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 | 102 | 2% | 20% | 17.3% |
| 0.10-0.20 | 2 | 18% | 0% | 18.1% |
| 0.20-0.30 | 4 | 22% | 0% | 21.8% |
| 0.30-0.40 | 2 | 36% | 100% | 63.7% |
| 0.60-0.70 | 2 | 63% | 0% | 63.3% |
| 0.70-0.80 | 2 | 74% | 0% | 74.0% |
| 0.80-0.90 | 6 | 82% | 33% | 49.1% |
| 0.90-1.00 | 28 | 97% | 21% | 75.8% |
Skill measures calibration quality (0-100). Variance measures return volatility (0-100, higher = more volatile).
On-chain verification: wallet age 58 days, 2086 txs, provenance grade B. Bot score: 10/100, wash trading score: 0/100.
Polymarket on-chain coverage: $0 in / $0 out across 0 withdrawal tx since never.
3100 total trades across 114 markets.
148 bets on resolved markets available for calibration scoring.
Calibration error: 31.8% — needs improvement.
Skill: 24/100 (calibration quality). Variance: 53/100 (higher = more volatile returns).
Brier Skill Score: -91.1% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.1590 RES=0.0121 UNC=0.1616.
Log loss: 1.2021 (skill: -138.5% vs naive). Lower log loss = better calibration on rare events.
No demonstrated forecasting skill. This trader performs at or below random chance based on available data.
Confidence: F/25 [CI95: F→F, 21-28] (148 resolved bets). Moderate confidence — score may shift as more markets resolve.
Methodology: Brier Score Decomposition (Murphy 1973), Log Loss, On-Chain USDC Verification. Same approach used by IARPA to identify superforecasters.