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 | 1 | 2% | 0% | 1.8% |
| 0.10-0.20 | 1 | 17% | 0% | 17.1% |
| 0.30-0.40 | 2 | 37% | 0% | 36.9% |
| 0.40-0.50 | 4 | 45% | 0% | 44.7% |
| 0.50-0.60 | 4 | 54% | 0% | 54.0% |
| 0.60-0.70 | 4 | 64% | 0% | 64.0% |
| 0.70-0.80 | 7 | 75% | 0% | 74.7% |
| 0.80-0.90 | 6 | 86% | 0% | 85.9% |
| 0.90-1.00 | 4 | 95% | 0% | 94.7% |
On-chain verification: wallet age 3 days, 2037 txs, provenance grade D. Bot score: 0/100, wash trading score: 80/100.
1396 total trades across 263 markets.
33 bets on resolved markets available for calibration scoring.
Calibration error: 65.5% — needs improvement.
Skill: 0/100 (calibration quality). Variance: 19/100 (higher = more volatile returns).
Brier Skill Score: -91.9% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.4793 RES=0.0000 UNC=0.0000.
Log loss: 1.3477 (skill: -16943.5% vs naive). Lower log loss = better calibration on rare events.
Timeliness: avg entry 2.5 days before resolution, 0% early mover.
No demonstrated forecasting skill. This trader performs at or below random chance based on available data.
Confidence: F/33 ± 15 (low confidence, 33 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.