Prediction Markets Order Books

Order Book Data

Order books provide a current view of available liquidity for every prediction market by exposing the buy and sell orders waiting to be matched. While trades and OHLCV data describe executed market activity, order books reveal the liquidity available before a transaction occurs, allowing applications to observe market depth, bid-ask spreads, and changes in supply and demand.

FinFeedAPI provides two complementary order book datasets. The current order book endpoint returns the latest snapshot of bids and asks for a market outcome, while the historical endpoint provides raw limit order updates from flat files. Together, these endpoints support both live liquidity monitoring and event-level historical analysis.

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What Is Prediction Market Order Book Data?

Prediction market order book data represents the outstanding buy and sell interest for an individual market outcome.

A current order book snapshot contains the available bid and ask levels together with their corresponding order sizes at the moment the snapshot is generated. Rather than recording completed transactions, the order book reflects the liquidity currently available on the market, providing insight into where participants are willing to buy or sell before trades occur.

FinFeedAPI also provides historical order book data through flat files. Unlike the current endpoint, the historical dataset returns raw limit order updates—including order additions, updates, and deletions—rather than reconstructed snapshots. This allows developers to replay historical order flow or rebuild order book state using their own reconstruction logic.

Together, these datasets support both live market monitoring and detailed historical liquidity analysis using the same exchange and market identifiers.

Why Use Prediction Market Order Book Data?

Order books expose information that cannot be derived from trades or OHLCV data alone.

Developers use prediction market order book data to:

  • Monitor current bid and ask liquidity for individual market outcomes
  • Measure bid-ask spreads and market depth
  • Track changes in available liquidity as orders are added, updated, or removed
  • Analyze order flow alongside executed trades and quotes
  • Reconstruct historical order books from raw limit order updates
  • Build quantitative research datasets based on historical liquidity
  • Develop execution models and market microstructure analytics
  • Provide AI systems with event-level market depth data in addition to aggregated price history

By combining order books with trades, quotes, OHLCV, and market metadata, applications can build a more complete representation of prediction market behavior.

What's Included in Prediction Market Order Book Data?

Current responses return a reconstructed snapshot of bids and asks. Historical requests return raw limit order events from flat files, using the same exchange_id and market_id identifiers.

Current Order Book Snapshot

Current order book responses include market identifiers, timestamps, and the current bid and ask ladders.

FieldDescription
exchange_idExchange where the market is listed.
market_idCanonical prediction market identifier, including the outcome.
time_exchangeTimestamp generated by the exchange.
time_coinapiTimestamp when FinFeedAPI processed the order book snapshot.
asksArray of current ask price levels.
bidsArray of current bid price levels.

Each bid and ask entry contains:

FieldDescription
priceOrder price.
sizeAvailable quantity at the specified price level.

Historical Order Updates

Historical order book records contain raw limit order events rather than reconstructed order book snapshots.

Historical requests return limit order updates retrieved from flat files and support both full-day (date) queries and bounded (time_start / time_end) time ranges.

These records are intended for applications that reconstruct historical order books, replay order flow, or analyze liquidity evolution over time.

The historical endpoint uses the same exchange_id and market_id identifiers as the current order book endpoint, allowing applications to combine live snapshots with historical order events using a consistent market model.

Available REST Endpoints

The Prediction Markets API exposes a current snapshot endpoint for live liquidity monitoring and a historical endpoint for raw limit order updates from flat files. Every endpoint uses the same exchange_id and market_id identifiers.

Current Order Book

Returns the latest order book snapshot for a specific market outcome. The response contains the current bid and ask ladders, allowing applications to inspect available depth, calculate spreads, or monitor changes in market liquidity.

Response includes
  • exchange identifier
  • market identifier
  • exchange timestamp
  • processing timestamp
  • bid levels
  • ask levels
Parameters:exchange_id • market_id

Historical Order Updates

Returns historical limit order updates for a market from flat files. This endpoint is intended for applications that replay historical order flow or rebuild order book state using their own reconstruction logic. Data can be requested for an entire day or for a bounded time range.

Response includes
  • historical limit order updates
  • order add events
  • order update events
  • order delete events
Parameters:exchange_id • market_id • date • time_start • time_end • limit

Historical Order Updates

Unlike the current order book endpoint, which returns a reconstructed snapshot of the latest bids and asks, the historical endpoint returns raw limit order updates stored in FinFeedAPI flat files. These events capture changes to the order book as they occurred, including order additions, updates, and deletions.

