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 |
|---|---|---|---|---|
| 0.10-0.20 | 7 | 15% | 0% | 14.9% |
| 0.20-0.30 | 6 | 26% | 0% | 25.7% |
| 0.30-0.40 | 7 | 35% | 0% | 34.6% |
Skill measures calibration quality (0-100). Variance measures return volatility (0-100, higher = more volatile).
On-chain verification: wallet age 7 days, 2500 txs, provenance grade C. Bot score: 10/100, wash trading score: 50/100.
2000 total trades across 958 markets.
20 bets on resolved markets available for calibration scoring.
Calibration error: 25.0% — needs improvement.
Skill: 30/100 (calibration quality). Variance: 13/100 (higher = more volatile returns).
Brier Skill Score: 71.8% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.0695 RES=0.0000 UNC=0.0000.
Log loss: 0.2951 (skill: -3631.6% vs naive). Lower log loss = better calibration on rare events.
Timeliness: avg entry 0.8 days before resolution, 0% early mover.
Below average. The data shows poor calibration, thin evidence, or both. When this trader expresses high confidence, events don't happen at the rate they imply.
Confidence: D/44 ± 15 (low confidence, 20 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.