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% | 545 | 45.3% | 41.8% | -3.4pp | 0.246 |
| 50-55% | 1215 | 52.2% | 50.8% | -1.5pp | 0.250 |
| 55-60% | 748 | 57.2% | 54.5% | -2.6pp | 0.249 |
| 60-65% | 687 | 61.4% | 48.2% | -13.3pp | 0.266 |
| 65-70% | 147 | 66.9% | 53.7% | -13.1pp | 0.266 |
| 70-75% | 1 | 72.2% | 100.0% | +27.8pp | 0.078 |
| 75-80% | 1 | 76.5% | 100.0% | +23.5pp | 0.055 |
| 80-90% | 9 | 84.0% | 88.9% | +4.8pp | 0.100 |