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The Brier score measures how good probability forecasts were: the average of (forecast − outcome)², where the outcome is 1 if it happened and 0 if not. 0 is perfect, 0.25 is what always saying 50% scores, 1 is the worst. Example: forecasts of 90%, 70%, 60%, 20% and 80% on events that went yes, yes, no, no, yes score 0.108 — a 57% improvement on coin-flipping.
Calibration is the table under the score: in each band your average forecast should roughly match how often the events happened. With a few dozen forecasts per band the gaps become meaningful. The same check for Polymarket itself, on about 2,000 resolved markets, is in the Polymarket accuracy study.
Log loss punishes confident misses much harder: a 99% forecast that fails costs 4.6, while a 60% miss costs 0.9. Use both — Brier for overall accuracy, log loss to catch overconfidence.
Write down your probability and the Polymarket price at the same moment, then score both once the markets resolve. If your Brier score beats the market's across a few dozen questions, your forecasts carry information the market lacked. Current prices are on Polymarket odds today; the EV calculator shows what an edge is worth.
Put real prices into the calculator: every page below shows current odds, 24-hour moves and the market rules.
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Lower is better. Always forecasting 50% scores 0.25, so anything clearly below that shows skill; strong forecasters on hard questions often land between 0.10 and 0.20.
For each forecast, subtract the outcome (1 if it happened, 0 if not) from the probability and square it; the Brier score is the average over all forecasts.
Group them into bands (0–10%, 10–20% and so on) and compare the average forecast in each band with the share of events that happened; the calculator builds that table under the score. Polymarket's own calibration is in the accuracy study.
Both reward accurate probabilities. Log loss (−ln of the probability you gave the actual outcome) punishes confident misses far more heavily than the Brier score does.
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