# StatMuse Scraper (`crawlerbros/statmuse-scraper`) Actor Scrape StatMuse sports statistics - ask natural language questions about NBA, NFL, MLB, and NHL stats. Get player career stats, game logs, team records, and season leaders via StatMuse's public Q\&A and stats API. - **URL**: https://apify.com/crawlerbros/statmuse-scraper.md - **Developed by:** [Crawler Bros](https://apify.com/crawlerbros) (community) - **Categories:** Agents, Automation, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## StatMuse Scraper Scrape sports statistics from [StatMuse](https://www.statmuse.com) using natural language queries. Ask any sports question in plain English and get structured stat data back for NBA, NFL, MLB, and NHL. Perfect for building sports analytics dashboards, betting research tools, and sports history research. ### What this actor does - **Four modes:** `queryNBA`, `queryNFL`, `queryMLB`, `queryNHL` - **Natural language queries:** ask anything, e.g. "LeBron James career points" or "most touchdowns in 2023" - **Structured output:** player name, team, season, rank, individual stats - **Fallback:** returns the answer sentence if no table data is available - **Empty fields are omitted — no null values in output** ### Output per record | Field | Description | |---|---| | `queryText` | Your original query | | `answer` | StatMuse's natural language answer | | `sport` | Sport (nba/nfl/mlb/nhl) | | `playerName` | Player name | | `playerId` | Player identifier | | `playerUrl` | StatMuse player page URL | | `imageUrl` | Player headshot URL | | `team` | Team name | | `season` | Season/year | | `rank` | Ranking in result list | | `stats` | Object with all numeric stat values | | `queryUrl` | StatMuse query URL | | `recordType` | Always `"stat"` | | `scrapedAt` | ISO 8601 timestamp | ### Input | Field | Type | Default | Description | |---|---|---|---| | `mode` | string | `queryNBA` | `queryNBA` / `queryNFL` / `queryMLB` / `queryNHL` | | `query` | string | `LeBron James career points` | Natural language sports question | | `maxItems` | integer | `10` | Max records to return (1–200) | #### Example: NBA player career stats ```json { "mode": "queryNBA", "query": "LeBron James career points", "maxItems": 10 } ```` #### Example: NFL touchdowns leaders 2023 ```json { "mode": "queryNFL", "query": "most touchdowns in 2023", "maxItems": 20 } ``` #### Example: MLB batting average leaders ```json { "mode": "queryMLB", "query": "highest batting average 2023 season", "maxItems": 10 } ``` ### Frequently Asked Questions **What kind of questions can I ask?** Any natural language sports question: player career stats, single-season leaders, game logs, team records, historical comparisons, etc. **Does this require a StatMuse account or API key?** No. This uses StatMuse's public website. **Which sports are supported?** NBA, NFL, MLB, and NHL. **What if there's no table in the answer?** The actor returns a single record with the StatMuse answer sentence and the query URL. **Can I get game-by-game data?** Yes, try queries like "LeBron James game log 2023-24 season". # Actor input Schema ## `mode` (type: `string`): Which sport to query. ## `query` (type: `string`): Ask a sports question in plain English, e.g. 'LeBron James career points' or 'most touchdowns in 2023'. ## `maxItems` (type: `integer`): Maximum number of records to return. ## Actor input object example ```json { "mode": "queryNBA", "query": "LeBron James career points", "maxItems": 10 } ``` # Actor output Schema ## `stats` (type: `string`): Dataset containing all scraped sports statistics. # 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 = { "mode": "queryNBA", "query": "LeBron James career points", "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("crawlerbros/statmuse-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 = { "mode": "queryNBA", "query": "LeBron James career points", "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("crawlerbros/statmuse-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 '{ "mode": "queryNBA", "query": "LeBron James career points", "maxItems": 10 }' | apify call crawlerbros/statmuse-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=crawlerbros/statmuse-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "StatMuse Scraper", "description": "Scrape StatMuse sports statistics - ask natural language questions about NBA, NFL, MLB, and NHL stats. Get player career stats, game logs, team records, and season leaders via StatMuse's public Q&A and stats API.", "version": "1.0", "x-build-id": "oMTgzUjFjNtgqeOHn" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/crawlerbros~statmuse-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-crawlerbros-statmuse-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/crawlerbros~statmuse-scraper/runs": { "post": { "operationId": "runs-sync-crawlerbros-statmuse-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/crawlerbros~statmuse-scraper/run-sync": { "post": { "operationId": "run-sync-crawlerbros-statmuse-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "mode", "query" ], "properties": { "mode": { "title": "Mode", "enum": [ "queryNBA", "queryNFL", "queryMLB", "queryNHL" ], "type": "string", "description": "Which sport to query.", "default": "queryNBA" }, "query": { "title": "Natural language query", "type": "string", "description": "Ask a sports question in plain English, e.g. 'LeBron James career points' or 'most touchdowns in 2023'.", "default": "LeBron James career points" }, "maxItems": { "title": "Max items", "minimum": 1, "maximum": 200, "type": "integer", "description": "Maximum number of records to return.", "default": 10 } } }, "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 } } } } } } } } } } ```