> ## Documentation Index > Fetch the complete documentation index at: https://artemis.ai/docs/llms.txt > Use this file to discover all available pages before exploring further. # Prediction Markets > Coverage, data sources, and metric methodology for the prediction-market (event-contract) venues Artemis tracks — Polymarket, Kalshi, CME, ForecastEx, Nadex, Gemini, Rothera, Opinion, Limitless, Myriad, Predict, and Hyperliquid HIP-4. 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](https://www.artemis.ai/sectors/prediction-markets) ## 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. ## Platforms we cover | Platform | Type | Chain / Venue | Data start | Symbol (`artemis_id`) | | - | - | - | - | - | | **Polymarket** | On-chain | Polygon | Sep 2020 | `polymarket` | | **Kalshi** | Centralized, CFTC-regulated | US exchange (API) | Jun 2021 | `kalshi` | | **CME** | Centralized, CFTC-regulated | CME Group (retail via FanDuel Predicts & DraftKings Predictions) | Sep 2022 | `cme` | | **Limitless** | On-chain | Base | Apr 2024 | `limitless` | | **ForecastEx** | Centralized, CFTC-regulated (DCM + DCO) | Interactive Brokers | Aug 2024 | `forecastex` | | **Myriad** | On-chain | Abstract / Base | Feb 2025 | `myriadmarket` | | **Nadex** | Centralized, CFTC-regulated (DCM) | Crypto.com \| Derivatives North America | Jun 2025 | `nadex` | | **Rain.one** | On-chain | — | Sep 2025 | `rain_one` | | **Opinion** | On-chain | — | Oct 2025 | `opinion` | | **Predict** | On-chain | — | Nov 2025 | `predict` | | **Gemini Predictions** | Centralized, CFTC-regulated (DCM) | Gemini (Gemini Titan, LLC) | Dec 2025 | `gemini` | | **Hyperliquid HIP-4** | On-chain | Hyperliquid | May 2026 | `hip4` | | **Rothera** | Centralized (EOD feed) | 24×7 event-contract venue | May 21, 2026 | `rothera` | > [!NOTE] > > **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](https://artemis.ai/docs/data-reference/supported-assets.md) for canonical IDs. ### Coming soon We're adding the following prediction-market venues soon: * **DKeX** — DraftKings' own CFTC-regulated exchange (formerly Railbird) FanDuel Predicts and DraftKings Predictions retail flow is already captured at the exchange level under **CME** above. New venues follow the same normalized metric framework and appear alongside the live venues as ingestion completes. ## Where the data comes from We use two ingestion models depending on whether a venue settles on-chain or off-chain: ### 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. ### 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 API market snapshots and trade feed (`fact_kalshi_trades`). Kalshi's event contracts are \$1-face binaries, so contract counts equal USD notional. Kalshi also lists perpetual futures, reported separately in USD-native `perp_*` fields. **ForecastEx** is Interactive Brokers' CFTC-regulated event-contract exchange (a DCM **and** DCO — it both lists and clears its own contracts), with published EOD history from 2024-08-01. We ingest ForecastEx's **end-of-day prices file** (per-contract, per-side volume and open interest). Each ForecastEx contract lists a YES and a NO (and, for elections, multiple) subtype row carrying the *same* pair-level figures, so we take the **MAX across a contract's subtype rows before summing across contracts** — a double-count-safe aggregation. On the \$1 cents-model each contract's face is \$1, so the contract count *is* the USD figure. **Gemini Predictions** is the prediction-markets venue run by Gemini Titan, LLC (Gemini's CFTC-regulated DCM), live since its 2025-12-15 launch. The headline volume is Gemini's own official **CFTC Rule 16.01 per-contract Market Data** publication; we also carry a complete-print secondary figure (`tick_contracts_traded`) built from the venue's **tick-by-tick Trade Data** file. Gemini does not report open interest — its file's OI column has been zero since launch — so `open_interest` is carried as an explicit `NULL`. **CME** lists CFTC-regulated binary yes/no event contracts on CME/CBOT/NYMEX/COMEX, distributed retail through **FanDuel Predicts** and **DraftKings Predictions** (both are FCM front-ends onto CME — the exchange-level figures here are the only published record, with no per-distributor split). We ingest CME's official daily volume + open-interest file (public FTP), filtered to event-contract products, with history from CME's 2022-09-19 event-contract launch. Coverage note: the **financial** event contracts (equity indices, energy, metals, FX, crypto) are captured; the **sports/culture** contracts — the bulk of volume since the Dec-2025 FanDuel Predicts launch — are published only in CME's Daily Bulletin Section 73 PDF and are a **known coverage gap**. Contract faces are not uniform (\$1 in the FanDuel era, \$20 for the 2022-era products), so `spot_volume` is a contract count, not USD. **Nadex** (North American Derivatives Exchange, operating as **Crypto.com | Derivatives North America** since the 2021 acquisition) is a CFTC-regulated event-contract DCM. We ingest the exchange's **Daily Bulletin PDF** (its CFTC Part 16 disclosure — per-contract daily volume, open interest, and settlement detail), aggregated twin-safe: a contract can appear twice per day (a trading-side and a settlement-side row), so we **sum volume but take MAX open interest** before summing across contracts. Coverage starts 2025-06-01 (the ingest backfill floor; bulletins exist back to 2019). Nadex