# Understat xG Football Data Scraper (`crawlerbros/understat-scraper`) Actor Scrape Understat (understat.com) for xG (expected goals) football analytics. Get player stats, team stats, and match data for Premier League, La Liga, Bundesliga, Serie A, Ligue 1, and RFPL. - **URL**: https://apify.com/crawlerbros/understat-scraper.md - **Developed by:** [Crawler Bros](https://apify.com/crawlerbros) (community) - **Categories:** Automation, Developer tools, Integrations - **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, NaN 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 ## Understat xG Football Data Scraper Scrape **Understat** (understat.com) for advanced expected goals (xG) football analytics across 6 major leagues. Get player xG, xA, xGChain, xGBuildup, and team performance data. ### What This Actor Does Fetches xG football analytics from Understat including: - **League Stats**: All player xG stats for a season (xG, xA, xGChain, xGBuildup, goals, assists, shots) - **Team Stats**: Aggregated team performance with xG and xGA over a season - **Player Stats**: Full match-by-match xG history for a specific player ### Supported Leagues | Code | League | |------|--------| | `EPL` | Premier League (England) | | `La_liga` | La Liga (Spain) | | `Bundesliga` | Bundesliga (Germany) | | `Serie_A` | Serie A (Italy) | | `Ligue_1` | Ligue 1 (France) | | `RFPL` | Russian Premier League | ### Input | Field | Type | Description | |-------|------|-------------| | `mode` | string | `leagueStats`, `teamStats`, or `playerStats` | | `league` | string | League code (e.g. `EPL`, `La_liga`) | | `season` | string | Season start year, e.g. `2024` for 2024/25 | | `teamName` | string | Filter by team name (teamStats mode) | | `playerId` | string | Understat player ID (playerStats mode) | | `playerName` | string | Player name filter or lookup | | `maxItems` | integer | Max records to return (default: 10) | #### Example Input ```json { "mode": "leagueStats", "league": "EPL", "season": "2024", "maxItems": 10 } ```` ### Output #### Player Record (leagueStats / playerStats) | Field | Description | |-------|-------------| | `playerId` | Understat player ID | | `playerName` | Player's name | | `team` | Club name | | `position` | Playing position | | `games` | Matches played | | `goals` | Goals scored | | `assists` | Assists | | `xG` | Expected goals | | `xA` | Expected assists | | `xGChain` | xG from all actions in a chain | | `xGBuildup` | xG contribution without shot/key pass | | `yellowCards` | Yellow cards | | `redCards` | Red cards | | `shots` | Total shots | | `minutesPlayed` | Minutes on pitch | | `season` | Season year | | `league` | League name | | `playerUrl` | Link to Understat player page | #### Example Output ```json { "playerId": "1250", "playerName": "Mohamed Salah", "team": "Liverpool", "position": "AML", "games": 32, "goals": 20, "assists": 12, "xG": 18.5, "xA": 9.2, "xGChain": 22.1, "season": "2024", "league": "Premier League", "playerUrl": "https://understat.com/player/1250" } ``` ### FAQs **Is this free to use?** Yes. Understat is publicly accessible and embeds all data as JSON in the page HTML — no API key required. **What is xG?** Expected Goals (xG) measures the quality of goal-scoring chances. Each shot is assigned a probability of being scored based on historical data. **What is xGChain?** xGChain is the total xG from every action (pass, dribble, shot) in the sequence of play that led to a shot, credited to every player involved. **How do I get a player ID?** Run `leagueStats` mode first to get the `playerId` field, then use it in `playerStats` mode. You can also use `playerName` to auto-find the ID. **Why does the 2024 season use year 2024 not 2024-2025?** Understat uses the start year of the season as the identifier (e.g. 2024 = 2024/25 season). # Actor input Schema ## `mode` (type: `string`): What to fetch from Understat. ## `league` (type: `string`): Understat league code. ## `season` (type: `string`): Season start year, e.g. 2024 for the 2024/25 season. ## `teamName` (type: `string`): Filter to a specific team name (partial match, case-insensitive). ## `playerId` (type: `string`): Understat player ID, e.g. 1250 for Salah. Find via leagueStats mode. ## `playerName` (type: `string`): Filter players by name (partial match). For playerStats mode, used to find player ID if playerId not set. ## `maxItems` (type: `integer`): Maximum number of records to return. ## Actor input object example ```json { "mode": "leagueStats", "league": "EPL", "season": "2024", "maxItems": 10 } ``` # Actor output Schema ## `stats` (type: `string`): Dataset containing scraped xG stats from Understat. # 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": "leagueStats", "league": "EPL", "season": "2024", "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("crawlerbros/understat-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": "leagueStats", "league": "EPL", "season": "2024", "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("crawlerbros/understat-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": "leagueStats", "league": "EPL", "season": "2024", "maxItems": 10 }' | apify call crawlerbros/understat-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=crawlerbros/understat-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Understat xG Football Data Scraper", "description": "Scrape Understat (understat.com) for xG (expected goals) football analytics. Get player stats, team stats, and match data for Premier League, La Liga, Bundesliga, Serie A, Ligue 1, and RFPL.", "version": "1.0", "x-build-id": "Vub4UU9CC0eOA3fRR" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/crawlerbros~understat-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-crawlerbros-understat-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/crawlerbros~understat-scraper/runs": { "post": { "operationId": "runs-sync-crawlerbros-understat-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/crawlerbros~understat-scraper/run-sync": { "post": { "operationId": "run-sync-crawlerbros-understat-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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" ], "properties": { "mode": { "title": "Mode", "enum": [ "leagueStats", "teamStats", "playerStats" ], "type": "string", "description": "What to fetch from Understat.", "default": "leagueStats" }, "league": { "title": "League", "enum": [ "EPL", "La_liga", "Bundesliga", "Serie_A", "Ligue_1", "RFPL" ], "type": "string", "description": "Understat league code.", "default": "EPL" }, "season": { "title": "Season year", "type": "string", "description": "Season start year, e.g. 2024 for the 2024/25 season.", "default": "2024" }, "teamName": { "title": "Team name filter (mode=teamStats)", "type": "string", "description": "Filter to a specific team name (partial match, case-insensitive)." }, "playerId": { "title": "Player ID (mode=playerStats)", "type": "string", "description": "Understat player ID, e.g. 1250 for Salah. Find via leagueStats mode." }, "playerName": { "title": "Player name filter", "type": "string", "description": "Filter players by name (partial match). For playerStats mode, used to find player ID if playerId not set." }, "maxItems": { "title": "Max items", "minimum": 1, "maximum": 500, "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 } } } } } } } } } } ```