Retrieval methods

Historical data can be requested for an entire trading day using the date parameter or for bounded time windows using time_start and time_end. For active markets, narrow time ranges and explicit limits are recommended to keep responses manageable.

Retrieval MethodDescription
Daily RetrievalReturns historical limit order updates for a specified date.
Custom Time RangeReturns historical order events between time_start and time_end.

According to the API documentation, filtering is performed using time_coinapi, while each returned record also includes the original exchange timestamp (time_exchange) for reference.

Related Endpoints

Order Book Data integrates naturally with the rest of the FinFeedAPI Prediction Markets ecosystem:

  • Prediction Market Exchanges
  • Prediction Market Listings
  • Active Market IDs
  • Trades & Quotes
  • OHLCV Time Series & Latest OHLCV Candles

Together, these APIs provide access to market discovery, liquidity, executed transactions, aggregated price history, and event-level order flow through a unified interface.

How Order Book Data Fits Into the FinFeedAPI Ecosystem

Order book data complements every other prediction market dataset available through FinFeedAPI. Because every dataset uses the same exchange_id and market_id identifiers, applications can move seamlessly between market discovery, liquidity analysis, transaction history, and historical analytics.

Typical integration workflow

  1. 1Supported Exchanges
  2. 2Market Listings
  3. 3Active Market IDs
  4. 4Current Order Book
  5. 5Historical Order Updates
  6. 6Trades, quotes, and OHLCV

Example API Requests

Retrieve the current order book snapshot for a market outcome:

bash
curl -X GET \
  "https://api.prediction-markets.finfeedapi.com/v1/orderbook/POLYMARKET/WILL-RAIN-YES/current" \
  -H "Authorization: YOUR_API_KEY"

Retrieve historical limit order updates:

bash
curl -X GET \
  "https://api.prediction-markets.finfeedapi.com/v1/orderbook/POLYMARKET/WILL-RAIN-YES/history?time_start=2025-01-01T12:00:00Z&time_end=2025-01-01T13:00:00Z&limit=100" \
  -H "Authorization: YOUR_API_KEY"

The historical endpoint supports either a full-day query using date or bounded requests using time_start and time_end, making it suitable for both historical backfills and targeted event replay.

REST, MCP & JSON-RPC

Prediction market order book data is available through every FinFeedAPI interface. Regardless of the interface, applications use the same exchange and market identifiers.

MCP Server

The hosted Prediction Markets MCP server exposes dedicated tools for retrieving current order books and historical order updates: orderbook_get_current and orderbook_get_history. The current tool returns a bid/ask snapshot, while the historical tool returns raw limit order events that can be used to reconstruct book state within downstream applications.

json
{
  "mcpServers": {
    "FinFeedAPI-Prediction-Markets": {
      "url": "https://api.prediction-markets.finfeedapi.com/mcp",
      "headers": {
        "X-APIKey": "YOUR_API_KEY_HERE"
      }
    }
  }
}

Compatible with Cursor, Claude Desktop, and other MCP-enabled AI applications.

JSON-RPC

Developers using JSON-RPC can access order books through the production proxy at https://api.prediction-markets.finfeedapi.com/jsonrpc.

JSON-RPC provides a thin proxy over the REST API, exposing the same order book resources, parameters, and response formats. Set method to v1/orderbook/{exchange_id}/{market_id}/current or v1/orderbook/{exchange_id}/{market_id}/history, and pass parameters through params. Successful JSON-RPC requests return the underlying REST payload in the result field.

Common Integration Patterns

Order book data supports live liquidity monitoring, historical reconstruction, and microstructure research from the same market identifiers.

Use CaseHow Order Book Data Is Used
Live Liquidity MonitoringRetrieve the latest bid and ask ladders for a market outcome.
Spread AnalysisMeasure bid-ask spreads using current order book snapshots.
Market Depth AnalyticsAnalyze available liquidity across multiple price levels.
Order Book ReconstructionReplay historical order additions, updates, and deletions to rebuild historical book state.
Market Microstructure ResearchStudy how order flow changes before trades are executed.
AI & Quantitative ResearchCombine event-level order updates with trades, quotes, and OHLCV datasets for model training and historical analysis.
Prediction Markets Order Books

Start Building with Prediction Market Order Book Data

Retrieve current order book snapshots and historical limit order updates through a unified API.

Monitor live market liquidity, replay historical order flow, reconstruct order book state, and combine event-level order updates with trades, quotes, and OHLCV data to build a complete view of prediction market activity.

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