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 | 140 | 5% | 1% | 4.0% |
| 0.10-0.20 | 178 | 15% | 1% | 13.6% |
| 0.20-0.30 | 106 | 24% | 6% | 18.7% |
| 0.30-0.40 | 36 | 34% | 11% | 23.2% |
| 0.40-0.50 | 18 | 44% | 22% | 22.2% |
| 0.50-0.60 | 8 | 56% | 0% | 56.1% |
| 0.60-0.70 | 36 | 65% | 6% | 59.6% |
| 0.70-0.80 | 62 | 76% | 0% | 75.7% |
| 0.80-0.90 | 136 | 86% | 3% | 82.9% |
| 0.90-1.00 | 266 | 97% | 1% | 95.8% |
Skill measures calibration quality (0-100). Variance measures return volatility (0-100, higher = more volatile).
On-chain verification: wallet age 59 days, 2770 txs, provenance grade C. Bot score: 0/100, wash trading score: 50/100.
Polymarket on-chain coverage: $0 in / $0 out across 0 withdrawal tx since never.
3100 total trades across 282 markets.
986 bets on resolved markets available for calibration scoring.
Calibration error: 50.9% — needs improvement.
Skill: 0/100 (calibration quality). Variance: 35/100 (higher = more volatile returns).
Brier Skill Score: -1572.4% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.4039 RES=0.0013 UNC=0.0257.
Log loss: 1.5200 (skill: -1147.0% 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/30 [CI95: F→F, 29-31] (986 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.