Introduction to Prediction Market APIs: What Developers Need to Know
A practical guide to prediction market APIs — what they are, why the data is fragmented, and how to start building on Kalshi, Polymarket, and Novig in minutes.
What are prediction markets?
Prediction markets are platforms where participants buy and sell contracts based on the outcome of future events. The price of a contract reflects the collective probability that an event will occur. If a contract trades at $0.54, the market believes there is roughly a 54% chance of that outcome happening.
Platforms like Polymarket, Kalshi, and Novig have grown significantly over the past few years, covering everything from elections and economic indicators to sports outcomes and geopolitical events. They have become a valuable signal for researchers, journalists, traders, and developers who want real-time crowd-sourced probability estimates on just about anything.
The problem with prediction market data today
Every prediction market platform is a silo. Polymarket uses its own smart contract identifiers. Kalshi has its own ticker system. Novig uses its own market IDs. PredictIt uses numeric IDs. The same underlying event — say, who wins the 2028 US presidential election — can appear across five platforms with five completely different identifiers, schemas, and update frequencies.
For a developer who wants to build a cross-platform odds comparison tool, an arbitrage scanner, or a consensus probability model, this fragmentation is a serious problem. You end up writing five different API integrations, normalizing five different schemas, handling five different rate limits, and maintaining five brittle pipelines just to get clean data.
What a prediction market API should do
A good prediction market API solves the fragmentation problem. It should normalize data across platforms so that a market always has the same fields regardless of where it comes from. It should resolve the same underlying event across platforms so you can compare apples to apples. And it should handle the infrastructure concerns — rate limiting, caching, uptime — so you don't have to.
Key things to look for when evaluating a prediction market API:
• Normalized schema — every market should have consistent fields: title, probability, volume, platform, resolution date.
• Cross-platform entity resolution — the same event matched across Polymarket, Kalshi, and other platforms.
• Real-time and historical data — both live prices and historical tick data for backtesting.
• REST and WebSocket access — REST for pulling data on demand, WebSocket for live streaming.
• Reliable uptime — data infrastructure should not be your problem.
Use cases developers are building
The range of things being built on prediction market data is broader than most people expect.
Arbitrage tools scan for price discrepancies across platforms on the same event. If Polymarket prices an event at 54% and Kalshi prices it at 58%, there may be a profitable trade available. Automated scanners need real-time cross-platform data to surface these windows before they close.
Consensus models aggregate probabilities across platforms to produce a single reference price, stripping out platform-specific liquidity effects and producing a cleaner signal.
ML and quant models use historical resolution data as labeled training sets. Every resolved market is a labeled outcome — a ground truth that can be used to train models predicting future events.
Platform builders use prediction market data as a foundation for their own products — embedding live market probabilities, building dashboards, or creating new interfaces on top of existing liquidity.
Getting started with Prediction Markets API
Prediction Markets API provides a single unified endpoint for prediction market data across Polymarket, Kalshi, Novig, and more. You get a normalized schema, cross-platform entity resolution, real-time and historical data, and both REST and WebSocket access — all through one integration.
The free plan gives you access to 10k objects per month across three platforms with no time limit — enough to prototype, experiment, and validate your use case before committing to a paid plan.
To get started, grab a free API key and make your first call in under a minute:
curl https://api.predictionmarketapi.com/v1/markets \ -H "Authorization: Bearer YOUR_API_KEY" \ -d platforms=polymarket,kalshi \ -d market_status=open
Full documentation, starter scripts, and SDK guides are available in the docs.