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Market 99.2% against model 81.1%. Resolves in 1d 22h, data updated 1d ago.
Decision layer
The model disagreement survives the current gates. This is still research context, not financial advice.
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.
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.
side NO
81.1% model / 99.2% market
fees, spread, slippage, risk
Model edge survives the current public research gates.
Watch whether the market price moves toward or away from the model.
Model 81.1% vs market 99.2%.
Raw disagreement is reduced by fees, spread, slippage, and risk controls.
Model leans NO
The model-market gap currently survives the decision gates, but it is still research context and must be judged against the public track record.
Sign in to return to this exact question, review governed evidence, and record an append-only probability without exposing private thesis text.
usable feature coverage.
Volume $1,635,094
The model estimates a 18-point lower 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 | 79% | — | +1.297 | Bullish | Historical frequency for this kind of event — the prior before any market-specific evidence. |
| Cross-market divergence | 0.00 | 0.20 |
No comparable events matched for this market.
A by-election for the United Kingdom parliamentary constituency of Clacton is expected to be held soon following the announced resignation of incumbent Nigel Farage. This market will resolve according to the candidate who wins the Clacton parliamentary by-election. If the election results are not known definitively by June 30, 2027, 11:59 PM ET, this market will resolve to "Other". The resolution source for this market will be a consensus of credible reporting. In case of ambiguity, this market will resolve solely based on official election results as published by Tendring District Council (https://www.tendringdc.gov.uk/) and the UK Parliament (https://www.parliament.uk/).
ambiguity 40/100analyzed by heuristicA by-election for the United Kingdom parliamentary constituency of Clacton is expected to be held soon following the announced resignation of incumbent Nigel Farage. This market will resolve according to the candidate who wins the Clacton parliamentary by-election. If the election results are not known definitively by June 30, 2027, 11:59 PM ET, this market will resolve to "Other". The resolution source for this market will be a consensus of credible reporting. In case of ambiguity, this market will resolve solely based on official election results as published by Tendring District Council (https://www.tendringdc.gov.uk/) and the UK Parliament (https://www.parliament.uk/).
- Undefined edge case The criteria themselves acknowledge unresolved edge cases.
- Oracle dependency Resolution depends on a single named source continuing to publish the metric.
Resolves Thu, 13 Aug 2026 16:00:00 GMT. The contract pays on these exact criteria, not on the thesis.
Paper position only. No real-money execution
| 0.000 |
| Neutral |
| Linked venue pricing the same event higher/lower (V2 scanner); 0 without an approved link. |
| 7-day price momentum | 0.00 | 0.35 | 0.000 | 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 | 78.5% | Prior: 79% · Market: 99.0% | |||
| 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%. | 0.88 | Final: 81.1% = λ·model + (1−λ)·market | |||
Since the first stored model read on 2026-07-31, the market has moved from 97.5% to 99.2%.
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 | 12 | |
| Price volatility | 1 | |
| Resolution proximity | 86 | |
| Data quality | 28 | |
| Category base risk | 55 | |
| Resolution ambiguity | 40 | |
| Regulatory exposure | 0 | |
| Portfolio concentration | 0 |
Composite score 30/100, higher = riskier.
| Market | Mkt | Delta |
|---|---|---|
| Category context | ||
| Putin out as President of Russia by July 31, 2026? category context: same category + wording overlap | 0.1% | -- |
| Trump out as President by July 31? category context: same category + wording overlap | 0.1% | -- |
| Will Haley Stevens win the 2026 Michigan Democratic Primary? category context: same category + wording overlap | 3.6% | +15pt |
| Trump out as President before GTA VI? category context: same category + wording overlap | 49.5% | +1pt |
| Will Abdul El-Sayed win Wayne County in the Michigan Senate Democratic primary? category context: same category + wording overlap | 80.5% | -10pt |
Divergences > 5pt flagged in amber. For cross-venue pricing, see the Scanner.