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 | 312 | 5% | 0% | 4.6% |
| 0.10-0.20 | 138 | 15% | 0% | 14.6% |
| 0.20-0.30 | 50 | 24% | 0% | 24.2% |
| 0.30-0.40 | 16 | 32% | 0% | 32.4% |
| 0.40-0.50 | 12 | 45% | 0% | 45.4% |
| 0.50-0.60 | 6 | 53% | 0% | 52.6% |
| 0.60-0.70 | 18 | 65% | 0% | 64.9% |
| 0.70-0.80 | 42 | 75% | 0% | 75.4% |
| 0.80-0.90 | 104 | 85% | 0% | 85.1% |
| 0.90-1.00 | 302 | 96% | 0% | 96.1% |
Skill measures calibration quality (0-100). Variance measures return volatility (0-100, higher = more volatile).
On-chain verification: wallet age 91 days, 2000 txs, provenance grade C. Bot score: 0/100, wash trading score: 0/100.
Polymarket on-chain coverage: $966 in / $0 out across 39 withdrawal tx since 2026-04-01.
3100 total trades across 144 markets.
1000 bets on resolved markets available for calibration scoring.
Calibration error: 48.3% — needs improvement.
Skill: 2/100 (calibration quality). Variance: 19/100 (higher = more volatile returns).
Brier Skill Score: -59.6% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.3982 RES=0.0000 UNC=0.0000.
Log loss: 1.4164 (skill: -17813.3% 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/34 [CI95: F→D, 33-35] (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.