contract faces vary (\$10–\$2,000 by product family), so `spot_volume` is a contract count with no uniform USD conversion; parlay ("combo") flow is broken out in `combo_volume`. **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, the price-weighted `volume_usd`/`open_interest_usd` fields are valued at the contract **settlement price**, an approximation rather than a fill-level tally. ## 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. | Metric | Definition | Methodology | Field name | | - | - | - | - | | **Spot Volume** | Daily trading volume across all event contracts. | On most venues, event contracts are **\$1-face binaries** (priced \$0–\$1), so a traded-contract *count* equals **USD notional** — the published convention on Kalshi, Polymarket, Rothera, ForecastEx, Gemini, and HIP-4, directly comparable across them. Sourced from indexed on-chain fills (on-chain venues), the exchange feed (Kalshi), the EOD prices file (ForecastEx, Rothera), or the Rule 16.01 Market Data file (Gemini). This is *notional*, not the price-weighted premium (cash actually traded, ≈ half of notional) — exposed separately as `volume_usd` where available. **Nadex and CME are the exception:** their contract faces vary by product family (Nadex \$10–\$2,000; CME \$1 or \$20), so their `spot_volume` is a contract count that does **not** convert uniformly to USD and is not directly comparable to the \$1-face venues. | `SPOT_VOLUME` | | **Open Interest** | Value of open, unsettled positions at end of day. | End-of-day snapshot of outstanding \$1-face contracts, so the contract count equals USD notional. Rothera additionally exposes a settlement-price-marked `open_interest_usd`. **Gemini does not report OI** (`NULL`); HIP-4 OI is reserved (fully collateralized outcomes). | `OPEN_INTEREST` | | **Contracts Traded** | Total number of contracts traded that day. | Count of contracts changing hands, independent of price — equal to Spot Volume on the \$1-face venues. Reported explicitly for Kalshi, CME, ForecastEx, Nadex, Gemini, and Rothera. Not currently exposed through the REST API — use `SPOT_VOLUME`, which equals the contract count on \$1-face venues. | `CONTRACTS_TRADED` | | **Spot Transactions** | Number of trades executed that day. | On-chain: count of trade/fill events. Centralized venues: number of trade records (fills) in the feed. | `SPOT_TXNS` | | **Spot DAU** | Daily active traders. | Distinct trading addresses (on-chain venues) or distinct accounts (centralized venues) that traded that day. | `SPOT_DAU` | | **MAU** | Monthly active traders. | Distinct trader addresses over the trailing 30 days, computed daily (currently exposed for Polymarket). | `MAU` | | **Fees** | Trading/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` | | **TVL** | Collateral locked in the protocol. | On-chain collateral backing open positions (exposed where a venue custodies collateral on-chain, e.g. Polymarket). | `TVL` | | **Active Markets** | Distinct markets with activity that day. | Count of distinct markets/symbols that traded. | `ACTIVE_MARKETS` | ### 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. > [!NOTE] > > **Reading volume across venues.** On the \$1-face binary venues, `spot_volume` is a contract/share count that already **equals USD notional**, so the headline numbers are directly comparable across Kalshi, Polymarket, ForecastEx, Gemini, Rothera, and HIP-4 without conversion. Keep in mind: > > * `spot_volume` is **notional**, not premium. The price-weighted cash actually traded (≈ half of notional at typical prices) is the separate `volume_usd` field where a venue exposes it (Rothera, ForecastEx). Don't mix the two. > * **Nadex and CME are not \$1-face.** Their contract faces vary by product family, so their `spot_volume` is a raw contract count that does not equal USD and should not be compared 1:1 with the \$1-face venues. On CME, note the sports/culture coverage gap; on Nadex, parlay flow (`combo_volume`) is a large share of the total. > * **Gemini** publishes two figures: the headline `spot_volume` (official Rule 16.01 Market Data) and `tick_contracts_traded` from the tick-by-tick file. The tick figure includes intraday 5/15-minute crypto contracts and repeated combo/cross prints that Gemini's own displayed volume excludes, so it runs a multiple of the headline — use `spot_volume` for cross-venue comparison. > * **Perpetual futures** on Kalshi and Polymarket are USD-native (not \$1-face) and live in separate `perp_*` fields — never sum them with event-contract `spot_volume`. ## Accessing the data Prediction-market metrics are available through every Artemis surface: * **Web app** — [Prediction Markets sector on artemis.ai](https://www.artemis.ai/sectors/prediction-markets) * **API / Python SDK** — see [Prediction Markets via the API](https://artemis.ai/docs/artemis-api/prediction-markets.md) 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__metrics`, with breakdowns under `RESULTS.EZ_METRICS_BY_DIMENSION` ## More information * [Prediction Markets — API & SDK examples](https://artemis.ai/docs/artemis-api/prediction-markets.md) * [Supported Assets](https://artemis.ai/docs/data-reference/supported-assets.md) * [Asset Metrics Catalog](https://artemis.ai/docs/data-reference/asset-metrics-catalog.md) * [Sector Metrics methodology](https://artemis.ai/docs/artemis-terminal/sector-metrics.md) This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.