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Market 36.5% against model 39.1%. Resolves in 61d 12h, data updated 2d ago.
The model can still be informative here, but one or more gates blocks a trade call.
Decision layer
The model may still be informative, but at least one gate blocks an action-style signal.
Expected value after costs, not raw probability spread.
How much support the model sees across available inputs.
Thin markets can erase apparent edge through spread and slippage.
Resolution ambiguity, timing, and data quality pressure the decision.
usable feature coverage.
Why / why not trade
This public box mirrors the internal diagnostic style without exposing execution controls: decision, probability gap, cost-adjusted edge, blocker, and next thing to monitor.
no side selected
39.1% model / 36.5% market
fees, spread, slippage, risk
No edge after fees and slippage — the market price is fair within costs.
No edge after fees and slippage — the market price is fair within costs.
Model 39.1% vs market 36.5%.
Raw disagreement is reduced by fees, spread, slippage, and risk controls.
No trade
The model may disagree with price, but the gates say the disagreement is not actionable right now.
Sign in to return to this exact question, review governed evidence, and record an append-only probability without exposing private thesis text.
Volume $228,751
Declining to trade is a feature: most markets are priced fairly within costs, and the risk gates run before any edge is considered.
The model estimates a 3-point higher probability than the market, primarily driven by historical base rate.
| FACTOR | SIGNAL | WEIGHT | LOG-ODDS ΔLog-odds contribution measures how much each factor shifted the model's probability estimate in log-odds space — the mathematically correct way to stack independent evidence. Formula: Δlog-odds = weight × signal. Positive values push the probability up; negative values push it down. Log-odds are converted back to probability via the logistic function at the end. | DIRECTION | DESCRIPTION |
|---|---|---|---|---|---|
| Historical base rate | 39% | — | −0.464 | Bearish | Historical frequency for this kind of event — the prior before any market-specific evidence. |
No comparable events matched for this market.
Ye, formerly known as Kanye West, is scheduled to perform in Russia in October 2026. This market will resolve to "Yes" if Kanye West performs live in-person on-stage in front of a live audience in Russia by October 31, 2026, 11:59 PM ET. Otherwise, this market will resolve to "No". The performance must take place at an event that was announced or promoted in advance, and held at a venue such as an arena, stadium, festival ground, concert hall, theater, or club, and is open to an audience by ticket, invitation, or other controlled entry. The resolution source for this market will be a consensus of credible reporting.
analyzed by heuristicYe, formerly known as Kanye West, is scheduled to perform in Russia in October 2026. This market will resolve to "Yes" if Kanye West performs live in-person on-stage in front of a live audience in Russia by October 31, 2026, 11:59 PM ET. Otherwise, this market will resolve to "No". The performance must take place at an event that was announced or promoted in advance, and held at a venue such as an arena, stadium, festival ground, concert hall, theater, or club, and is open to an audience by ticket, invitation, or other controlled entry. The resolution source for this market will be a consensus of credible reporting.
Resolves Sun, 01 Nov 2026 03:59:00 GMT. The contract pays on these exact criteria, not on the thesis.
The engine sizes NO TRADE markets to zero. Sizing never overrides the risk gates.
Paper position only. No real-money execution
| 0.00 |
| 0.20 |
| 0.000 |
| Neutral |
| Linked venue pricing the same event higher/lower (V2 scanner); 0 without an approved link. |
| 7-day price momentum | +0.13 | 0.35 | +0.047 | Neutral | 7-day drift of the market's own implied probability — sustained moves carry information. |
| BTC/ETH 7-day momentum | —This factor was not available for this market. This factor applies to crypto markets only. | 0.20 | — | — | 7-day Bitcoin or Ethereum return, normalized. Applied to crypto-category markets only. |
| Rate surprise | —This factor was not available for this market. This factor applies to Fed, CPI, and macro markets only. | 0.25 | — | — | 2-year Treasury yield reaction in the 48 hours after the most recent scheduled release — a proxy for how markets interpreted the data versus expectations. |
| Yield curve shift | —This factor was not available for this market. This factor applies to Fed, CPI, and macro markets only. | 0.15 | — | — | 30-day change in the 10-year minus 2-year Treasury spread. A flattening curve signals tightening expectations; steepening signals easing. |
| News signal | —This factor was not available for this market. No news signal available for this market in the past 14 days. | 0.25 | — | — | Reliability-weighted direction of relevant news from the past 14 days. Official sources (filings, agency statements) carry more weight than commentary. |
| Crowd forecast | —This factor was not available for this market. Insufficient forecasters to compute crowd signal. Requires at least 5 calibration-weighted estimates. | 0.20 | — | — | Calibration-weighted average of user probability estimates. Only applied when 5 or more weighted forecasters have submitted estimates. |
| Model probability | 39.7% | Prior: 39% · Market: 36.5% | |||
| Confidence (λ)Confidence λ (lambda) controls how much weight to give the model vs. the market. Formula: p_final = λ·p_model + (1−λ)·p_market. λ is derived from data quality, factor agreement, and liquidity. When inputs are weak, the model shrinks toward the market — not toward 50%. | 0.80 | Final: 39.1% = λ·model + (1−λ)·market | |||
Since the first stored model read on 2026-08-26, the market has moved from 30.0% to 36.5%.
This is a directional diagnostic for unresolved markets, not final performance. Resolved outcomes still determine the official live record.
Missing: News signal, Crowd forecast
When features are unavailable, the model increases uncertainty and weights the final estimate closer to the market price. Lower data quality does not mean the market is wrong. It means the model is being appropriately humble.
| Inverse liquidity | 33 | |
| Price volatility | 75 | |
| Resolution proximity | 0 | |
| Data quality | 59 | |
| Category base risk | 80 | |
| Resolution ambiguity | 8 | |
| Regulatory exposure | 0 | |
| Portfolio concentration | 0 |
Composite score 35/100, higher = riskier.
| Market | Mkt | Delta |
|---|---|---|
| Category context | ||
| US obtains Iranian enriched uranium by August 31? category context: same category + wording overlap | 2.5% | +16pt |
| Total Internet Blackout in Iran by August 31, 2026? category context: same category + wording overlap | 8.5% | +14pt |
| Will Russia enter Mykhailivka by August 31? category context: same category + wording overlap | 9.5% | +12pt |
| Will Israel launch a ground operation in Iran by August 31, 2026? category context: same category + wording overlap | 14.5% | +8pt |
| Will China invades Taiwan before GTA VI? category context: same category + wording overlap | 50.5% | -0pt |
Divergences > 5pt flagged in amber. For cross-venue pricing, see the Scanner.