence scoring so you know how strong each signal really is
- Continuous retraining that adapts to roster and form changes
- Backtested against years of closing lines for honest calibration