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 | 556 | 5% | 0% | 4.7% |
| 0.10-0.20 | 8 | 12% | 0% | 12.4% |
| 0.20-0.30 | 6 | 23% | 0% | 23.2% |
| 0.30-0.40 | 4 | 38% | 0% | 37.9% |
| 0.50-0.60 | 2 | 59% | 0% | 59.1% |
| 0.80-0.90 | 6 | 89% | 0% | 88.9% |
| 0.90-1.00 | 418 | 96% | 0% | 95.6% |
Skill measures calibration quality (0-100). Variance measures return volatility (0-100, higher = more volatile).
On-chain verification: wallet age 65 days, 2000 txs, provenance grade C. Bot score: 0/100, wash trading score: 0/100.
Polymarket on-chain coverage: $23,950 in / $0 out across 956 withdrawal tx since 2026-04-13.
3100 total trades across 617 markets.
1000 bets on resolved markets available for calibration scoring.
Calibration error: 43.6% — needs improvement.
Skill: 8/100 (calibration quality). Variance: 14/100 (higher = more volatile returns).
Brier Skill Score: -56.2% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.3901 RES=0.0000 UNC=0.0000.
Log loss: 1.4144 (skill: -17787.8% 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/13 [CI95: F→F, 12-14] (1000 resolved bets). This score is highly reliable — enough resolved bets to be confident.
Methodology: Brier Score Decomposition (Murphy 1973), Log Loss, On-Chain USDC Verification. Same approach used by IARPA to identify superforecasters.