Kalshi Markets Scraper

Kalshi Markets Scraper: prediction market prices, volume and settlement, as rows

Pull Kalshi's markets into a table: the yes and no quotes, the last trade, volume, open interest, when trading closes and how it settled. Ask by city, by Kalshi category, by tag, or by series, event or market ticker. The orderbook and recent trades come along if you want them.

Prices carry Kalshi's own 15-second cache header, so treat a row as up to 15 seconds old rather than as a live tick.

📈 What Kalshi Markets Scraper does

It runs each search you give it and writes one row per market. A market is a single yes-or-no contract, an event is one occurrence of a question, and a series is the question Kalshi asks over and over, so KXHIGHNY is the series, KXHIGHNY-26SEP14 the event and KXHIGHNY-26SEP14-B81.5 one bracket inside it.

Temperature markets get extra treatment. Kalshi runs daily high and low temperature brackets in 24 US cities, six brackets a day. Pick cities and every bracket comes back with the weather station it settles on, the bracket edges in whole degrees, the settled temperature once there is one, and a forecast for that station and day: the number, whether it lands inside the bracket, and by how many degrees it misses. Today and the next 15 days get a forecast. Past days do not.

Combo markets, where several outcomes are bundled into one contract, are left out by default. Kalshi generates them in very large numbers and they would swamp everything else.

📥 What you give it

{
  "status": "open",
  "weatherCities": ["New York City", "Chicago", "Miami"],
  "weatherKind": "both",
  "addForecast": true,
  "minVolume24h": 100,
  "maxMarkets": 500
}

📤 What you get back

A real temperature row from a recent run:

{
  "ticker": "KXHIGHNY-26SEP14-T81",
  "eventTicker": "KXHIGHNY-26SEP14",
  "seriesTicker": "KXHIGHNY",
  "title": "Will the maximum temperature be >81° on Sep 14, 2026?",
  "yesSubTitle": "82° or above",
  "eventTitle": "Highest temperature in New York City on Sep 14, 2026?",
  "category": "Climate and Weather",
  "status": "active",
  "statusGroup": "open",
  "result": null,
  "marketType": "binary",
  "strikeType": "greater",
  "floorStrike": 81,
  "capStrike": null,
  "yesBid": 0,
  "yesAsk": 0.01,
  "noBid": 0.99,
  "noAsk": 1,
  "lastPrice": 0.01,
  "yesAskSize": 11128.31,
  "volume": 1186.01,
  "volume24h": 1186.01,
  "openInterest": 1186.01,
  "openTime": "2026-09-13T14:00:00Z",
  "closeTime": "2026-09-15T05:00:00Z",
  "settlementValue": null,
  "isCombo": false,
  "rulesPrimary": "If the maximum temperature recorded at New York City (CLINYC) for Sep 14, 2026, is greater than 81° fahrenheit according to The Weather Company, then the market resolves to Yes.",
  "url": "https://kalshi.com/markets/kxhighny",
  "fetchedAt": "2026-09-14T05:45:15.320Z",
  "city": "New York City",
  "stationCode": "CLINYC",
  "stationName": "New York City, Central Park",
  "weatherDate": "2026-09-14",
  "temperatureKind": "high",
  "bracketLowF": 82,
  "bracketHighF": null,
  "settledTempF": null,
  "forecastTempF": 71.8,
  "forecastInBracket": false,
  "forecastDistanceF": 10
}

Cut short here: the row also carries noSubTitle, eventSubTitle, yesBidSize, previousYesBid, previousYesAsk, previousPrice, notionalValue, expectedExpirationTime, latestExpirationTime, settlementTime, expirationValue, canCloseEarly, archived, forecastSource and forecastFetchedAt.

🧾 Reading the output

Run it with nothing set and you get that one sample row, a real temperature bracket with its forecast attached.

The forecast, the orderbook and the trades ride along with the market row. They are not charged separately.

There are no diagnostic rows. The status message leads with the result, like "Returned N markets (M temperature brackets, K with a forecast)", then names what was set aside and why. RUN_REPORT in the key-value store holds the long version: one entry per search with its status and page count, skipped counts by reason, tickers Kalshi did not recognise, and where the archive cutoff fell.

Two dataset views are set up, overview and weather, so the temperature fields have somewhere sensible to land in a spreadsheet.

▶️ How to run it

1. Open Kalshi Markets Scraper and click Try for free. 2. For temperature markets, pick Cities and leave Add the forecast on. 3. For anything else, pick Categories, or paste tickers into Series tickers, Event tickers or Market tickers. 4. Set Market status and Maximum markets, then click Start. 5. Download the dataset as JSON, CSV or Excel, or read it from the Apify API.

💰 How much does it cost?

$0.92 per 1,000 markets. Flat on every Apify plan, no volume tiers.

You pay per market row delivered. Markets your filters set aside, repeats, a ticker Kalshi does not know, a search that could not be read, and the sample row are all free. The forecast, orderbook and trades add nothing on top of the market row.

💡 What people use it for

• Watching the temperature brackets for a city against the forecast, to see where the two disagree.
• Pulling a settled series with closeFrom and closeTo to build a history of how a question paid.
• Screening the open board by minVolume24h to find the markets that are actually trading.
• Feeding a model with yes and no quotes plus open interest, on a schedule, keyed on ticker.
• Reading the orderbook on a handful of markets to see how deep the resting bids go.

🚧 What it does not do

• No trading. It reads public market data. It does not place, hold or cancel anything.
• Prices are up to 15 seconds old, because that is what Kalshi's own cache header says.
• A wide walk stops at 120 pages, about 120,000 markets. The open board without combos was

119,253, so anything broader than that gets cut off with a message.

• A category search does not reach the archive. Old settled markets need a series, event,

ticker or city.

• Combo markets arrive thin. No event title, series, category or link, because Kalshi leaves

multivariate events out of the events endpoint.

• If the forecast service does not answer, brackets come back without forecast fields and are

still charged as markets. The status says how many.

• The city list is fixed at Kalshi's 24 US cities. A new one Kalshi adds arrives as a plain

market with no weather fields until the list is updated here.

• An archived bracket can be missing its settled value, so settledTempF is null. One row in

552 on a recent archive read.

• Trades cost a request each, which is why a run with trades on stops at 2,000 markets.

🧭 Which markets scraper do you need?

❓ Questions people ask

Do I need a Kalshi account? No. No login and no API key.

How do I get one day's temperature brackets for a city? Set Cities to that city and Closes on or after and Closes on or before to the day you want.

Why is a row's category not the one I searched? category belongs to the event, and a series can live under more than one. 15 of 300 rows found through Economics came back labelled Financials, Science and Technology, Politics or Elections.

Can I get historical settled markets? Yes, for a series, event, ticker or city. Set Market status to settled and push Closes on or after back.

Why did my wide search stop early? Either Maximum markets or the 120-page walk limit. The status message says which.

Is scraping Kalshi legal? This reads Kalshi's own public market data with no account. Kalshi's terms govern what you may do with it, so read them against your plan. Apify's write-up on scraping and the law is a starting point, and we are not lawyers.

🆘 If something breaks

Open the Issues tab on the actor page. Send the run ID and the tickers or cities you used. The status message and RUN_REPORT name which search fell short.