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 |
|---|---|---|---|---|
| 0.30-0.40 | 4 | 39% | 0% | 39.0% |
| 0.40-0.50 | 20 | 42% | 50% | 8.4% |
| 0.50-0.60 | 6 | 58% | 0% | 58.3% |
Skill measures calibration quality (0-100). Variance measures return volatility (0-100, higher = more volatile).
On-chain verification: wallet age 58 days, 2282 txs, provenance grade B. Bot score: 40/100, wash trading score: 50/100.
841 total trades across 803 markets.
30 bets on resolved markets available for calibration scoring.
Calibration error: 22.5% — needs improvement.
Skill: 42/100 (calibration quality). Variance: 40/100 (higher = more volatile returns).
Brier Skill Score: -16.4% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.0930 RES=0.0556 UNC=0.2222.
Log loss: 0.7105 (skill: -11.6% vs naive). Lower log loss = better calibration on rare events.
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/40 ± 15 (low confidence, 30 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.