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Market 52.0% against model 69.7%. Resolves in resolved.
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.
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
69.7% model / 52.0% market
fees, spread, slippage, risk
Inside the 24h resolution-risk window — late-breaking information dominates any model edge.
Inside the 24h resolution-risk window — late-breaking information dominates any model edge.
Model 69.7% vs market 52.0%.
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.
strong feature coverage.
Volume $144,400
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 18-point higher probability than the market, primarily driven by historical base rate and 7-day price momentum.
| 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% | — | +0.916 | Bullish | Historical frequency for this kind of event — the prior before any market-specific evidence. |
| Cross-market divergence | 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 | +0.22 | 0.35 | +0.075 | Bullish | 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 | |||
| Model probability | 73.0% | Prior: 71% · Market: 52.0% | |||
| 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%. | 0.84 | Final: 69.7% = λ·model + (1−λ)·market | |||
| Event | Date | Outcome | Prior mkt prob. |
|---|---|---|---|
| Nvidia Q3 FY2025 — Beats but softer guidance | 2024-11-20 | EPS $0.81 vs $0.74 est. Beat, but Q4 guidance midpoint slightly light. | 72% |
| Alphabet Q3 2024 — Search and Cloud beat | 2024-10-29 | EPS $2.12 vs $1.85 est. Google Cloud $11.4B vs $10.9B est. Beat. | 68% |
| Boeing Q3 2024 — Strike and write-downs miss | 2024-10-23 | EPS -$10.44 vs -$3.57 est. $6.2B loss from strikes and defense charges. Massive miss. | 35% |
| Apple Q3 FY2024 — Services record and iPhone beat | 2024-08-01 | EPS $1.40 vs $1.35 est. Services $24.2B all-time record. Beat. | 64% |
| Meta Q2 2024 — AI-driven ad revenue beat | 2024-07-31 | EPS $5.16 vs $4.72 est. Revenue $39.1B vs $38.3B est. Beat. |
Node probabilities are conditional on the parent; hover for cumulative path probability. Leaf EV is per $1 YES contract at the current price, before fees (fee-adjusted EVs in the table on the left).
| Path | Path prob. | YES pays | EV (YES, after costs) |
|---|---|---|---|
| Threshold hit in first half of window | 31.4% | $1 | +44.9c |
| Threshold hit in second half | 38.3% | $1 | +44.9c |
| Never reaches threshold in window | 30.3% | $0 | -55.1c |
Root-implied probability 69.7% reconciles with the model's 69.7% (±1pt invariant).
A 16.2% probability gap at a 52.0% price translates to 13.1% expected value per dollar of payout exposure after costs on the YES side. EV — not the raw probability gap — is the comparable number: the same gap is worth very different amounts at 50¢ and at 92¢.
The model's edge depends on its inputs being right. Concretely: the base rate of 71.4% may not apply if this event differs structurally from its reference class; the pm.momentum_7d factor could be noise rather than information at this horizon; and with confidence at 0.82, the model itself concedes meaningful estimation error. Resolution risk remains: the contract pays on the precise criteria — "Resolves YES if Apple reports Q2 FY2026 diluted EPS above the consensus estimate published by Bloomberg at market close on the day before th…" — not on the thesis.
Apple Q2 FY2026 earnings. The model sees a small edge but below the tradeable hurdle.
analyzed by heuristicResolves YES if Apple reports Q2 FY2026 diluted EPS above the consensus estimate published by Bloomberg at market close on the day before the earnings call.
Resolves Fri, 19 Jun 2026 03:48:52 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
| — |
| — |
| 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. |
| 68% |
| Intel Q2 2024 — Massive miss and 15,000 layoffs | 2024-07-25 | EPS $0.02 vs $0.10 est. Announced 15,000 layoffs and dividend cut. Miss. | 42% |
| Nvidia Q1 FY2025 — Blackwell transition beat | 2024-05-22 | EPS $6.12 vs $5.16 est. Revenue $26.0B vs $24.6B est. Beat. | 75% |
| Alphabet Q1 2024 — First-ever dividend + buyback | 2024-04-25 | EPS $1.89 vs $1.51 est. Beat + $70B buyback + first dividend. | -- |
| Tesla Q1 2024 — Delivery and margin miss | 2024-04-23 | EPS $0.45 vs $0.51 est. Revenue $21.3B vs $22.3B est. Miss. | 45% |
| Goldman Sachs Q1 2024 — Trading revenue beat | 2024-04-15 | EPS $11.58 vs $8.73 est. FICC and equities trading dominated. Beat. | 60% |
| Meta Q4 2023 — First dividend + massive efficiency beat | 2024-02-01 | EPS $5.33 vs $4.82 est. Revenue $40.1B vs $39.2B est. First dividend announced. Beat. | 68% |
| Amazon Q4 2023 — AWS re-acceleration beat | 2024-02-01 | EPS $1.00 vs $0.80 est. AWS grew 13%, re-accelerating. Beat. | 65% |
Real historical events from the comparable-events library (showing 12 of 21 matched). The model's base rate is the realized frequency over the full matched set.
Since the first stored model read on 2026-06-09, the market has moved from 52.0% to 52.0%.
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 | 24 | |
| Price volatility | 0 | |
| Resolution proximity | 100 | |
| Data quality | 55 | |
| Category base risk | 40 | |
| Resolution ambiguity | 8 | |
| Regulatory exposure | 0 | |
| Portfolio concentration | 0 |
Composite score 35/100, higher = riskier.
| Market | Mkt | Delta |
|---|---|---|
| Category context | ||
| Core CPI below 2.8% YoY for May 2026? same event: same venue event + similar expiry window | 48.0% | +3pt |
| Fed holds rates at June 2026 FOMC meeting? same event: same venue event + similar expiry window | 74.0% | -52pt |
| UK inflation falls below 2.0% for May 2026? same event: same venue event + wording overlap | 55.0% | -6pt |
| BTC closes above $100k this week? same event: same venue event + wording overlap | 61.0% | -2pt |
| EU AI Act enforcement delayed past Q3 2026? same event: same venue event + wording overlap | 49.0% | -8pt |
Divergences > 5pt flagged in amber. For cross-venue pricing, see the Scanner.