For every bucket of predicted probability, what did the model actually hit? A well-calibrated model has actual win rate ≈ predicted prob. A negative gap means the model is overconfident in that bucket (dangerous); positive gap means it's underpredicting (safe). Rows turn red when |gap| > 5pp AND N ≥ 10.
Combined "all sports" is rarely meaningful — sports differ in market efficiency, signal availability, and base rates. Use the chips to drill into a single sport. N<50 (red) means the calibration is brittle; N≥200 (green) is trustworthy.
Filter: window=90d · sport=nhl
| Predicted-prob bucket | N | Mean predicted | Actual win rate | Gap (actual − predicted) | Brier |
|---|---|---|---|---|---|
| <50% | 61 | 40.7% | 36.1% | -4.7pp | 0.233 |
| 50-55% | 50 | 52.2% | 52.0% | -0.2pp | 0.250 |
| 55-60% | 23 | 57.4% | 39.1% | -18.2pp | 0.268 |
| 60-65% | 11 | 62.4% | 54.5% | -7.8pp | 0.249 |
| 65-70% | 13 | 66.5% | 84.6% | +18.1pp | 0.163 |
| 70-75% | 3 | 72.0% | 100.0% | +28.0pp | 0.079 |
| 75-80% | 1 | 75.9% | 0.0% | -75.9pp | 0.577 |