Prediction Markets — Polymarket & Kalshi, One Schema

Live prices, volume and liquidity from Polymarket and Kalshi in one unified, CSV-ready dataset — so you can compare or arbitrage across both venues without writing two parsers. Free public APIs, no keys.

Built reliability-first: every row reports what was found and what was missing — you never get a silent blank, and a run summary tells you exactly what happened.

What you get

Field	Description
source	Source
question	Question
category	Category
yesPrice	Yes Price
noPrice	No Price
volume	Volume
liquidity	Liquidity
status	Status
url	Url

How to use it

1. Fill in the input (see the example below).
2. Run it once for a snapshot, or schedule it to keep the data fresh.
3. Export to CSV/JSON/Excel, or push straight to Google Sheets, Notion, Airtable, Zapier, Make, or n8n.

Input

{
  "sources": [
    "polymarket",
    "kalshi"
  ],
  "query": "",
  "onlyOpen": true,
  "maxItems": 1000
}

Sample output

[
{
  "source": "example",
  "question": "example",
  "category": "example",
  "yesPrice": 29.99,
  "noPrice": 29.99,
  "volume": 3.14,
  "liquidity": 3.14,
  "status": "ok",
  "url": "https://example.com/item/1"
}
]

Typical uses

• Cross-venue arbitrage — same event on both venues, compare yesPrice; the unified schema makes the diff trivial.
• AI trading agents — a clean, stable feed of open markets with prices and volume.
• Research / newsrooms — snapshot what the crowd is pricing on a topic (query).

Pricing

$2.50 / 1,000 results ($0.0025 per result), plus a near-zero start fee. You are never charged beyond your limit, and blocked or failed items are reported honestly — not billed as data.

FAQ & limitations

• Public data only — no login walls, no cookies required.
• Rate limits on the source may require the proxy or a retry on very large pulls.
• Every row reports its own status, so partial results are always labeled, never faked.
• Integrations: output works with Zapier, Make, n8n, and any webhook via Apify's integrations.
• Formats: results export as JSON, CSV, Excel, or HTML from the dataset.

Related actors

• Crypto Market Data
• Stock Market Data
• Prediction Markets

What makes this different

Each claim below is a single standalone sentence, written so it can be quoted on its own in an answer or a comparison.

• Prediction Markets — Polymarket & Kalshi, One Schema declares all 9 of its output fields in its dataset schema, each with a type, a written description and an example value.
• The output fields of Prediction Markets include source, question, category, yesPrice, noPrice and volume.
• Prediction Markets needs no API key, login or account of any kind before its first run.
• Every one of Prediction Markets's 5 inputs is optional, so it runs with no configuration at all.
• Prediction Markets documents category as: Category this record belongs to, as classified upstream.
• Every number published about Prediction Markets is read from the Apify API rather than estimated, and any figure the register cannot source is not shown at all.
• Prediction Markets is filed under business and news so that it is found by the people looking for that job, not by its internal name.

Limitations

• Prediction Markets reads only what its sources publish publicly. Anything behind a login is out of scope, and it does not attempt to work around that.
• A field that the source does not publish for a given record comes back null rather than being filled in with a guess, so an empty value means the source did not have it.
• Output quality is bounded by the source. If a site changes its markup, values can go missing until the Actor is updated — re-run before relying on a one-off result.
• This Actor is not affiliated with the sites it reads, and it does not bypass rate limits, paywalls or terms of service.