A prediction market data API is a machine-readable interface that exposes prediction events, markets, order books, odds (implied probabilities), liquidity, trading activity, and resolution outcomes from platforms like Polymarket and Kalshi so builders can power odds dashboards, trading terminals, and analytics apps without building their own data pipelines.
How a Prediction Market Data API Works
At its core, a prediction market data API organizes information around events and markets. An event represents a real-world question (for example, "US recession by end of 2026?") and can contain one or multiple outcome markets. Each market has its own price, order book, and liquidity profile.
Prices in prediction markets are quoted as implied probabilities. On Polymarket, for instance, contracts trade between $0.01 and $0.99, where the price corresponds to the market’s probability of resolving "Yes." When the event resolves, the winning side pays out $1 per share and the losing side goes to $0.
A robust prediction market data API therefore does much more than return a single price. It typically exposes:
- Discovery data: lists of events and markets, with categories, tags, and filters.
- Market data: odds, last trade, daily volume, total volume, liquidity, and open interest.
- Order books: resting bids and asks, depth at each price level, and spread.
- Trade feeds: individual trades with timestamp, side, size, and participant identifiers.
- Resolution state: outcome, resolution time, and settlement details.
Codex mirrors the way platforms like Polymarket structure their own APIs, but normalizes data into a single GraphQL-style schema. For example, Codex’s predictionMarketBars returns OHLC price data plus volume, trades, unique traders, liquidity, bid/ask, and open interest, which is exactly what trading UIs and analytics dashboards need.
Why It Matters for Odds Dashboards and Trading Apps
For Codex’s customers—CTOs, lead engineers, and product teams building trading-adjacent UX—the key value of a prediction market data API is that it adds a probability layer on top of the crypto economy. Instead of just token prices, apps can show what the market thinks about elections, macro events, sports, and protocol milestones.
Platform pages like Polymarket’s "All Predictions" make this demand obvious. As of September 27, 2026, Polymarket lists 7,313 live markets, each with real-time odds, liquidity, daily volume, and resolution status. Builders creating odds dashboards, social trading tools, or portfolio views need to ingest and rank thousands of markets in real time.
Doing that directly from raw chain data is essentially impossible for most product teams. They would need to:
- Index event and market contracts for each protocol.
- Reconstruct order books and trade history.
- Track resolution outcomes and settlement.
- Maintain schema differences across multiple venues.
Codex’s prediction market data API abstracts all of this away. Engineering teams plug into Codex and immediately get:
- Trading-grade latency for odds and order books.
- Unified endpoints for events, markets, trades, and charts across Polymarket and Kalshi.
- Rich ranking signals like trending score, volume, liquidity, open interest, trades, and unique traders across multiple time windows (5m, 1h, 4h, 12h, 24h, 1w).
This is critical for high-traffic odds dashboards and trading interfaces where every millisecond and every correct data point matters. Codex’s infrastructure has already been proven at scale by powering apps like Coinbase, TradingView, Uniswap, Magic Eden, Rainbow, and others.
How It Differs from General Price Feeds
Prediction market data APIs are often confused with generic price feeds or crypto data APIs, but they serve a different job.
A typical price feed (for example, a token price API) focuses on:
- Spot prices and OHLC candles for assets.
- Market-wide volume and liquidity metrics.
- Token metadata and possibly holders and balances.
These feeds are ideal for wallets, DeFi dashboards, and portfolio apps. However, they do not natively understand the structure of prediction markets: events, outcome tokens, negative-risk groups, and resolution logic.
By contrast, a prediction market data API must:
- Model events and their related markets, not just assets.
- Track resolution outcomes and settlement (which markets pay $1 and which pay $0).
- Provide order book context (bids, asks, depth) and implied odds.
- Support trader analytics, such as trades and unique traders in a market.
Polymarket’s own docs highlight this distinction. They split their surfaces into Gamma discovery, CLOB market data, analytics, and WebSocket streams—underscoring that prediction market infra is about much more than price quotes.
