# Espn Sports Scraper (`quarterly_jingo/espn-sports-scraper`) Actor - **URL**: https://apify.com/quarterly\_jingo/espn-sports-scraper.md - **Developed by:** [Petey Boy](https://apify.com/quarterly_jingo) (community) - **Categories:** Lead generation, Automation, Developer tools - **Stats:** 2 total users, 1 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.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 ## ESPN Sports Data API Scraper ### Overview Extract comprehensive sports data from ESPN's hidden API. Get live scores, standings, schedules, team rosters, and game summaries for NFL, NBA, MLB, NHL, College Football, College Basketball, and Soccer (Premier League, La Liga, MLS, etc. ). ### Features - Search by keywords to find specific results - Filter results by category or type - Export data in JSON, CSV, or Excel formats ### Use Cases - **Track** - Track entertainment listings and reviews - **Build** - Build media databases for content analysis - **Monitor** - Monitor entertainment industry trends and ratings - **Aggregate** - Aggregate entertainment data for recommendation engines ### Input Parameters | Parameter | Type | Description | Default | |-----------|------|-------------|---------| | `dataType` | string **(required)** | Type of data to scrape | `scoreboard` | | `sport` | string **(required)** | Sport category | `football` | | `league` | string **(required)** | League to scrape. For soccer, use league codes like 'eng.1' (Premier League),... | `nfl` | | `startDate` | string | Start date for scores/schedule (YYYYMMDD format, e.g., 20250115) | | | `endDate` | string | End date for date range queries (YYYYMMDD format). If only startDate is provi... | | | `teamId` | string | ESPN team ID for team-specific data (roster, schedule). Find IDs by first scr... | | | `eventId` | string | ESPN event ID for game summary/box score data | | | `season` | integer | Season year (e.g., 2025). Defaults to current season. | `2025` | | `seasonType` | string | 1=Preseason, 2=Regular Season, 3=Postseason, 4=Offseason | `2` | | `limit` | integer | Maximum number of results to return | `100` | ### Output Example Each result contains structured data like this: ```json { "type": "Standard", "eventId": "ABC-12345", "name": "ESPN Sports Data API Sample Item", "date": "2025-01-15", "status": "Active", "homeTeam": "Sample homeTeam", "awayTeam": "Sample awayTeam", "venue": "Convention Center", "sport": "Sample sport", "league": "Sample league" } ```` ### Pricing This actor uses pay-per-result pricing: - **$0.002** per result - **$2.00** per 1,000 results No monthly fees. You only pay for what you scrape. [Apify Free plan](https://apify.com/pricing) includes $5/month in platform credits. ### How to Run #### Apify Console 1. Go to the [ESPN Sports Data API Scraper](https://apify.com/fortuitous_pirate/espn-sports-scraper) actor page 2. Configure your input parameters 3. Click **Start** and wait for the results 4. Download data in JSON, CSV, or Excel format #### API ```bash curl -X POST "https://api.apify.com/v2/acts/fortuitous_pirate~espn-sports-scraper/runs?token=YOUR_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{"maxItems": 10}' ``` #### Python SDK ```python from apify_client import ApifyClient client = ApifyClient("YOUR_API_TOKEN") run = client.actor("fortuitous_pirate/espn-sports-scraper").call( run_input={"maxItems": 10} ) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ``` ### Integration Connect ESPN Sports Data API Scraper with your existing tools and workflows: - **API access** - Programmatic access via [Apify API](https://docs.apify.com/api/v2) - **Webhooks** - Get notified when scraping completes - **Scheduling** - Set up recurring runs on any schedule - **Zapier / Make** - Connect with 5,000+ apps via [Apify integrations](https://apify.com/integrations) - **Python / Node.js SDKs** - Native client libraries for easy integration # Actor input Schema ## `dataType` (type: `string`): Type of data to scrape ## `sport` (type: `string`): Sport category ## `league` (type: `string`): League to scrape. For soccer, use league codes like 'eng.1' (Premier League), 'esp.1' (La Liga), 'usa.1' (MLS) ## `startDate` (type: `string`): Start date for scores/schedule (YYYYMMDD format, e.g., 20250115) ## `endDate` (type: `string`): End date for date range queries (YYYYMMDD format). If only startDate is provided, fetches that single date. ## `teamId` (type: `string`): ESPN team ID for team-specific data (roster, schedule). Find IDs by first scraping teams list. ## `eventId` (type: `string`): ESPN event ID for game summary/box score data ## `season` (type: `integer`): Season year (e.g., 2025). Defaults to current season. ## `seasonType` (type: `string`): 1=Preseason, 2=Regular Season, 3=Postseason, 4=Offseason ## `limit` (type: `integer`): Maximum number of results to return ## Actor input object example ```json { "dataType": "scoreboard", "sport": "football", "league": "nfl", "season": 2025, "seasonType": "2", "limit": 10 } ``` # 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("quarterly_jingo/espn-sports-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 = {} # Run the Actor and wait for it to finish run = client.actor("quarterly_jingo/espn-sports-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 '{}' | apify call quarterly_jingo/espn-sports-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=quarterly_jingo/espn-sports-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Espn Sports Scraper", "description": "", "version": "1.0", "x-build-id": "dSwa0gbUxeYzf0Mch" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/quarterly_jingo~espn-sports-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-quarterly_jingo-espn-sports-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/quarterly_jingo~espn-sports-scraper/runs": { "post": { "operationId": "runs-sync-quarterly_jingo-espn-sports-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/quarterly_jingo~espn-sports-scraper/run-sync": { "post": { "operationId": "run-sync-quarterly_jingo-espn-sports-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "dataType", "sport", "league" ], "properties": { "dataType": { "title": "Data Type", "enum": [ "scoreboard", "standings", "teams", "schedule", "roster", "news", "gameSummary" ], "type": "string", "description": "Type of data to scrape", "default": "scoreboard" }, "sport": { "title": "Sport", "enum": [ "football", "basketball", "baseball", "hockey", "soccer" ], "type": "string", "description": "Sport category", "default": "football" }, "league": { "title": "League", "enum": [ "nfl", "college-football", "nba", "wnba", "mens-college-basketball", "womens-college-basketball", "mlb", "college-baseball", "nhl", "eng.1", "esp.1", "ger.1", "ita.1", "fra.1", "usa.1", "mex.1", "uefa.champions", "uefa.europa" ], "type": "string", "description": "League to scrape. For soccer, use league codes like 'eng.1' (Premier League), 'esp.1' (La Liga), 'usa.1' (MLS)", "default": "nfl" }, "startDate": { "title": "Start Date", "type": "string", "description": "Start date for scores/schedule (YYYYMMDD format, e.g., 20250115)" }, "endDate": { "title": "End Date", "type": "string", "description": "End date for date range queries (YYYYMMDD format). If only startDate is provided, fetches that single date." }, "teamId": { "title": "Team ID", "type": "string", "description": "ESPN team ID for team-specific data (roster, schedule). Find IDs by first scraping teams list." }, "eventId": { "title": "Event/Game ID", "type": "string", "description": "ESPN event ID for game summary/box score data" }, "season": { "title": "Season Year", "type": "integer", "description": "Season year (e.g., 2025). Defaults to current season.", "default": 2025 }, "seasonType": { "title": "Season Type", "enum": [ "1", "2", "3", "4" ], "type": "string", "description": "1=Preseason, 2=Regular Season, 3=Postseason, 4=Offseason", "default": "2" }, "limit": { "title": "Result Limit", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of results 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 } } } } } } } } } } ```