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 | 5 | 7% | 0% | 7.3% |
| 0.10-0.20 | 4 | 17% | 0% | 17.1% |
| 0.20-0.30 | 5 | 27% | 0% | 27.1% |
| 0.30-0.40 | 8 | 33% | 0% | 33.1% |
| 0.40-0.50 | 13 | 45% | 8% | 37.8% |
| 0.50-0.60 | 31 | 54% | 3% | 51.2% |
| 0.60-0.70 | 31 | 65% | 3% | 61.8% |
| 0.70-0.80 | 38 | 75% | 3% | 72.7% |
| 0.80-0.90 | 44 | 86% | 2% | 83.9% |
| 0.90-1.00 | 159 | 96% | 1% | 94.5% |
On-chain verification: wallet age 1 days, 2234 txs, provenance grade C. Bot score: 60/100, wash trading score: 80/100.
2275 total trades across 347 markets.
338 bets on resolved markets available for calibration scoring.
Calibration error: 76.8% — needs improvement.
Skill: 0/100 (calibration quality). Variance: 30/100 (higher = more volatile returns).
Brier Skill Score: -3158.0% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.6396 RES=0.0002 UNC=0.0203.
Log loss: 2.2032 (skill: -2085.9% 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/42 ± 3 (high confidence, 338 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.