When this trader buys at $0.70, they imply 70% probability. Perfect calibration = the event happens 70% of the time.
| Bucket | Bets | Expected | Actual | Error |
|---|---|---|---|---|
| 0.00-0.10 | 39 | 1% | 38% | 37.5% |
| 0.90-1.00 | 6 | 99% | 100% | 1.0% |
Skill measures calibration quality (0-100). Variance measures return volatility (0-100, higher = more volatile).
On-chain verification: wallet age 34 days, 2103 txs, provenance grade B. Bot score: 0/100, wash trading score: 0/100.
48 total trades across 48 markets.
45 bets on resolved markets available for calibration scoring.
Calibration error: 32.6% — needs improvement.
Skill: 28/100 (calibration quality). Variance: 19/100 (higher = more volatile returns).
Brier Skill Score: -31.3% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.1216 RES=0.0438 UNC=0.2489.
Log loss: 1.5418 (skill: -123.1% vs naive). Lower log loss = better calibration on rare events.
Timeliness: avg entry 7.8 days before resolution, 8% early mover.
No demonstrated forecasting skill. This trader performs at or below random chance based on available data.
Confidence: F/1 ± 15 (low confidence, 45 resolved bets). Low confidence — take this score with a grain of salt until more markets resolve.
Methodology: Brier Score Decomposition (Murphy 1973), Log Loss, On-Chain USDC Verification. Same approach used by IARPA to identify superforecasters.