# Probablemarket Pool Details Spider (`getdataforme/probablemarket-pool-details-spider`) Actor Scrape comprehensive prediction market data from Probable Markets event pages with this Apify Actor. Extracts event metadata, market questions, trading volumes, liquidity, and descriptions into clean JSON. Supports batch processing, ensures high reliability and speed without API dependencies.... - **URL**: https://apify.com/getdataforme/probablemarket-pool-details-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 ### Description Scrape comprehensive prediction market data from Probable Markets event pages with this Apify Actor. Extracts event metadata, market questions, trading volumes, liquidity, and descriptions into clean JSON. Supports batch processing, ensures high reliability and speed without API dependencies.... --- ## Probablemarket Pool Details Spider ### Introduction The Probablemarket Pool Details Spider is an Apify Actor designed to scrape comprehensive details from Probable Markets event pages. It extracts structured data about prediction markets, including event metadata, market questions, trading volumes, liquidity, and descriptions, enabling users to gather insights into speculative trading activities. This tool is ideal for researchers, analysts, and developers needing automated access to Probable Markets data for analysis or integration. ### Features - **Comprehensive Data Extraction**: Scrapes detailed event and market information, including IDs, titles, volumes, liquidity, and descriptions from Probable Markets URLs. - **Structured JSON Output**: Produces clean, machine-readable JSON data with nested objects for events and their associated markets. - **Flexible URL Input**: Accepts multiple URLs for batch processing, allowing efficient scraping of multiple events in a single run. - **High Reliability**: Handles web scraping with robust error handling to ensure data integrity even on dynamic pages. - **Fast Performance**: Optimized for quick execution, processing URLs concurrently to minimize runtime. - **No API Dependencies**: Directly scrapes web pages, avoiding rate limits or API access requirements. - **Customizable**: Supports custom URL lists for targeted data collection on specific events or markets. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|----------|----------|-----------------------------------------------------------------------------|---------| | Urls | Array of Strings | Yes | A list of URLs from Probable Markets event pages to scrape. Must be valid HTTPS URLs matching the pattern. Minimum 1 URL required. | ["https://probable.markets/event/usdai-fdv-above-one-day-after-launch?market=897", "https://probable.markets/event/based-fdv-above-one-day-after-launch?market=715"] | ### Example Usage #### Input Example ```json { "Urls": [ "https://probable.markets/event/based-fdv-above-one-day-after-launch?market=715", "https://probable.markets/event/opinion-fdv-above-one-day-after-launch?market=587" ] } ```` #### Output Example ```json [ { "event_id": "301", "slug": "based-fdv-above-one-day-after-launch", "title": "Based FDV above ___ one day after launch?", "created_at": "2026-01-13T15:57:49.881Z", "active": true, "ended": false, "liquidity": "2686.0335299999997", "volume": "46271325.00000000", "volume_24hr": 0, "markets": [ { "market_id": "715", "question": "Based FDV above $1B one day after launch?", "question_id": "0x72d47001bcf8644e4e365ee763a3e02544af2cd6925711d93c244dfd8f0adfcf", "volume_24hr": "24408581.00000000", "liquidity": "1048.785450", "active": true, "closed": false, "start_date": "2026-01-13T16:00:00.000000Z", "end_date": "2027-01-01T05:00:00Z", "icon": "https://locales.probable.markets/images/9102d1c48ef7b35c89decd09da5ad75cd0c2c6ab67f44d64d58b4396c57c1501.jpg", "description": "This market will resolve to \"Yes\" if the Fully Diluted Valuation of Based's token is greater than the value specified in the title 1 day after launch. Otherwise, the market will resolve to \"No.\"\n\nThe token must be actively, publicly transferable and tradable to be considered a launch.\n\n\"1 day after launch\" is defined as 4:00 PM ET on the calendar day following launch. The resolution source for this market is the most liquid price source available. If Based (https://x.com/BasedOneX) doesn't launch a token by December 31, 2026, 11:59 PM ET, this market will resolve to \"No\"." } ], "actor_id": "fF6YS7drCnzhe0gEn", "run_id": "w5IpYd4tf3IoFYPJN" } ] ``` ### Use Cases - **Market Research**: Analyze trading volumes and liquidity across multiple prediction markets to identify trends in speculative investments. - **Competitive Intelligence**: Monitor competitor events on Probable Markets for insights into market sentiment and pricing strategies. - **Price Monitoring**: Track FDV predictions for cryptocurrencies like XRP or tokens from projects like Based and Opinion. - **Content Aggregation**: Collect detailed market descriptions and questions for content creation or reporting on emerging trends. - **Academic Research**: Gather data for studies on prediction markets, behavioral economics, or cryptocurrency valuation models. - **Business Automation**: Integrate scraped data into dashboards or alerts for real-time monitoring of market activities. ### Installation and Usage 1. Search for "Probablemarket Pool Details Spider" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters by providing a list of URLs. 4. Click "Start" to begin extraction. 