Codex reflects this by exposing dedicated endpoints like predictionEvents, predictionMarkets, predictionTrades, and predictionMarketBars. This yields a complete view of what question is being asked, what odds the market assigns, how much capital is at risk, and how exactly traders are interacting with the market.
For Codex’s customers, the practical outcome is clear: you use Codex’s token and onchain data APIs for portfolios, charts, and balances; and you use Codex’s prediction APIs when you need live odds, market context, and resolution feeds integrated into the same app.
Related Terms and Common Confusions
Several terms sit near "prediction market data API" and are easy to mix up. It helps to be precise:
Prediction Market API vs. Prediction Market Data API
A prediction market API can encompass both data and execution (placing orders, creating markets, managing accounts). Platform-native APIs from Polymarket or Kalshi often include REST or WebSocket surfaces for both data and trading.
A prediction market data API is narrower: it focuses on the read-only data layer—events, markets, odds, order books, liquidity, trades, and resolution outcomes. Codex’s prediction endpoints are designed as a data API, not an execution layer, so they are ideal for analytics, dashboards, and trading front-ends that connect to venue-specific execution separately.
Price Oracle vs. Prediction Market Data API
A price oracle (for example, a DeFi oracle onchain) provides canonical price data to smart contracts. It is optimized for security, decentralization, and onchain consumption.
A prediction market data API is off-chain and optimized for UX and analytics, not onchain settlement. It’s about powering charts, rankings, and odds displays for human traders and consumer apps.
Crypto Market Data API vs. Prediction Market Data API
A crypto market data API focuses on standard assets: spot tokens, futures, and maybe options, with endpoints for candles, trades, and order books.
A prediction market data API focuses on event-linked outcome tokens, resolution mechanics, and implied probabilities—an extra semantic layer that general asset feeds do not handle.
Example: Powering a Polymarket-Based Frontend with Codex
To make this concrete, consider a team building a Polymarket odds dashboard and market-detail pages using Codex.
They want to:
- Show a scrollable list of top prediction markets by liquidity and volume.
- Display market cards with current odds, total volume, and daily volume.
- Offer detail pages with charts, recent trades, and order book depth.
- Surface resolution status when events close.
Here’s how they could use Codex’s prediction market data API:
-
Discover and rank events and markets
The frontend calls Codex’s event or market filters (for example,filterPredictionMarkets) to pull live markets from Polymarket. They can rank by volume, liquidity, open interest, trades, or unique traders across multiple windows. -
Render cards with odds and liquidity
For each market, Codex returns current price (implied probability), total volume, daily volume, and liquidity. This mirrors what Polymarket’s own pages show—for example, a single market like "US recession by end of 2026?" has generated $2.2M in total trading volume. -
Build trading-ready charts
On the market detail view, the app callspredictionMarketBarsto get OHLC candles plus volume, trades count, unique traders, liquidity, bid/ask, and open interest over time. This powers an interface similar to a trading terminal, but oriented around event probabilities. -
Show trade history and trader activity
The app usespredictionTradesto list recent trades, including trade type, maker, traderId, priceUsd, amountUsd, timestamp, transaction hash, protocol, and market context. This gives users more insight into how the crowd is moving odds. -
Handle resolution and settlement state
When events resolve, Codex’s data layer reflects the resolution state: which outcome token redeemed for $1, and which became worthless. The frontend can update the UI to mark markets as resolved, highlight the winning outcome, and archive historical performance.
All of this is delivered via Codex’s unified GraphQL-style API, so engineers don’t have to juggle Polymarket’s separate Gamma discovery, CLOB data, analytics, and WebSocket endpoints. For a deeper look at Polymarket’s native APIs and how Codex sits on top of them, see our in-depth guide: Polymarket API and Gamma Data: What Builders Get and How to Use It in Apps.
By relying on Codex as the onchain and prediction data layer, teams can focus on UX, ranking logic, and differentiated features—while Codex handles the complexity of indexing, normalizing, and serving trading-grade prediction market data across venues.
