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 | 20 | 6% | 0% | 5.8% |
| 0.10-0.20 | 110 | 16% | 0% | 16.3% |
| 0.20-0.30 | 228 | 25% | 0% | 24.9% |
| 0.30-0.40 | 88 | 34% | 0% | 34.4% |
| 0.40-0.50 | 54 | 44% | 0% | 43.8% |
| 0.50-0.60 | 56 | 55% | 0% | 54.7% |
| 0.60-0.70 | 118 | 65% | 0% | 65.4% |
| 0.70-0.80 | 194 | 75% | 1% | 74.2% |
| 0.80-0.90 | 114 | 84% | 0% | 83.7% |
| 0.90-1.00 | 18 | 95% | 0% | 94.6% |
Skill measures calibration quality (0-100). Variance measures return volatility (0-100, higher = more volatile).
On-chain verification: wallet age 33 days, 2000 txs, provenance grade D. Bot score: 0/100, wash trading score: 0/100.
Polymarket on-chain coverage: $0 in / $0 out across 0 withdrawal tx since never.
3100 total trades across 333 markets.
1000 bets on resolved markets available for calibration scoring.
Calibration error: 49.4% — needs improvement.
Skill: 1/100 (calibration quality). Variance: 27/100 (higher = more volatile returns).
Brier Skill Score: -15463.3% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.3080 RES=0.0000 UNC=0.0020.
Log loss: 0.8596 (skill: -5857.9% vs naive). Lower log loss = better calibration on rare events.
No demonstrated forecasting skill. This trader performs at or below random chance based on available data.
Confidence: F/24 [CI95: F→F, 23-25] (1000 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.