# Kalshi Prediction Market Scraper: Live Event Odds (`scrapemint/kalshi-prediction-market-scraper`) Actor Live odds from Kalshi, the regulated US event contract exchange: sports, elections, economics, weather, and culture markets with yes/no prices, implied probability, volume, and open interest. Filter by category, keyword, or ticker. Keyless, no browser. Pay per market row. - **URL**: https://apify.com/scrapemint/kalshi-prediction-market-scraper.md - **Developed by:** [Ken M](https://apify.com/scrapemint) (community) - **Categories:** Business, News - **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Kalshi Prediction Market Scraper: Live Event Odds Live market data from Kalshi, the CFTC-regulated US event contract exchange. Every market is a real-money yes/no question - who wins the game, where the Fed sets rates, how hot the summer gets - and the price is the crowd's probability. This actor reads those markets through Kalshi's public API and gives you clean rows. ### What you get One row per market: | Field | Description | | --- | --- | | `eventTitle`, `outcome` | The question and the specific outcome this market prices | | `yesBid`, `yesAsk`, `noBid`, `noAsk` | Live order book, in dollars (0 to 1) | | `lastPrice` | Last trade price | | `impliedProbabilityPct` | Book midpoint (or last trade) as a percentage | | `volume`, `volume24h`, `openInterest` | Activity and positioning | | `openTime`, `closeTime`, `status`, `result` | Lifecycle | | `rules` | Exact resolution criteria | | `ticker`, `eventTicker`, `seriesTicker`, `category` | Identifiers for joins | ### Three ways to query 1. **Discovery** - pick `categories` (Politics, Economics, Sports, Financials, Climate and Weather, Culture, Crypto...) and optional `keywords`; the actor browses open events and returns matching markets. 2. **Event tickers** - exact events like `KXNEWPOPE-70`. 3. **Series tickers** - everything in a recurring series, like Fed decisions or monthly CPI. ### Typical uses - **Traders and arb hunters**: compare Kalshi prices against Polymarket and sportsbook lines. Pairs with our Polymarket Prediction Market Scraper for a two-exchange view. - **Researchers and journalists**: probability time series on elections, rates, and geopolitics - schedule the actor and build your own history. - **Dashboards and newsletters**: structured event odds without touching an exchange account. - **Sports analytics**: event contract prices on games as a sharp, regulated reference line. ### Pricing You pay per market row (`market_row`). The first 2 rows of every run are free. Unknown tickers and searches with no matches cost nothing. ### Input example ```json { "categories": ["Economics"], "keywords": ["Fed", "CPI", "inflation"], "onlyPriced": true, "minVolume": 100, "maxRows": 100 } ```` ### Notes - Data comes from Kalshi's public market-data API. No account, no API key, no browser. This actor reads prices; it does not trade. - Prices are dollars per contract that pays $1, so 0.63 means a 63% implied probability. - `onlyPriced` (default on) skips empty order books and long-dated combo markets that have never traded. - Kalshi rate limits are handled: the actor paces requests, retries once, and stops cleanly with partial data if limits persist. # Actor input Schema ## `categories` (type: `array`): Kalshi categories to browse, e.g. Politics, Economics, Sports, Financials, Climate and Weather, Science and Technology, Culture, World, Health, Companies, Crypto. Matched loosely. ## `keywords` (type: `array`): Only markets whose event title or outcome mentions one of these, e.g. Fed, inflation, Chiefs, Bitcoin. ## `eventTickers` (type: `array`): Exact Kalshi event tickers to fetch, e.g. KXNEWPOPE-70. Overrides categories and series. ## `seriesTickers` (type: `array`): Kalshi series tickers to fetch all markets from, e.g. KXFED, KXCPI. ## `status` (type: `string`): Open markets trade now; closed and settled are history. ## `onlyPriced` (type: `boolean`): Skip markets that have no bids and no trades yet (empty books, long-dated combos). ## `minVolume` (type: `integer`): Skip markets with lifetime volume below this. ## `maxRows` (type: `integer`): Cap on market rows returned. Controls total cost. ## Actor input object example ```json { "categories": [ "Economics", "Politics" ], "keywords": [], "eventTickers": [], "seriesTickers": [], "status": "open", "onlyPriced": true, "minVolume": 0, "maxRows": 100 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "categories": [ "Economics", "Politics" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapemint/kalshi-prediction-market-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "categories": [ "Economics", "Politics", ] } # Run the Actor and wait for it to finish run = client.actor("scrapemint/kalshi-prediction-market-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "categories": [ "Economics", "Politics" ] }' | apify call scrapemint/kalshi-prediction-market-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapemint/kalshi-prediction-market-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Kalshi Prediction Market Scraper: Live Event Odds", "description": "Live odds from Kalshi, the regulated US event contract exchange: sports, elections, economics, weather, and culture markets with yes/no prices, implied probability, volume, and open interest. Filter by category, keyword, or ticker. Keyless, no browser. Pay per market row.", "version": "0.1", "x-build-id": "EJkXX1Ypp4tbomOhB" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapemint~kalshi-prediction-market-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapemint-kalshi-prediction-market-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapemint~kalshi-prediction-market-scraper/runs": { "post": { "operationId": "runs-sync-scrapemint-kalshi-prediction-market-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapemint~kalshi-prediction-market-scraper/run-sync": { "post": { "operationId": "run-sync-scrapemint-kalshi-prediction-market-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "categories": { "title": "Categories (discovery mode)", "type": "array", "description": "Kalshi categories to browse, e.g. Politics, Economics, Sports, Financials, Climate and Weather, Science and Technology, Culture, World, Health, Companies, Crypto. Matched loosely.", "default": [], "items": { "type": "string" } }, "keywords": { "title": "Keywords (optional)", "type": "array", "description": "Only markets whose event title or outcome mentions one of these, e.g. Fed, inflation, Chiefs, Bitcoin.", "default": [], "items": { "type": "string" } }, "eventTickers": { "title": "Event tickers (optional)", "type": "array", "description": "Exact Kalshi event tickers to fetch, e.g. KXNEWPOPE-70. Overrides categories and series.", "default": [], "items": { "type": "string" } }, "seriesTickers": { "title": "Series tickers (optional)", "type": "array", "description": "Kalshi series tickers to fetch all markets from, e.g. KXFED, KXCPI.", "default": [], "items": { "type": "string" } }, "status": { "title": "Market status", "enum": [ "open", "closed", "settled" ], "type": "string", "description": "Open markets trade now; closed and settled are history.", "default": "open" }, "onlyPriced": { "title": "Only markets with prices", "type": "boolean", "description": "Skip markets that have no bids and no trades yet (empty books, long-dated combos).", "default": true }, "minVolume": { "title": "Min volume (contracts)", "minimum": 0, "type": "integer", "description": "Skip markets with lifetime volume below this.", "default": 0 }, "maxRows": { "title": "Max market rows per run", "minimum": 1, "maximum": 2000, "type": "integer", "description": "Cap on market rows returned. Controls total cost.", "default": 100 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```