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 | 110 | 5% | 0% | 4.7% |
| 0.10-0.20 | 128 | 15% | 0% | 14.6% |
| 0.20-0.30 | 82 | 25% | 0% | 24.5% |
| 0.30-0.40 | 76 | 34% | 0% | 34.2% |
| 0.40-0.50 | 64 | 44% | 3% | 41.0% |
| 0.50-0.60 | 68 | 56% | 0% | 55.8% |
| 0.60-0.70 | 48 | 65% | 0% | 64.7% |
| 0.70-0.80 | 102 | 77% | 0% | 76.5% |
| 0.80-0.90 | 182 | 85% | 0% | 84.8% |
| 0.90-1.00 | 140 | 95% | 0% | 95.3% |
On-chain verification: wallet age 168 days, 1000 txs, provenance grade C. Bot score: 0/100, wash trading score: 0/100.
Polymarket on-chain coverage: $0 in / $0 out across 0 withdrawal tx since never.
5000 total trades across 288 markets.
1000 bets on resolved markets available for calibration scoring.
Calibration error: 53.1% — needs improvement.
Skill: 0/100 (calibration quality). Variance: 100/100 (higher = more volatile returns).
Brier Skill Score: -19414.1% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.3867 RES=0.0001 UNC=0.0020.
Log loss: 1.1823 (skill: -8094.8% 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/32 [CI95: F→F, 31-33] (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.