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 | 78 | 5% | 5% | 0.6% |
| 0.10-0.20 | 38 | 16% | 5% | 10.4% |
| 0.20-0.30 | 30 | 25% | 0% | 25.1% |
| 0.30-0.40 | 16 | 35% | 0% | 34.7% |
| 0.40-0.50 | 10 | 47% | 0% | 47.1% |
| 0.50-0.60 | 8 | 55% | 0% | 55.4% |
| 0.60-0.70 | 10 | 66% | 0% | 65.7% |
| 0.70-0.80 | 10 | 76% | 0% | 75.8% |
| 0.80-0.90 | 32 | 85% | 13% | 72.4% |
| 0.90-1.00 | 46 | 96% | 17% | 78.4% |
Skill measures calibration quality (0-100). Variance measures return volatility (0-100, higher = more volatile).
On-chain verification: wallet age 655 days, 2945 txs, provenance grade A. Bot score: 10/100, wash trading score: 20/100.
2000 total trades across 71 markets.
278 bets on resolved markets available for calibration scoring.
Calibration error: 36.0% — needs improvement.
Skill: 17/100 (calibration quality). Variance: 80/100 (higher = more volatile returns).
Brier Skill Score: -377.5% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.2302 RES=0.0037 UNC=0.0606.
Log loss: 0.9583 (skill: -299.6% 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/57 ± 3 (high confidence, 278 resolved bets). This score is highly reliable — enough resolved bets to be confident.
Methodology: Brier Score Decomposition (Murphy 1973), Log Loss, On-Chain USDC Verification. Same approach used by IARPA to identify superforecasters.