# Prediction Market Odds API — Polymarket + Kalshi (`westerly_breaker/prediction-market-odds-api`) Actor Search or look up Polymarket and Kalshi prediction markets and get one unified JSON schema back: prices, volume, liquidity, order books, and de-vigged fair probabilities (multiplicative/power method). No API key needed — built for research, arbitrage-scanning, and AI agents. - **URL**: https://apify.com/westerly\_breaker/prediction-market-odds-api.md - **Developed by:** [Daniel Posztos](https://apify.com/westerly_breaker) (community) - **Categories:** AI, Agents, Automation - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 ## Prediction Market Odds API — Polymarket + Kalshi, De-vigged Fair Probabilities **SEO title:** Prediction Market Odds API — Polymarket & Kalshi Scraper, extract de-vigged probabilities as JSON **SEO description:** Search or look up Polymarket and Kalshi prediction markets and get one unified JSON schema back: prices, volume, liquidity, order books, and de-vigged fair probabilities (multiplicative/power method). No API key needed — built for research, arbitrage-scanning, and AI agents. One actor, one schema, two prediction market platforms. Query by keyword or by exact market ID, get back current prices AND the de-vigged "fair" probability for every outcome — the overround-adjusted number you actually want if you're comparing markets, building a model, or looking for mispriced longshots. ### Why this exists Polymarket (Gamma + CLOB APIs) and Kalshi (trade-api v2) both expose public, unauthenticated market data — but in two different shapes, with prices that still include the platform's own vig/overround. This actor: 1. queries both (or either) platform for markets matching a keyword, or fetches specific markets by ID, 2. normalizes them into one schema, 3. removes the vig with a standard de-vig method (multiplicative by default) so `devigged_prob` values for a market's outcomes actually sum to 1.0, 4. optionally attaches a top-of-book order book snapshot. No scraping, no anti-bot risk, no login — both platforms' public market-data endpoints are called directly (over HTTPS, no browser). ### Input | Field | Type | Default | Description | |---|---|---|---| | `query` | string | — | Free-text search keyword, e.g. `"bitcoin"`, `"2028 election"`. Use this OR `market_ids`. | | `market_ids` | array of strings | `[]` | Exact market IDs to fetch directly: Polymarket condition IDs (`0x...`) or slugs, and/or Kalshi tickers (e.g. `"KXBTCD-26JUL0517-T52999.99"`). Mixing IDs from both platforms in one list is fine — each platform only matches its own IDs. | | `platforms` | array of strings | `["polymarket", "kalshi"]` | Which platform(s) to query. | | `include_orderbook` | boolean | `false` | Attach a top-10-level order book per market. Bills an extra event (see pricing) and roughly doubles request count. | | `max_markets` | integer (1–200) | `20` | Total markets to return across all platforms combined. Split evenly between the requested platforms so one platform's abundance of matches (Polymarket tends to have far more markets matching a broad query than Kalshi) doesn't crowd out the other. | You must provide `query` and/or `market_ids` — an actor input with neither fails immediately with a message telling you exactly that. #### Worked example — input ```json { "query": "bitcoin", "platforms": ["polymarket", "kalshi"], "include_orderbook": false, "max_markets": 5 } ```` #### Worked example — output (2 of 5 items, real data) ```json [ { "platform": "polymarket", "market_id": "0x4863841fee98ae432b657dbad973cd5562e7fa6bab5e1a725ebd833723c9493d", "question": "Will the price of Bitcoin be above $50,000 on July 5?", "outcomes": [ { "name": "Yes", "price": 0.9995, "implied_prob": 0.9995, "devigged_prob": 0.9995 }, { "name": "No", "price": 0.0005, "implied_prob": 0.0005, "devigged_prob": 0.0005 } ], "volume": 132828.07, "liquidity": 126913.72, "close_time": "2026-07-05T16:00:00Z", "url": "https://polymarket.com/event/bitcoin-above-50k-on-july-5-2026", "scraped_at": "2026-07-05T14:57:29.520Z" }, { "platform": "kalshi", "market_id": "KXBTCMAX150-25-26OCT31-149999.99", "question": "When will Bitcoin cross $100k again? — Before October 2026", "outcomes": [ { "name": "Yes", "price": 0.055, "implied_prob": 0.055, "devigged_prob": 0.0524 }, { "name": "No", "price": 0.945, "implied_prob": 0.945, "devigged_prob": 0.9476 } ], "volume": 3678944.42, "liquidity": 1104224.42, "close_time": "2026-10-31T03:59:00Z", "url": "https://kalshi.com/markets/kxbtcmax150/kxbtcmax150-25-26oct31-149999.99", "scraped_at": "2026-07-05T14:57:29.522Z" } ] ``` With `include_orderbook: true`, each item additionally gets: ```json "orderbook": { "bids": [{ "price": 0.98, "size": 357.0 }, "... up to 10 levels"], "asks": [{ "price": 0.99, "size": 45095.0 }, "... up to 10 levels"] } ``` ### Output schema | Field | Type | Notes | |---|---|---| | `platform` | string | `"polymarket"` or `"kalshi"` | | `market_id` | string | Polymarket condition ID (or slug if no condition ID) / Kalshi ticker | | `question` | string | Human-readable