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 | 4 | 7% | 100% | 92.6% |
| 0.10-0.20 | 2 | 19% | 100% | 81.2% |
| 0.20-0.30 | 6 | 27% | 67% | 39.3% |
| 0.30-0.40 | 6 | 35% | 0% | 34.7% |
| 0.40-0.50 | 2 | 48% | 100% | 52.0% |
| 0.50-0.60 | 2 | 51% | 0% | 51.0% |
| 0.60-0.70 | 4 | 67% | 0% | 66.5% |
| 0.70-0.80 | 6 | 72% | 33% | 39.2% |
| 0.80-0.90 | 6 | 84% | 67% | 17.0% |
| 0.90-1.00 | 2 | 92% | 0% | 91.9% |
Skill measures calibration quality (0-100). Variance measures return volatility (0-100, higher = more volatile).
On-chain verification: wallet age 2 days, 2937 txs, provenance grade C. Bot score: 40/100, wash trading score: 20/100.
2000 total trades across 312 markets.
40 bets on resolved markets available for calibration scoring.
Calibration error: 49.2% — needs improvement.
Skill: 25/100 (calibration quality). Variance: 57/100 (higher = more volatile returns).
Brier Skill Score: -61.0% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.3001 RES=0.1475 UNC=0.2475.
Log loss: 1.1098 (skill: -61.3% 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/24 ± 15 (low confidence, 40 resolved bets). Low confidence — take this score with a grain of salt until more markets resolve.
Methodology: Brier Score Decomposition (Murphy 1973), Log Loss, On-Chain USDC Verification. Same approach used by IARPA to identify superforecasters.