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 | 5% | 0% | 4.6% |
| 0.10-0.20 | 3 | 15% | 0% | 15.0% |
| 0.20-0.30 | 1 | 21% | 0% | 21.0% |
| 0.30-0.40 | 2 | 36% | 0% | 36.0% |
| 0.40-0.50 | 5 | 45% | 0% | 45.2% |
| 0.50-0.60 | 3 | 54% | 0% | 54.0% |
| 0.60-0.70 | 1 | 63% | 0% | 63.0% |
| 0.70-0.80 | 1 | 78% | 0% | 78.0% |
| 0.80-0.90 | 1 | 81% | 100% | 19.0% |
Skill measures calibration quality (0-100). Variance measures return volatility (0-100, higher = more volatile).
On-chain verification: wallet age 58 days, 2220 txs, provenance grade B. Bot score: 30/100, wash trading score: 0/100.
2000 total trades across 445 markets.
22 bets on resolved markets available for calibration scoring.
Calibration error: 32.2% — needs improvement.
Skill: 28/100 (calibration quality). Variance: 11/100 (higher = more volatile returns).
Brier Skill Score: -249.4% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.1510 RES=0.0434 UNC=0.0434.
Log loss: 0.4515 (skill: -144.2% vs naive). Lower log loss = better calibration on rare events.
Timeliness: avg entry 39.0 days before resolution, 89% early mover.
No demonstrated forecasting skill. This trader performs at or below random chance based on available data.
Confidence: F/23 ± 15 (low confidence, 22 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.