Model Calibration

We publish our calibration. For every market family, this is what the model predicted versus what actually happened across every settled bet — straight from the results ledger, no synthetic data. A positive gap means the model was overconfident. Families proven to lose money are curated out of the boards entirely; well-sampled families have their displayed probabilities calibrated toward the realized rate. This is the engine behind the High Confidence Board.

Curated-out families split two ways: overconfident — the model's probability itself is broken (realized far below predicted), so the edge is fake at any price; and priced-short — the probability is roughly right but the bet loses at fair odds (it could still be +EV at a soft book line). The distinction is why we curate by ROI, not hit rate.