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 |
|---|---|---|---|---|
| 0.10-0.20 | 2 | 14% | 0% | 14.4% |
| 0.20-0.30 | 1 | 23% | 0% | 22.9% |
| 0.30-0.40 | 1 | 39% | 0% | 38.8% |
| 0.40-0.50 | 11 | 47% | 0% | 46.9% |
| 0.50-0.60 | 4 | 56% | 0% | 56.4% |
| 0.60-0.70 | 4 | 65% | 0% | 64.7% |
| 0.70-0.80 | 6 | 73% | 0% | 73.1% |
| 0.80-0.90 | 2 | 82% | 0% | 81.9% |
| 0.90-1.00 | 1 | 98% | 0% | 98.0% |
On-chain verification: wallet age 0 days, 1550 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.
1145 total trades across 32 markets.
32 bets on resolved markets available for calibration scoring.
Calibration error: 56.0% — needs improvement.
Skill: 0/100 (calibration quality). Variance: 16/100 (higher = more volatile returns).
Brier Skill Score: -39.4% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.3478 RES=0.0000 UNC=0.0000.
Log loss: 0.9633 (skill: -12082.2% 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/28 [CI95: F→F, 24-31] (32 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.