{"asOf":"2026-10-15","forward":{"generatedAt":"2026-10-15T13:57:36.342327+00:00","capturedTotal":118914,"maturedMarkets":33213,"baseRateYes":0.1215,"design":"Forecasts captured while the market was OPEN (contamination-proof, time is the air-gap), graded as reality resolved them. The living benchmark: it grows and re-grades every time the bus refreshes; a young log grades few until its markets mature.","forecasters":{"crowd":{"n":33213,"nMarkets":33213,"brier":0.0503,"brierCI95":[0.0488,0.0518],"baseRateBrier":0.108,"skillVsBaseRate":0.534,"logLoss":0.1652,"reliability":[{"bin":"0.0-0.1","n":23170,"meanPredicted":0.0144,"empiricalFrequency":0.0082},{"bin":"0.1-0.2","n":2470,"meanPredicted":0.1434,"empiricalFrequency":0.0972},{"bin":"0.2-0.3","n":1789,"meanPredicted":0.2454,"empiricalFrequency":0.1778},{"bin":"0.3-0.4","n":1325,"meanPredicted":0.3468,"empiricalFrequency":0.2951},{"bin":"0.4-0.5","n":1201,"meanPredicted":0.4486,"empiricalFrequency":0.3614},{"bin":"0.5-0.6","n":795,"meanPredicted":0.5374,"empiricalFrequency":0.4843},{"bin":"0.6-0.7","n":470,"meanPredicted":0.644,"empiricalFrequency":0.634},{"bin":"0.7-0.8","n":344,"meanPredicted":0.7468,"empiricalFrequency":0.7122},{"bin":"0.8-0.9","n":319,"meanPredicted":0.8484,"empiricalFrequency":0.8589},{"bin":"0.9-1.0","n":1330,"meanPredicted":0.9688,"empiricalFrequency":0.991}]}}},"retrospective":{"generatedAt":"2026-06-23T06:10:56.693233+00:00","windowDays":45,"horizonHours":72,"resolvedMarkets":34325,"trainMarkets":17162,"testMarkets":17163,"design":"Markets split train/test by resolution date. The deterministic engine is FIT on train (OLS residual correction on the crowd) and the leaderboard is the disjoint TEST split (clean OOS); the base-rate null is measured on train, applied to test. Every forecaster sees only snapshots with ts<=as_of (contamination guard). Reproducible, offline, no LLM in any forecaster here.","forecasters":{"base_rate":{"n":17163,"nMarkets":17163,"brier":0.1063,"brierCI95":[0.103,0.1097],"baseRateBrier":0.1063,"skillVsBaseRate":0,"logLoss":0.3699,"reliability":[{"bin":"0.1-0.2","n":17163,"meanPredicted":0.1453,"empiricalFrequency":0.1201}]},"crowd":{"n":4069,"nMarkets":4069,"brier":0.0705,"brierCI95":[0.0658,0.0756],"baseRateBrier":0.1586,"skillVsBaseRate":0.5555,"logLoss":0.2339,"reliability":[{"bin":"0.0-0.1","n":2287,"meanPredicted":0.0206,"empiricalFrequency":0.0131},{"bin":"0.1-0.2","n":325,"meanPredicted":0.1432,"empiricalFrequency":0.12},{"bin":"0.2-0.3","n":272,"meanPredicted":0.2495,"empiricalFrequency":0.1654},{"bin":"0.3-0.4","n":207,"meanPredicted":0.3474,"empiricalFrequency":0.1836},{"bin":"0.4-0.5","n":242,"meanPredicted":0.4501,"empiricalFrequency":0.2025},{"bin":"0.5-0.6","n":107,"meanPredicted":0.5369,"empiricalFrequency":0.4206},{"bin":"0.6-0.7","n":68,"meanPredicted":0.6531,"empiricalFrequency":0.6765},{"bin":"0.7-0.8","n":67,"meanPredicted":0.747,"empiricalFrequency":0.6269},{"bin":"0.8-0.9","n":70,"meanPredicted":0.8475,"empiricalFrequency":0.7857},{"bin":"0.9-1.0","n":424,"meanPredicted":0.9719,"empiricalFrequency":0.9434}]}}},"whatThisCovers":"This dataset grades the market sensor we cite, and only that: `crowd` is the prediction-market price, `base_rate` is the naive null it is scored against. No forecaster of ours is published here, in either slice. We maintain a source-traced record of the entities and events in a customer's domain and sell that maintained state; prediction-market prices are one source we cite and grade for accuracy; we serve current state, not forecasts. Each price was logged while its market was open and graded when it matured, so the grade cannot be back-filled. The `design` notes describe the whole internal benchmark, graders we run included; the rows above are what is served."}