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Calibration.

How accurate are our forecasts? Every prediction we publish is locked at publish time. We grade ourselves in public.

Time range
| Category
Last update 2026-05-19 11:42:01Z

Reliability curve

Predicted probability vs. realized frequency · decile buckets
n = 412 · 90d · all
100% 0% 50% 0% predicted probability 100% realized frequency n=44 n=89 n=110 n=98 n=71
Realized frequency Perfect calibration 95% confidence interval

Headline numbers

Forecasts tracked412
Brier score0.082
Log loss0.31
Calibration error (avg)±2.1%
Forecast horizon1–42d

By confidence bucket

Each row links to the individual forecasts and their outcomes.

Predicted Realized Delta n
50–59% 53% −0.5 44
60–69% 64% −0.5 89
70–79% 72% −2.5 110
80–89% 87% +2.5 98
90–99% 94% −0.5 71

Per category

Same scoring, sliced.

Export CSV →
Weather n = 284
0.061 Brier
Cal. err ±1.6% · best-calibrated category
Econ n = 84
0.118 Brier
Cal. err ±3.2% · noisier; thin sample at 80–89
Politics n = 44
0.142 Brier
Cal. err ±4.4% · small n; treat with caution

How these numbers are computed

Forecasts are written to validation_cf6 at publish time with a forecast_id, the predicted probability, and the resolving market. Outcomes attach when the market settles. Nothing is retroactively edited.

Read methodology