> ## 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, Rothera, Opinion, Limitless, Myriad, Predict, Rain.one, 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` |
| **Limitless** | On-chain | Base | Apr 2024 | `limitless` |
| **Myriad** | On-chain | Abstract / Base | Feb 2025 | `myriadmarket` |
| **Rain.one** | On-chain | — | Sep 2025 | `rain_one` |
| **Opinion** | On-chain | — | Oct 2025 | `opinion` |
| **Predict** | On-chain | — | Nov 2025 | `predict` |
| **Hyperliquid HIP-4** | On-chain | Hyperliquid | May 2026 | `hip4` |
| **Rothera** | Centralized (EOD feed) | 24×7 event-contract venue | May 21, 2026 | `rothera` |
**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](/data-reference/supported-assets) for canonical IDs.
### 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.
## 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 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.
## 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. | 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 Interest** | Value 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 Traded** | Total number of contracts traded that day. | Count of contracts changing hands, independent of price. Reported for Kalshi and Rothera. | `CONTRACTS_TRADED` |
| **Spot Transactions** | Number of trades executed that day. | On-chain: count of trade/fill events. Rothera: number of EOD trade records (`trade_count`). | `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.
**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.
## 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](/artemis-api/prediction-markets) 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](/artemis-api/prediction-markets)
* [Supported Assets](/data-reference/supported-assets)
* [Asset Metrics Catalog](/data-reference/asset-metrics-catalog)
* [Sector Metrics methodology](/artemis-terminal/sector-metrics)