market question | | `outcomes[].name` | string | e.g. `"Yes"` / `"No"`, or a named outcome for multi-way markets | | `outcomes[].price` | float (0–1) | Raw last/mid price, i.e. the platform's own implied probability including vig | | `outcomes[].implied_prob` | float (0–1) | Same as `price` — kept as its own explicit field per the output contract | | `outcomes[].devigged_prob` | float (0–1) or `null` | Vig-removed fair probability (multiplicative method); all outcomes of one market sum to 1.0. `null` only if de-vig math wasn't possible (e.g. a single-outcome market) | | `volume` | float or `null` | Platform-reported traded volume | | `liquidity` | float or `null` | Platform-reported liquidity/open interest | | `close_time` | string (ISO 8601) or `null` | Market close/expiration time | | `url` | string or `null` | Link to the market on the platform's site | | `scraped_at` | string (ISO 8601) | When this actor fetched the data | | `orderbook` | object, only if `include_orderbook: true` | `{bids: [{price, size}], asks: [{price, size}]}`, top 10 levels each | ### Pricing (pay-per-event) | Event | Price | When it's charged | |---|---|---| | `market-result` | $0.003 | Once per market returned | | `orderbook-snapshot` | $0.02 | Once per market, only when `include_orderbook: true` | Plus Apify's own `apify-actor-start` synthetic event (first 5 seconds of compute free, platform-managed — never charged from this actor's code). **Example:** 100 markets, no order books: `100 × $0.003 = $0.30`. 100 markets + order books on 10 of them: `$0.30 + 10 × $0.02 = $0.50`. If a run's cost would exceed the `Max total charge USD` you set for it, the actor stops producing further results at exactly that point — it never crashes and never produces unbilled/"free" results past the limit. ### Error messages - **No `query` and no `market_ids`:** *"Missing search criteria: provide either 'query' ... or 'market\_ids' ..."* — add one of the two fields. - **Unsupported `platforms` value:** *"'platforms' contains unsupported value(s) \[...]. Supported values are: \['kalshi', 'polymarket']."* — fix the typo/remove the entry. - **`max_markets` out of range:** *"'max\_markets' must be between 1 and 200, got N."* — pick a value in range. - **Wrong type for any field** (e.g. `query` as a number, `market_ids` as a bare string instead of an array): the message states the expected type and shows a corrected example. - **0 results with otherwise valid input:** not an error — the run succeeds, but the log has an explicit `WARNING: 0 results produced despite valid input (...)` line and the run's status message says so, so this is never a silent/invisible "nothing happened." ### Known limitations (documented, not hidden) - **Kalshi has no public full-text market search endpoint.** `query` search against Kalshi resolves by substring-matching the query against the ~11k-entry `/series` catalog's titles/tickers (fetched once per run, cached in-memory for that run), then lists open markets for matching series. This is adequate for the actor's per-run cost/latency budget; a future improvement could cache the catalog in the key-value store across runs. - **Order books are attached per-market, not per-outcome.** For binary Yes/No markets this is the whole picture (No is fully determined by Yes); for a multi-outcome market, only the first outcome's book is attached. - **`market_ids` mixing platforms:** the input is a single flat list rather than per-platform lists, so an ID that doesn't belong to a requested platform simply yields nothing for that platform — this is intentional (see Input table), not an error. ### Data sources (public, no API key, no scraping) - Polymarket Gamma API: `https://gamma-api.polymarket.com/public-search`, `/markets` - Polymarket CLOB API: `https://clob.polymarket.com/book` - Kalshi trade-api v2: `https://api.elections.kalshi.com/trade-api/v2/{series,events,markets}` All are the same public, unauthenticated endpoints the platforms' own web UIs call — no login, no key, no ToS-risk scraping. # Actor input Schema ## `query` (type: `string`): Keyword(s) to search for across market questions/titles, e.g. "bitcoin", "2028 election", "Fed rate cut". Use this OR 'market\_ids' below — you don't need both. Leave empty if you already know the exact market ID(s) you want (use 'market\_ids' instead). ## `market_ids` (type: `array`): Specific market identifiers to fetch directly instead of searching. Accepts Polymarket condition IDs (start with "0x...") or slugs (e.g. "bitcoin-above-50k-on-july-5-2026"), and/or Kalshi market tickers (e.g. "KXBTCD-26JUL0517-T52999.99"). Every requested platform tries every ID in this list; an ID that doesn't belong to a given platform simply returns nothing for that platform (not an error) — so it's fine to mix Polymarket and Kalshi IDs in one list when 'platforms' includes both. Leave empty and use 'query' to search instead. ## `platforms` (type: `array`): Which prediction market platform(s) to query. Allowed values: "polymarket", "kalshi". Defaults to both. Set to just one value to skip the