# Football H2H Head-to-Head Scraper (`mandobatman/h2h-head-to-head`) Actor Football head-to-head (H2H) scraper. Returns full historical matchups between any two teams via API-Football: scores, dates, venues, half-time, extra time, penalties, refs. Perfect for betting tips, form analysis, football trading & match prediction. - **URL**: https://apify.com/mandobatman/h2h-head-to-head.md - **Developed by:** [Sid](https://apify.com/mandobatman) (community) - **Categories:** Sports - **Stats:** 2 total users, 1 monthly users, 0.0% 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 ## Football H2H Head-to-Head Scraper **Apify Actor:** [h2h-head-to-head](https://apify.com/mandobatman/h2h-head-to-head) Scrape complete historical head-to-head results between any two football teams. Returns full match data — scores, dates, venues, competitions, half-time results, extra time, penalties, and more. --- ### What This Actor Does Given two football team names, this actor: 1. Resolves team names to official API-Football IDs (fuzzy matching, e.g. "Arsenal" → ID 42) 2. Fetches all head-to-head matches between them via the API-Football API 3. Filters and formats the data into a clean structured dataset 4. Saves results to your Apify dataset (CSV/JSON/HTML export) --- ### Input Parameters | Field | Type | Required | Default | Description | |-------|------|----------|---------|-------------| | `team1` | string | ✅ | — | Name of first team (e.g. "Arsenal", "Manchester United") | | `team2` | string | ✅ | — | Name of second team | | `max_matches` | integer | ❌ | 50 | Max number of H2H matches to return (1–200) | | `competition` | string | ❌ | — | Filter by competition name (e.g. "Premier League") | | `api_key` | string | ❌ | — | API-Football key (uses env secret if not provided) | --- ### Output Dataset Fields Each record contains: ```` match\_id, match\_date, match\_time, match\_datetime, league\_name, league\_country, season, round, home\_team, away\_team, home\_goals, away\_goals, home\_goals\_ht, away\_goals\_ht, extra\_time\_home, extra\_time\_away, penalties\_home, penalties\_away, venue, referee, status (FINISHED/LIVE/POSTPONED), odds\_home, odds\_draw, odds\_away, match\_url, api\_football\_url ``` --- ### Use Cases - **Betting analysis** — H2H history is a key input for match prediction models - **Football trading** — Pre-match H2H data for trading algorithms - **Form guides** — Build team comparison reports for any matchup - **Fantasy football** — Historical performance data between specific teams - **Journalism** — Quick access to any head-to-head record for match previews --- ### Example **Input:** ``` team1: Arsenal team2: Manchester City max\_matches: 10 ```` **Output:** 10 most recent Arsenal vs Manchester City matches with full score details, dates, venues, and competition info. --- ### Data Source - **Source:** [API-Football](https://www.api-football.com/) (free tier: 100 requests/day) - **Coverage:** 600+ leagues, 100,000+ teams - **Freshness:** Data is typically updated within hours of match completion --- ### Pricing This actor uses the free tier of API-Football. Set `APIFOOTBALL_API_KEY` as an Apify secret to use your own key for higher rate limits. Recommended run cost: **$0.05 – $0.10 per run** (covers API overhead + Apify compute). --- ### About Built by **Sid / Statistically World Cup** — sports statistics and data content for the beautiful game. - [Apify Profile](https://apify.com/mandobatman) - [Statistically World Cup](https://www.instagram.com/statisticallyworldcup/) # Actor input Schema ## `team1` (type: `string`): Name of first team (e.g. 'Arsenal', 'Chelsea', 'Barcelona') ## `team2` (type: `string`): Name of second team (e.g. 'Manchester City', 'Liverpool', 'Real Madrid') ## `max_matches` (type: `integer`): Maximum number of H2H matches to return (default: 50) ## `competition` (type: `string`): Filter results by competition name (e.g. 'Premier League', 'Champions League'). Leave empty for all competitions. ## `api_key` (type: `string`): API-Football key. Recommended: store as secret 'APIFOOTBALL_API_KEY' in Apify console instead. ## Actor input object example ```json { "team1": "Arsenal", "team2": "Manchester City", "max_matches": 50, "competition": "" } ```` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "team1": "Arsenal", "team2": "Manchester City" }; // Run the Actor and wait for it to finish const run = await client.actor("mandobatman/h2h-head-to-head").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "team1": "Arsenal", "team2": "Manchester City", } # Run the Actor and wait for it to finish run = client.actor("mandobatman/h2h-head-to-head").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 '{ "team1": "Arsenal", "team2": "Manchester City" }' | apify call mandobatman/h2h-head-to-head --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=mandobatman/h2h-head-to-head", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Football H2H Head-to-Head Scraper", "description": "Football head-to-head (H2H) scraper. Returns full historical matchups between any two teams via API-Football: scores, dates, venues, half-time, extra time, penalties, refs. Perfect for betting tips, form analysis, football trading & match prediction.", "version": "1.0", "x-build-id": "EBNKFXgcuSghzwnJG" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/mandobatman~h2h-head-to-head/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-mandobatman-h2h-head-to-head", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/mandobatman~h2h-head-to-head/runs": { "post": { "operationId": "runs-sync-mandobatman-h2h-head-to-head", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/mandobatman~h2h-head-to-head/run-sync": { "post": { "operationId": "run-sync-mandobatman-h2h-head-to-head", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "team1", "team2" ], "properties": { "team1": { "title": "Team 1", "type": "string", "description": "Name of first team (e.g. 'Arsenal', 'Chelsea', 'Barcelona')" }, "team2": { "title": "Team 2", "type": "string", "description": "Name of second team (e.g. 'Manchester City', 'Liverpool', 'Real Madrid')" }, "max_matches": { "title": "Max Matches", "minimum": 1, "maximum": 200, "type": "integer", "description": "Maximum number of H2H matches to return (default: 50)", "default": 50 }, "competition": { "title": "Competition Filter", "type": "string", "description": "Filter results by competition name (e.g. 'Premier League', 'Champions League'). Leave empty for all competitions.", "default": "" }, "api_key": { "title": "API Key (optional)", "type": "string", "description": "API-Football key. Recommended: store as secret 'APIFOOTBALL_API_KEY' in Apify console instead." } } }, "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 } } } } } } } } } } ```