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 |
|---|---|---|---|---|
| 0.20-0.30 | 1 | 28% | 0% | 27.8% |
| 0.30-0.40 | 5 | 34% | 0% | 34.4% |
| 0.40-0.50 | 18 | 45% | 0% | 45.4% |
| 0.50-0.60 | 8 | 55% | 0% | 54.9% |
| 0.60-0.70 | 5 | 62% | 0% | 62.4% |
| 0.70-0.80 | 2 | 73% | 0% | 73.3% |
Skill measures calibration quality (0-100). Variance measures return volatility (0-100, higher = more volatile).
On-chain verification: wallet age 28 days, 402 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.
380 total trades across 54 markets.
39 bets on resolved markets available for calibration scoring.
Calibration error: 49.1% — needs improvement.
Skill: 1/100 (calibration quality). Variance: 31/100 (higher = more volatile returns).
Brier Skill Score: -0.9% vs naive baseline (>0% = better than always predicting base rate).
Brier decomposition: REL=0.2516 RES=0.0000 UNC=0.0000.
Log loss: 0.7001 (skill: -8753.9% vs naive). Lower log loss = better calibration on rare events.
Timeliness: avg entry 3.0 days before resolution, 10% early mover.
Below average. The data shows poor calibration, thin evidence, or both. When this trader expresses high confidence, events don't happen at the rate they imply.
Confidence: D/39 [CI95: D→D, 37-41] (39 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.