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 | 66 | 2% | 3% | 0.6% |
| 0.10-0.20 | 6 | 16% | 33% | 17.1% |
| 0.20-0.30 | 2 | 27% | 0% | 27.0% |
| 0.40-0.50 | 2 | 43% | 100% | 57.0% |
Skill measures calibration quality (0-100). Variance measures return volatility (0-100, higher = more volatile).
On-chain verification: wallet age 881 days, 2304 txs, provenance grade A. Bot score: 10/100, wash trading score: 0/100.
2000 total trades across 860 markets.
76 bets on resolved markets available for calibration scoring.
Calibration error: 4.1% — excellent.
Skill: 60/100 (calibration quality). Variance: 74/100 (higher = more volatile returns).
Brier Skill Score: 20.2% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.0128 RES=0.0297 UNC=0.0727.
Log loss: 0.2027 (skill: 26.6% vs naive). Lower log loss = better calibration on rare events.
This trader shows some skill signal, but not enough to clearly distinguish from luck. More data needed.
Confidence: C/64 ± 8 (medium confidence, 76 resolved bets). Moderate confidence — score may shift as more markets resolve.
Methodology: Brier Score Decomposition (Murphy 1973), Log Loss, On-Chain USDC Verification. Same approach used by IARPA to identify superforecasters.