Best Prediction Market Data API (2026)

What makes a prediction market data API good?

Four things, and only one of them is the thing most comparisons lead with.

Coverage. Not a headline count, but which venues, and whether adding one costs you an engineering week. Two venues is a starting point rather than a data layer.

Depth, not just price. A feed that hands you a single number per market is telling you what something is worth in theory. A feed that hands you the bid, the ask and the size behind them is telling you what you can actually do.

Latency you can specify. Polling is fine for a dashboard and useless for anything competitive. If there is no stream, you have a reporting tool rather than a trading input.

A shape that stays still. Venues change their APIs. The value of an aggregation layer is that those changes land on somebody else's desk.

Should you just use each venue's API directly?

Sometimes, and it is worth being straight about when.

If you trade one venue, go direct. Kalshi and Polymarket both publish real documentation and neither charges for market data. Adding a layer to read one book is complexity you are not being paid for.

It stops being sensible around the third venue. Each one brings its own authentication, its own ticker format, its own pagination, its own rate limit policy and its own idea of what a market object contains. None of that is hard. It is just permanent, because it never compresses: five venues is five sets of quirks to keep current, forever, and the work arrives on their schedule rather than yours.

Kalshi's fixed point migration in March 2026 is the clean example. Integer yes_bid and yes_ask fields were removed in favor of yes_bid_dollars, yes_ask_dollars and volume_fp. Anyone holding a direct integration rewrote their parser that week. Anyone reading through a normalized layer did not notice.

Why do midpoints break a data pipeline?

Because a midpoint is an average of two numbers and one of them is frequently missing.

Across 5,000 live Kalshi markets, 18.1% had no bid at all. Not a wide bid. No bid. On those markets the midpoint is arithmetic performed on a blank, and on a Kalshi binary the NO ask is 100 minus the YES bid, so a zero YES bid puts the NO leg at a full 100 cents against a 100 cent payout.

The problem concentrates exactly where a scanner looks most promising. Under 5 cents, 41% of markets had no bid at all. At 25 to 50 cents, none did. Cheap longshots look like free money precisely because nobody is standing on the other side of them.

Spread tells the same story about liquidity rather than error. The median on two sided books was 5.1 cents, but that figure moves with activity.

The widest books measured were scalar economic markets, with KXUSCPIYEAR at 57 cents. That is not mispricing, it is two far apart opinions and nothing in between.

One unit warning while you compare venues. Kalshi volume is counted in contracts and Polymarket volume in US dollars. They describe different things, so never divide one by the other.

How do you stream live prices?

Poll for a dashboard, stream for anything that has to act. Predictefy exposes a WebSocket at /v1/stream, and the Free plan opens two of them alongside 60 requests a minute.

curl -H "Authorization: Bearer pk_live_..." https://data.predictefy.com/api/kalshi/{verb}

curl -H "Authorization: Bearer pk_live_..." https://data.predictefy.com/api/smarkets/{verb}

What does it cost?

The line worth knowing: the arbitrage API is free. It is not a Builder unlock, and paid tiers buy throughput rather than a different set of prices. If your question is whether a gap exists between two venues right now, the Free plan answers it.

How do you place an order once you have the data?

Through a separate service, deliberately. Execution is isolated and non custodial, at its own origin rather than the reads API, under /v1/exec/{venue}/orders/... for build, submit, cancel, modify and refresh.

Three properties matter more than the routes. Every write takes an Idempotency-Key, so a retry after a timeout resolves to the same order instead of opening a second position at a worse price. Building an order is not metered, so you can rehearse the whole path before spending anything, and credits are charged only on submit, cancel and modify. Default caps are 100 USD per order and 1,000 USD per key per rolling 24 hours.

Orders are signed client side with your own venue credentials, so key custody stays with you and the layer never holds the ability to trade on your behalf. Balances stay on your side too.

What can you build on top of it?

Three routes in, depending on how much code you want to write.

Raw HTTP. A bearer token and /api/{venue}/{verb} is the whole surface. Any language with an HTTP client works, and there is nothing to install.

The SDKs. @predictefy/sdk and @predictefy/mcp are published on npm at 1.0.0-beta.3, and predictefy is on PyPI at 1.0.0b2. All three are available in beta and publicly installable. Pin exact versions when you install, since the latest tag points at a beta.

The MCP server. npx -y @predictefy/mcp puts prediction market data in front of an agent in plain language. It is MIT licensed and holds one rule worth quoting: no tool both builds and submits an order, so a badly phrased question cannot place a trade.

Historical data is stored across 11 venues, which covers the pairs most backtests are built on. Check the venues your strategy depends on before you commit to a long backtest, the same way you would with any data source.

Frequently Asked Questions