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 | 142 | 5% | 1% | 4.0% |
| 0.10-0.20 | 175 | 15% | 1% | 14.1% |
| 0.20-0.30 | 109 | 24% | 1% | 23.6% |
| 0.30-0.40 | 48 | 34% | 0% | 33.8% |
| 0.40-0.50 | 15 | 43% | 0% | 43.3% |
| 0.50-0.60 | 7 | 54% | 0% | 53.9% |
| 0.60-0.70 | 2 | 61% | 0% | 61.1% |
| 0.70-0.80 | 1 | 78% | 0% | 77.6% |
Skill measures calibration quality (0-100). Variance measures return volatility (0-100, higher = more volatile).
On-chain verification: wallet age 14 days, 3000 txs, provenance grade B. Bot score: 100/100, wash trading score: 50/100.
Polymarket on-chain coverage: $4,559 in / $0 out across 344 withdrawal tx since 2026-04-22.
3100 total trades across 793 markets.
499 bets on resolved markets available for calibration scoring.
Calibration error: 16.9% — good.
Skill: 40/100 (calibration quality). Variance: 28/100 (higher = more volatile returns).
Brier Skill Score: -550.7% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.0430 RES=0.0000 UNC=0.0080.
Log loss: 0.2267 (skill: -385.8% vs naive). Lower log loss = better calibration on rare events.
Below average. The data shows poor calibration, thin evidence, or both. When this trader expresses high confidence, events don't happen at the rate they imply.
Confidence: D/38 [CI95: D→D, 38-38] (499 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.