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Artemis tracks the leading prediction-market (event-contract) venues on the same fundamental framework we use for exchanges and protocols: daily volume, open interest, transactions, active users, fees, and — where the venue is on-chain — TVL. This page documents every prediction market we cover, where the underlying data comes from, and exactly how each metric is calculated. Explore the Prediction Markets sector on Artemis

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What is a prediction market?

A prediction market is an exchange where users trade binary (or multi-outcome) event contracts — “Will X happen by date Y?” — that settle to a fixed value (typically $1) if the event resolves true and $0 otherwise. The traded price between $0 and $1 is read as the market-implied probability of the event. Because contracts are fully collateralized and settle to a known value, prediction markets have their own metric vocabulary (contracts traded, open interest in contracts, settlement value) that we normalize into the standard Artemis fields below.

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Platforms we cover

PlatformTypeChain / VenueData startSymbol (artemis_id)
PolymarketOn-chainPolygonSep 2020polymarket
KalshiCentralized, CFTC-regulatedUS exchange (API)Jun 2021kalshi
LimitlessOn-chainBaseApr 2024limitless
MyriadOn-chainAbstract / BaseFeb 2025myriadmarket
Rain.oneOn-chain—Sep 2025rain_one
OpinionOn-chain—Oct 2025opinion
PredictOn-chain—Nov 2025predict
Hyperliquid HIP-4On-chainHyperliquidMay 2026hip4
RotheraCentralized (EOD feed)24×7 event-contract venueMay 21, 2026rothera
Drift (drift) also operates a prediction-market (“BET”) product, but is tracked primarily as a Solana perpetuals/spot venue, so its prediction-market activity is folded into its protocol metrics rather than broken out here.
Coverage windows are the first date with data through today; new venues are added as they reach meaningful volume. See the full asset list for canonical IDs.

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Coming soon

We’re adding the following prediction-market venues soon:
  • ForecastEx (Interactive Brokers)
  • Nadex (Crypto.com | Derivatives North America)
  • DKeX (DraftKings, formerly Railbird)
  • FanDuel prediction market
These will follow the same normalized metric framework and appear alongside the live venues above as ingestion completes.

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Where the data comes from

We use two ingestion models depending on whether a venue settles on-chain or off-chain:

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On-chain venues (indexed from the blockchain)

Polymarket, Limitless, Myriad, Rain.one, Opinion, Predict, and Hyperliquid HIP-4 settle on public blockchains. For these we index raw trade/fill events directly from archive nodes and raw block feeds, then aggregate to a daily grain. This is the same event-level pipeline used for DEXes and perps — no reliance on a venue-reported dashboard number.
  • Polymarket — indexed from Polygon. Every fill is a USDC-denominated on-chain event; the raw trade table (fact_polymarket_trades) feeds the daily model. Because Polymarket settles via UMA’s optimistic oracle, we also track UMA dispute counts and unique disputers, plus maker rebates paid on Polygon.
  • Hyperliquid HIP-4 — indexed from Hyperliquid’s raw node feed. Outcome markets are fully collateralized; each binary share settles to $1, so notional volume is measured in shares.

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Off-chain / centralized venues (venue data feed)

Kalshi is a CFTC-regulated US exchange whose contracts do not settle on-chain, so we ingest from Kalshi’s official data feed (fact_kalshi_trades), denominated in USD. Rothera is a 24×7 event-contract venue that launched on 2026-05-21. We ingest Rothera’s end-of-day (EOD) market feed — per-contract volume and open interest snapshotted daily. Because the EOD feed carries no per-trade VWAP, USD figures are valued at the contract settlement price, which makes volume_usd/open_interest_usd an approximation rather than a fill-level tally.

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How we calculate each metric

All venues are normalized onto the standard Artemis metric fields so they can be compared side-by-side. Not every venue exposes every metric; the table notes where a field is venue-specific.
MetricDefinitionMethodologyField name
Spot VolumeDaily trading volume across all event contracts.For on-chain venues, sum of every fill for the day from indexed trade events (USD notional). For Kalshi, USD volume from the exchange feed. For Rothera, this is a contract count (identical to Contracts Traded), pending the family-wide contracts→USD standardization; USD notional is in volume_usd. For HIP-4, notional in binary shares (each share = $1).SPOT_VOLUME
Open InterestValue of open, unsettled positions at end of day.End-of-day snapshot of outstanding contracts. On-chain venues value in USD; Kalshi/Rothera report a contract count, with USD in open_interest_usd (Rothera).OPEN_INTEREST
Contracts TradedTotal number of contracts traded that day.Count of contracts changing hands, independent of price. Reported for Kalshi and Rothera.CONTRACTS_TRADED
Spot TransactionsNumber of trades executed that day.On-chain: count of trade/fill events. Rothera: number of EOD trade records (trade_count).SPOT_TXNS
Spot DAUDaily active traders.Distinct trading addresses (on-chain venues) or distinct accounts (centralized venues) that traded that day.SPOT_DAU
MAUMonthly active traders.Distinct trader addresses over the trailing 30 days, computed daily (currently exposed for Polymarket).MAU
FeesTrading/protocol fees generated that day.Sum of fees taken by the venue on each fill, in USD. Exposed as FEES (protocol total) and SPOT_FEES (spot leg) depending on venue.FEES / SPOT_FEES
TVLCollateral locked in the protocol.On-chain collateral backing open positions (exposed where a venue custodies collateral on-chain, e.g. Polymarket).TVL
Active MarketsDistinct markets with activity that day.Count of distinct markets/symbols that traded.ACTIVE_MARKETS

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Category & sub-category breakdowns

For the largest venues we split daily volume and open interest into a cross-venue-comparable taxonomy (Sports, Politics, Economics, Crypto, …) so the same categories line up across platforms:
  • Polymarket and Kalshi expose SPOT_VOLUME_SPORTS, SPOT_VOLUME_POLITICS, SPOT_VOLUME_CRYPTO, and ..._WITHOUT_SPORTS variants, plus per-category tables (*_metrics_by_category) and hourly tables (*_metrics_by_hour).
  • Rothera has no category field in its EOD feed, so category is derived from each contract’s product-code prefix (via an internal mapping) into the same cross-venue taxonomy. Rothera additionally offers a sport-level drilldown (Soccer / Baseball / Tennis / American Football / Macro) that is intentionally not cross-venue-comparable.
Reading volume across venues: on-chain venues and Kalshi report USD-denominated volume. Rothera’s spot_volume and HIP-4’s spot_volume are contract/share counts — use Rothera’s volume_usd when you need a dollar figure, and treat HIP-4 shares as $1 each. We are standardizing all venues onto USD-denominated spot_volume; until then, check the field notes above before summing across platforms.

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Accessing the data

Prediction-market metrics are available through every Artemis surface:
  • Web app — Prediction Markets sector on artemis.ai
  • API / Python SDK — see Prediction Markets via the API for fetch_metrics examples
  • Sheets — pull the fields above directly into Google Sheets or Excel
  • Snowflake Data Share — daily models live under RESULTS.EZ_METRICS.ez_<venue>_metrics, with breakdowns under RESULTS.EZ_METRICS_BY_DIMENSION

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More information