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=ncaab
| Predicted-prob bucket | N | Mean predicted | Actual win rate | Gap (actual − predicted) | Brier |
|---|---|---|---|---|---|
| 50-55% | 3 | 52.8% | 0.0% | -52.8pp | 0.279 |
| 55-60% | 4 | 57.6% | 25.0% | -32.6pp | 0.305 |
| 60-65% | 1 | 60.7% | 100.0% | +39.3pp | 0.155 |
| 65-70% | 2 | 68.6% | 100.0% | +31.4pp | 0.099 |
| 70-75% | 1 | 74.6% | 100.0% | +25.4pp | 0.064 |