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 |
|---|---|---|---|---|
| 0.30-0.40 | 4 | 36% | 0% | 35.5% |
| 0.40-0.50 | 7 | 43% | 0% | 43.1% |
| 0.50-0.60 | 6 | 54% | 0% | 54.3% |
| 0.60-0.70 | 7 | 65% | 0% | 64.8% |
| 0.70-0.80 | 4 | 74% | 0% | 74.3% |
| 0.80-0.90 | 1 | 86% | 0% | 86.0% |
On-chain verification: wallet age 114 days, 1103 txs, provenance grade C. Bot score: 0/100, wash trading score: 0/100.
859 total trades across 492 markets.
29 bets on resolved markets available for calibration scoring.
Calibration error: 55.4% — needs improvement.
Skill: 0/100 (calibration quality). Variance: 13/100 (higher = more volatile returns).
Brier Skill Score: -30.7% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.3261 RES=0.0000 UNC=0.0000.
Log loss: 0.8676 (skill: -10872.3% vs naive). Lower log loss = better calibration on rare events.
Timeliness: avg entry 75.7 days before resolution, 100% early mover.
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/41 ± 15 (low confidence, 29 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.