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=mlb
| Predicted-prob bucket | N | Mean predicted | Actual win rate | Gap (actual − predicted) | Brier |
|---|---|---|---|---|---|
| <50% | 594 | 45.5% | 40.9% | -4.6pp | 0.244 |
| 50-55% | 1340 | 52.2% | 48.6% | -3.6pp | 0.251 |
| 55-60% | 751 | 57.4% | 55.3% | -2.1pp | 0.248 |
| 60-65% | 674 | 61.6% | 49.9% | -11.7pp | 0.263 |
| 65-70% | 198 | 66.8% | 58.1% | -8.8pp | 0.252 |
| 70-75% | 14 | 71.7% | 78.6% | +6.8pp | 0.170 |
| 75-80% | 4 | 76.3% | 75.0% | -1.3pp | 0.194 |
| 80-90% | 6 | 84.8% | 100.0% | +15.2pp | 0.023 |
| 90%+ | 1 | 90.9% | 100.0% | +9.1pp | 0.008 |