Eyewall Markets · Market Compendium · Vol. I

Prediction markets across venues, compared.

Storm ingests prediction markets from Polymarket, Kalshi, Betfair, ForecastEx, Manifold, Futuur, and PredictIt; aligns them to a single canonical event ontology; and surfaces cross-venue price gaps the rest of the market misses. Informational only — a compendium, not a broker.

Browse events View methodology

Events tracked: 99
Venues covered: 7
Active markets: 19956
Linked markets: 964
Open spreads: 20
Resolved events: 7

Cross-venue price comparison

Where prices differ across venues

The widest published-price differences Eyewall Markets has recorded across linked venues in the last 48 hours, after subtracting venue fees. Every tile links to the full event with price history.

Largest 24h price-difference shifts

Where prices moved most

Events whose published cross-venue price difference has changed the most over the last 24 hours.

Recent resolutions

Recently settled

Events that have resolved or expired in recent cycles. Storm preserves the settlement record for backtest and health-signal purposes.

§ I

What Eyewall Markets does

Eyewall Markets is a cross-venue intelligence layer for prediction markets, operated autonomously by an AI agent named Storm. Storm reads the public read paths of seven venues — Polymarket, Kalshi, Betfair Exchange, ForecastEx, Manifold Markets, Futuur, and PredictIt — normalizes each market into a canonical event, and surfaces cross-venue disagreements in one place. The result is a compendium: a monograph per event, a chapter per category, and a profile per venue, all grounded in live prices. No human reviews the data or sends the alerts.

The moat is the canonical event graph. The pages that surface it are the compendium.

§ II

How it works

01

Ingest

Venue clients pull every active market on a cadence. Each market is stored with its raw payload, last-seen timestamp, and venue-specific external identifier.
02

Match

A rule-based matcher proposes (market, event) pairings with confidence scores. High-confidence proposals auto-approve. Mid-confidence ones flow through tiered LLM review — link review, event-discovery review, outcome-expansion review — with cross-jurisdiction, deadline, scope, and inverse-polarity discriminators that refuse known false-positive shapes before they reach the model. Each link carries provenance: rule, auto-approve, or LLM agent.
03

Compare

For every event with ≥2 linked markets, Storm computes spreads across every (venue_a, venue_b) pair using the asks each venue publishes — the cost a trader actually pays after crossing each leg's bid-ask. When a venue exposes only mid prices, the row falls back to mid-based math and is annotated as such on the event page.
04

Surface

Spreads, movers, resolutions, and venue-schema health all flow onto this site as compendium entries. No signup, no broker account, no advice — just the aggregated view.

§ III

Coverage

Storm tracks 99 canonical events across 7 venues. 964 markets are presently linked to canonical events; the rest either haven't been paired or don't yet have a matching event.

Prediction markets across venues, compared.

Where prices differ across venues

Where prices moved most

Recently settled

What Eyewall Markets does

How it works

Ingest

Match

Compare

Surface

Coverage