5. Monitor progress in the log. 6. Export results in your preferred format (JSON, CSV, Excel). ### Output Format The output is a JSON array of objects, each representing an event. Key fields include: - `event_id`: Unique identifier for the event. - `slug`: URL-friendly event name. - `title`: Event title. - `created_at`: Creation timestamp. - `active` and `ended`: Status flags. - `liquidity` and `volume`: Trading metrics. - `markets`: Array of market objects with details like `market_id`, `question`, `volume_24hr`, `liquidity`, `active`, `closed`, dates, `icon`, and `description`. - `actor_id` and `run_id`: Metadata from the scraping run. This structure allows easy parsing for analysis or integration. ### Error Handling The Actor includes built-in error handling for invalid URLs, network issues, or page changes. Failed URLs are logged with details; successful extractions continue. If a page is unavailable, the Actor skips it and proceeds. ### Rate Limiting and Best Practices Apify handles rate limiting automatically. For best results, limit to 10-20 URLs per run to avoid overloading. Respect Probable Markets' terms of service and avoid excessive requests. ### Limitations and Considerations Data accuracy depends on Probable Markets' site structure; changes may require updates. Output is limited to publicly available information. Not suitable for real-time trading due to scraping delays. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: https://getdataforme.com/contact/ We're here to help you get the most out of this Actor! *** # Actor input Schema ## `Urls` (type: `array`): The urls for the spider. ## Actor input object example ```json { "Urls": [ "https://probable.markets/event/usdai-fdv-above-one-day-after-launch?market=897", "https://probable.markets/event/based-fdv-above-one-day-after-launch?market=715", "https://probable.markets/event/will-satoshi-move-any-bitcoin-in-2026", "https://probable.markets/event/opinion-fdv-above-one-day-after-launch?market=587", "https://probable.markets/event/what-price-will-msft-hit-in-february-2026?market=1104", "https://probable.markets/event/what-price-will-xrp-hit-in-february-2026?market=1348", "https://probable.markets/event/what-price-will-aapl-hit-in-february-2026?market=1142" ] } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/probablemarket-pool-details-spider").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 = {} # Run the Actor and wait for it to finish run = client.actor("getdataforme/probablemarket-pool-details-spider").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 '{}' | apify call getdataforme/probablemarket-pool-details-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/probablemarket-pool-details-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Probablemarket Pool Details Spider", "description": "Scrape comprehensive prediction market data from Probable Markets event pages with this Apify Actor. Extracts event metadata, market questions, trading volumes, liquidity, and descriptions into clean JSON. Supports batch processing, ensures high reliability and speed without API dependencies....", "version": "0.0", "x-build-id": "w6vzQtPNdfOx46rPz" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~probablemarket-pool-details-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-probablemarket-pool-details-spider", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~probablemarket-pool-details-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-probablemarket-pool-details-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~probablemarket-pool-details-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-probablemarket-pool-details-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "Urls": { "title": "Urls", "minItems": 1, "type": "array", "description": "The urls for the spider.", "default": [ "https://probable.markets/event/usdai-fdv-above-one-day-after-launch?market=897", "https://probable.markets/event/based-fdv-above-one-day-after-launch?market=715", "https://probable.markets/event/will-satoshi-move-any-bitcoin-in-2026", "https://probable.markets/event/opinion-fdv-above-one-day-after-launch?market=587", "https://probable.markets/event/what-price-will-msft-hit-in-february-2026?market=1104", "https://probable.markets/event/what-price-will-xrp-hit-in-february-2026?market=1348", "https://probable.markets/event/what-price-will-aapl-hit-in-february-2026?market=1142" ], "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```