Q beats Polymarket on 59.0% of markets.
Q beats a market when its forecasts have a lower average Brier score than Polymarket’s prices at the same times.
Resolved Polymarket markets · Last 60 days · Updated October 4, 2026
All Polymarket markets
Every covered, resolved market. Each market counts once.
- Markets Q beats
- 59.0%1,386 of 2,351 markets
- Q average Brier
- 0.1588Lower is better
- Polymarket average Brier
- 0.1615Prices at forecast time
16,526 forecasts
Geopolitics and global elections
Markets tagged geopolitics or global elections.
- Markets Q beats
- 50.7%154 of 304 markets
- Q average Brier
- 0.1186Lower is better
- Polymarket average Brier
- 0.1181Prices at forecast time
2,574 forecasts
Everything else
All covered, resolved Polymarket markets outside geopolitics and global elections.
- Markets Q beats
- 60.2%1,232 of 2,047 markets
- Q average Brier
- 0.1648Lower is better
- Polymarket average Brier
- 0.1680Prices at forecast time
13,952 forecasts
Largest topics by market count
- Equities 1,025
- Sports 365
- Culture 220
A market can appear in more than one topic.
How we measure accuracy
Brier scores measure how close a forecast probability is to the outcome. Lower is better. We compare Q with Polymarket’s price recorded at the time of each forecast.
We average the forecast scores within each market, then weight every market equally. Q beats a market when its average score is lower. Ties stay in the total but do not count as wins.
The percentage shows how often Q has the better score. Average Brier shows the size of the errors, so a small win and a large miss affect the two measures differently.
Scoring details
Each Brier score is the squared difference between the forecast probability and the outcome, with YES scored as 1 and NO as 0. We include forecasts made in the last 60 days on markets marked closed or resolved, with a final YES price above 99% or below 1%. Open markets and other venues are excluded.
One row per forecast, with Q’s probability, Polymarket’s price, and the outcome.
Q turns any question into a calibrated probability.
- 01Classify the questionResolution rule, horizon, and question type.
- 02Map the landscapeActors, assets, linked markets, and related questions.
- 03Research the evidenceCheck the sources behind each claim.
- 04Build scenariosBase rates, pathways, dependencies, and disconfirming evidence.
- 05Produce the forecastA calibrated probability with uncertainty and cited analysis.
Signal selection
Q generates many forecasts. The best ones become Signals. A forecast becomes a Signal when its market resolves within 7 days, the side Q favors costs under 65and the gap to the market clears its category's minimum, 510 for events and 15 for commodities. Each event gets one Signal, held to resolution.
- 500forecasts / day
- 7 daysor less to resolution
- 65¢ceiling on Q's side
- 5–15 ptsminimum gap by category
Q gets better over time.
Score each outcome
Compare Q and the forecast-time market price with the resolved result.
Diagnose the error
Trace the evidence, expert weights, and missing inputs behind the miss.
Feed the next model
Turn repeatable findings into fine-tuning and data changes.