Will MegaETH perform an airdrop by June 30?
Market 1.0% against model 29.7%. Resolves in 4d 6h, data updated 7d ago.
Decision layer
Actionable research signal
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
One decision layer for the market read.
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 YES
29.7% model / 1.0% 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.
Read this market in three passes
Model 29.7% vs market 1.0%.
Raw disagreement is reduced by fees, spread, slippage, and risk controls.
Model leans YES
Why this read matters
The model-market gap currently survives the decision gates, but it is still research context and must be judged against the public track record.
Will MegaETH perform an airdrop by June 30?
Volume $1,595,397
Market-implied vs model probability
Factor attribution
The model estimates a 29-point higher probability than the market, primarily driven by historical base rate and btc/eth 7-day 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 | 31% | — | −0.815 | Bearish | Historical frequency for this kind of event — the prior before any market-specific evidence. |
| Cross-market divergence | —This factor was not available for this market. No approved cross-venue link exists 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. |
| 7-day price momentum | —This factor was not available for this market. This factor was not available for this market. | 0.35 | — | — | 7-day drift in the market's own implied probability. Sustained directional moves carry information. |
| BTC/ETH 7-day momentum | +0.69 | 0.20 | +0.139 | Bullish | 7-day BTC/ETH return z-score, tanh-squashed. |
| 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 | 33.7% | Prior: 31% · Market: 14.4% | |||
| 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%. | 0.79 | Final: 29.7% = λ·model + (1−λ)·market | |||
Comparable eventsseeded prior 31% - 0 matches (min 8 for historical)
| Event | Outcome | Relevance |
|---|---|---|
| BTC all-time-high retests after >20% drawdowns (2017–2025) | Reclaimed within 6 months in most bull regimes | Price-threshold markets depend heavily on prevailing regime. |
| Round-number threshold markets on Polymarket 2024–25 | Markets systematically overpriced near-miss thresholds | Anchoring bias inflates YES prices near salient levels. |
Scenario treeEngine template
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 | 13.4% | $1 | +95.7c |
| Threshold hit in second half | 16.4% | $1 | +95.7c |
| Never reaches threshold in window | 70.3% | $0 | -4.3c |
Root-implied probability 29.7% reconciles with the model's 29.7% (±1pt invariant).
Why this mattersTemplate (no LLM key)
A 15.3% probability gap at a 14.4% price translates to 11.8% 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¢.
What could make this wrongTemplate (no LLM key)
The model's edge depends on its inputs being right. Concretely: the base rate of 30.7% may not apply if this event differs structurally from its reference class; the crypto.btc_eth_momentum_7d factor could be noise rather than information at this horizon; and with confidence at 0.79, the model itself concedes meaningful estimation error. Resolution risk remains: the contract pays on the precise criteria — "This market will resolve to "Yes" if MegaETH launches a token and performs an airdrop by June 30, 2026, 11:59 PM ET. Otherwise, this market …" — not on the thesis.
- - Risk score 24/100 — composite of liquidity, volatility, time-to-resolution, data quality and category risk.
- - Factor agreement 1.00: factors broadly agree, but shared blind spots are possible.
- - Data quality 0.69 (simulated input in MVP).
- - Simulated model values — this brief demonstrates structure, not live research.
Description
This market will resolve to "Yes" if MegaETH launches a token and performs an airdrop by June 30, 2026, 11:59 PM ET. Otherwise, this market will resolve to "No". For the purposes of this market "locked" tokens or non-swappable tokens will not suffice to resolve this market to "Yes". Airdrops of NFTs will not qualify. The primary resolution source for this market is on-chain information and official information from MegaETH, however a consensus of credible reporting will also be used.
Resolution criteria (verbatim, with analyzer flags)
analyzed by heuristicThis market will resolve to "Yes" if MegaETH launches a token and performs an airdrop by June 30, 2026, 11:59 PM ET. Otherwise, this market will resolve to "No". For the purposes of this market "locked" tokens or non-swappable tokens will not suffice to resolve this market to "Yes". Airdrops of NFTs will not qualify. The primary resolution source for this market is on-chain information and official information from MegaETH, however a consensus of credible reporting will also be used.
Resolves Wed, 01 Jul 2026 04:00:00 GMT. The contract pays on these exact criteria, not on the thesis.
Suggested paper position
Paper position only. No real-money execution
Live open-market tracking
Since the first stored model read on 2026-06-15, the market has moved from 17.8% to 1.0%.
This is a directional diagnostic for unresolved markets, not final performance. Resolved outcomes still determine the official live record.
Data quality69/100 - usable
Missing: Cross-market divergence, 7-day 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.
Risk factor breakdownsim
| Inverse liquidity | 32 | |
| Price volatility | 12 | |
| Resolution proximity | 70 | |
| Data quality | 38 | |
| Category base risk | 50 | |
| Resolution ambiguity | 8 | |
| Regulatory exposure | 0 | |
| Portfolio concentration | 3 |
Composite score 24/100, higher = riskier.
Related markets
| Market | Mkt | Delta |
|---|---|---|
| Category context | ||
| BTC closes above $100k this week? category context: same category + wording overlap | 61.0% | -4pt |
Divergences > 5pt flagged in amber. For cross-venue pricing, see the Scanner.