other platform entirely (faster, cheaper). ## `include_orderbook` (type: `boolean`): If true, additionally fetches the top-of-book order book (up to 10 price levels per side) for every returned market. This bills one extra 'orderbook-snapshot' event per market (see README pricing) and roughly doubles the number of upstream HTTP requests — leave this false unless you specifically need bid/ask depth rather than just the last traded price. ## `max_markets` (type: `integer`): Maximum number of markets to return in total, across all requested platforms combined. Must be between 1 and 200. Each market returned bills one 'market-result' event, so lowering this caps cost; raise it (up to 200) for broad research scans. ## Actor input object example ```json { "query": "bitcoin", "market_ids": [], "platforms": [ "polymarket", "kalshi" ], "include_orderbook": false, "max_markets": 20 } ``` # Actor output Schema ## `markets` (type: `string`): Unified prediction-market items (one per market) with de-vigged fair probabilities, stored in the run's default dataset. # 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 = { "query": "bitcoin" }; // Run the Actor and wait for it to finish const run = await client.actor("westerly_breaker/prediction-market-odds-api").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 = { "query": "bitcoin" } # Run the Actor and wait for it to finish run = client.actor("westerly_breaker/prediction-market-odds-api").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 '{ "query": "bitcoin" }' | apify call westerly_breaker/prediction-market-odds-api --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=westerly_breaker/prediction-market-odds-api", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Prediction Market Odds API — Polymarket + Kalshi", "description": "Search or look up Polymarket and Kalshi prediction markets and get one unified JSON schema back: prices, volume, liquidity, order books, and de-vigged fair probabilities (multiplicative/power method). No API key needed — built for research, arbitrage-scanning, and AI agents.", "version": "0.1", "x-build-id": "lIie0xriTetCtKPTo" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/westerly_breaker~prediction-market-odds-api/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-westerly_breaker-prediction-market-odds-api", "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/westerly_breaker~prediction-market-odds-api/runs": { "post": { "operationId": "runs-sync-westerly_breaker-prediction-market-odds-api", "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/westerly_breaker~prediction-market-odds-api/run-sync": { "post": { "operationId": "run-sync-westerly_breaker-prediction-market-odds-api", "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": { "query": { "title": "Search query", "type": "string", "description": "Keyword(s) to search for across market questions/titles, e.g. \"bitcoin\", \"2028 election\", \"Fed rate cut\". Use this OR 'market_ids' below — you don't need both. Leave empty if you already know the exact market ID(s) you want (use 'market_ids' instead)." }, "market_ids": { "title": "Market IDs", "type": "array", "description": "Specific market identifiers to fetch directly instead of searching. Accepts Polymarket condition IDs (start with \"0x...\") or slugs (e.g. \"bitcoin-above-50k-on-july-5-2026\"), and/or Kalshi market tickers (e.g. \"KXBTCD-26JUL0517-T52999.99\"). Every requested platform tries every ID in this list; an ID that doesn't belong to a given platform simply returns nothing for that platform (not an error) — so it's fine to mix Polymarket and Kalshi IDs in one list when 'platforms' includes both. Leave empty and use 'query' to search instead.", "items": { "type": "string" } }, "platforms": { "title": "Platforms", "type": "array", "description": "Which prediction market platform(s) to query. Allowed values: \"polymarket\", \"kalshi\". Defaults to both. Set to just one value to skip the other platform entirely (faster, cheaper).", "items": { "type": "string", "enum": [ "polymarket", "kalshi" ], "enumTitles": [ "Polymarket", "Kalshi" ] }, "default": [ "polymarket", "kalshi" ] }, "include_orderbook": { "title": "Include order book", "type": "boolean", "description": "If true, additionally fetches the top-of-book order book (up to 10 price levels per side) for every returned market. This bills one extra 'orderbook-snapshot' event per market (see README pricing) and roughly doubles the number of upstream HTTP requests — leave this false unless you specifically need bid/ask depth rather than just the last traded price.", "default": false }, "max_markets": { "title": "Max markets", "minimum": 1, "maximum": 200, "type": "integer", "description": "Maximum number of markets to return in total, across all requested platforms combined. Must be between 1 and 200. Each market returned bills one 'market-result' event, so lowering this caps cost; raise it (up to 200) for broad research scans.", "default": 20 } } }, "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 } } } } } } } } } } ```