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Market 82.3% against model 73.2%. Resolves in 28d 7h, data updated 14d 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.
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.
side NO
73.2% model / 82.3% 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 73.2% vs market 82.3%.
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.
Volume $76,813
The model estimates a 9-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 | 71% | — | +0.888 | Bullish | Historical frequency for this kind of event — the prior before any market-specific evidence. |
No comparable events matched for this market.
This market will resolve according to the candidate who wins the 2026 Alaska gubernatorial election currently scheduled for November 3, 2026. If the results of the election are not confirmed by July 31, 2027, this market will resolve to "Other". The resolution source for this market is the Associated Press, Fox News, and NBC. This market will resolve once all three sources call the race for the same candidate. If all three sources haven’t called the race in Alaska for the same candidate, this market will resolve based on official certification.
analyzed by heuristicThis market will resolve according to the candidate who wins the 2026 Alaska gubernatorial election currently scheduled for November 3, 2026. If the results of the election are not confirmed by July 31, 2027, this market will resolve to "Other". The resolution source for this market is the Associated Press, Fox News, and NBC. This market will resolve once all three sources call the race for the same candidate. If all three sources haven’t called the race in Alaska for the same candidate, this market will resolve based on official certification.
- Oracle dependency Resolution depends on a single named source continuing to publish the metric.
- Deadline without timezone A deadline is stated without a timezone — the cutoff moment is undefined.
Resolves Tue, 03 Nov 2026 00:00:00 GMT. The contract pays on these exact criteria, not on the thesis.
Paper position only. No real-money execution
| —This factor was not available for this market. No approved link prices the same event on another venue for this market. |
| 0.20 |
| — |
| — |
| Whether the same event is priced differently on another venue. A gap may signal an opportunity or a structural difference. |
| Recent price momentum | —This factor was not available for this market. This factor was not available for this market. | 0.35 | — | — | Drift in the market's own implied probability over its last 8 price updates, typically a few hours. Recent directional 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 | 70.9% | Prior: 71% · Market: 83.2% | |||
| 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%. | 0.81 | Final: 73.2% = λ·model + (1−λ)·market | |||
Since the first stored model read on 2026-09-21, the market has moved from 84.8% to 82.3%.
This is a directional diagnostic for unresolved markets, not final performance. Resolved outcomes still determine the official live record.
Missing: Cross-market divergence, Recent price momentum, 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 | 23 | |
| Price volatility | 7 | |
| Resolution proximity | 0 | |
| Data quality | 51 | |
| Category base risk | 55 | |
| Resolution ambiguity | 30 | |
| Regulatory exposure | 0 | |
| Portfolio concentration | 0 |
Composite score 23/100, higher = riskier.
| Market | Mkt | Delta |
|---|---|---|
| Category context | ||
| Will Camilo Santana win the 2026 Brazilian presidential election? category context: same category + wording overlap | 0.1% | +17pt |
| Will Augusto Cury win the 2026 Brazilian presidential election? category context: same category + wording overlap | 0.1% | +17pt |
| Will Geraldo Alckmin win the 2026 Brazilian presidential election? category context: same category + wording overlap | 0.1% | +17pt |
| Will Sol Zanetti be the next Premier of Quebec following the 2026 Quebec general election? category context: same category + wording overlap | 0.2% | -- |
| Will Bernard Drainville be the next Premier of Quebec following the 2026 Quebec general election? category context: same category + wording overlap | 0.2% | -- |
Divergences > 5pt flagged in amber. For cross-venue pricing, see the Scanner.