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 | 34 | 3% | 47% | 44.1% |
| 0.10-0.20 | 16 | 15% | 50% | 34.7% |
| 0.20-0.30 | 22 | 25% | 36% | 11.7% |
| 0.30-0.40 | 16 | 35% | 75% | 39.6% |
| 0.40-0.50 | 24 | 46% | 50% | 4.2% |
| 0.50-0.60 | 28 | 57% | 43% | 13.8% |
| 0.60-0.70 | 20 | 65% | 80% | 15.4% |
| 0.70-0.80 | 14 | 76% | 29% | 47.1% |
| 0.80-0.90 | 18 | 85% | 56% | 29.2% |
| 0.90-1.00 | 20 | 95% | 40% | 54.8% |
Skill measures calibration quality (0-100). Variance measures return volatility (0-100, higher = more volatile).
On-chain verification: wallet age 26 days, 2620 txs, provenance grade C. Bot score: 0/100, wash trading score: 50/100.
2000 total trades across 150 markets.
212 bets on resolved markets available for calibration scoring.
Calibration error: 28.4% — needs improvement.
Skill: 29/100 (calibration quality). Variance: 100/100 (higher = more volatile returns).
Brier Skill Score: -37.9% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.1087 RES=0.0202 UNC=0.2500.
Log loss: 1.0969 (skill: -58.3% 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/50 ± 3 (high confidence, 212 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.