# Flashscore Team Statistics Scraper - Football & Basketball (`extractify-labs/flashscore-team-stats`) Actor Extract season-level team stats from Flashscore standings: wins, losses, goals, points and more. Supports football and basketball. No proxy required. - **URL**: https://apify.com/extractify-labs/flashscore-team-stats.md - **Developed by:** [Extractify Labs](https://apify.com/extractify-labs) (community) - **Categories:** News, Other - **Stats:** 1 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 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 ## Flashscore Team Statistics Scraper — Football & Basketball Extract season-level aggregated team statistics from [Flashscore](https://www.flashscore.com) standings pages. One item per team row, covering matches played, win/loss/draw records, goals or points for/against, league points, and full team identity. Supports both football and basketball. Historical and current-season standings both accepted. No proxy required. **Pricing:** $1 per 1,000 results (PPR) — no proxy surcharge. ### What does this actor extract? This actor scrapes Flashscore league standings pages and returns one structured record per team per standings page. Each record includes up to 23 fields split into four categories: league context, team identity, universal statistics (both sports), and sport-specific statistics. #### League context | Field | Type | Example | Notes | |-------|------|---------|-------| | `source_url` | string | `"https://www.flashscore.com/football/england/premier-league/standings/"` | The input URL used | | `sport_name` | string | `"football"` / `"basketball"` | Auto-detected from URL path | | `country_name` | string | `"England"` | Each word of URL slug capitalised (e.g. `"england"` → `"England"`, `"usa"` → `"Usa"`) | | `league_name` | string | `"Premier League"` | Each word of URL slug capitalised (e.g. `"premier-league"` → `"Premier League"`, `"nba"` → `"Nba"`) | | `tournament_id` | string | `"KKay4EE8"` | Flashscore internal tournament ID | | `stage_id` | string | `"OEEq9Yvp"` | Flashscore internal season/stage ID | | `season` | string | `"2024/2025"` / `""` | Season label; empty for current-season URLs | | `group_name` | string | `"Western Conference"` | Present only for grouped/conference competitions | #### Team identity | Field | Type | Example | Notes | |-------|------|---------|-------| | `standing_position` | integer | `1` | Rank in this standings table | | `team_name` | string | `"Arsenal"` | Display name | | `team_id` | string | `"hA1Zm19f"` | Flashscore internal team ID | | `team_slug` | string | `"/team/arsenal/hA1Zm19f/"` | Full URL path from feed | | `team_logo_url` | string | `"https://static.flashscore.com/res/image/data/..."` | Logo image URL; empty string if absent | #### Statistics — both sports | Field | Type | Example | Notes | |-------|------|---------|-------| | `matches_played` | integer | `36` | Games completed in the season | | `wins` | integer | `24` | Wins | | `losses` | integer | `5` | Losses | | `points` | integer | `79` | League table points; **absent for basketball leagues that rank by win%** (e.g. NBA) | #### Statistics — football only | Field | Type | Example | Notes | |-------|------|---------|-------| | `draws` | integer | `7` | Draws; absent for basketball | | `goals_for` | integer | `68` | Goals scored | | `goals_against` | integer | `26` | Goals conceded | | `goal_difference` | integer | `42` | Computed: goals_for − goals_against | #### Statistics — basketball only | Field | Type | Example | Notes | |-------|------|---------|-------| | `points_for` | integer | `112` | Total points scored | | `points_against` | integer | `104` | Total points conceded | ### Supported sports **Football and basketball.** Both are detected automatically from the Flashscore URL path — no sport parameter needed. - **Football:** All fields active, including `draws`, `goals_for`, `goals_against`, `goal_difference`. - **Basketball:** `draws`, `goals_for`, `goals_against`, `goal_difference` are absent. `points_for` and `points_against` are present. `points` (league table points) is absent for leagues that rank by win percentage (NBA) — the field is present for basketball leagues that do use a points table. Any Flashscore standings page URL works for either sport. ### Input parameters #### `startUrls` — required An array of Flashscore league standings page URLs. Each URL must contain `/standings/` in the path. | Property | Value | |----------|-------| | Type | array of URLs | | Required | Yes | | Supported formats | String URL or `{ "url": "..." }` object | **Football examples:** ```` https://www.flashscore.com/football/england/premier-league/standings/ https://www.flashscore.com/football/spain/laliga/standings/ https://www.flashscore.com/football/europe/champions-league/standings/ ``` **Basketball examples:** ``` https://www.flashscore.com/basketball/usa/nba/standings/ https://www.flashscore.com/basketball/europe/euroleague/standings/ ``` **Historical season example** (stageId encoded in URL): ``` https://www.flashscore.com/football/england/premier-league/OEEq9Yvp/standings/overall/ ```` You can mix football and basketball URLs in a single run. #### `maxItems` — optional Global cap on total output items across all input URLs combined. Useful for testing or cost control. | Property | Value | |----------|-------| | Type | integer | | Required | No | | Default | Unlimited | Leave unset to extract all teams from all input URLs. ### Sample output #### Football — Premier League team ```json { "source_url": "https://www.flashscore.com/football/england/premier-league/standings/", "sport_name": "football", "country_name": "England", "league_name": "Premier League", "tournament_id": "KKay4EE8", "stage_id": "OEEq9Yvp", "season": "", "standing_position": 1, "team_name": "Arsenal", "team_id": "hA1Zm19f", "team_slug": "/team/arsenal/hA1Zm19f/", "team_logo_url": "https://static.flashscore.com/res/image/data/hA1Zm19f_h.png", "matches_played": 36, "wins": 24, "draws": 7, "losses": 5, "goals_for": 68, "goals_against": 26, "goal_difference": 42, "points": 79 } ```` #### Basketball — NBA team (Eastern Conference) ```json { "source_url": "https://www.flashscore.com/basketball/usa/nba/standings/", "sport_name": "basketball", "country_name": "Usa", "league_name": "Nba", "tournament_id": "OIo52B5b", "stage_id": "MHnOejlI", "season": "", "group_name": "Eastern Conference", "standing_position": 1, "team_name": "Boston Celtics", "team_id": "IvBGpHs5", "team_slug": "/team/boston-celtics/IvBGpHs5/", "team_logo_url": "https://static.flashscore.com/res/image/data/IvBGpHs5_h.png", "matches_played": 82, "wins": 61, "losses": 21, "points_for": 9184, "points_against": 8750 } ``` ### How to use this actor 1. Open the actor on the [Apify Store](https://apify.com/extractify-labs/flashscore-team-stats). 2. Find the standings page for your league on [Flashscore](https://www.flashscore.com). The URL must contain `/standings/`. 3. Paste one or more standings URLs into the `startUrls` field. 4. (Optional) Set `maxItems` to limit results for testing. 5. Click **Start** and download results as JSON, CSV, or XLSX when the run completes. **Sample input:** ```json { "startUrls": [ "https://www.flashscore.com/football/england/premier-league/standings/", "https://www.flashscore.com/basketball/usa/nba/standings/" ], "maxItems": 100 } ``` ### Key features - **Football and basketball in one actor** — no need to switch tools or manage two separate actors - **Historical and current seasons** — any Flashscore standings URL works, including season-specific URLs with stageId encoded in the path - **Auto sport detection** — sport is detected from the URL path; no `sport` parameter required - **Conference and division grouping** — `group_name` is populated for grouped competitions (NBA conferences, Champions League groups, etc.) - **No proxy required** — direct requests with a static `x-fsign` header; you pay only for compute - **Efficient feed requests** — only two HTTP requests per standings URL (HTML page + one feed call); no unnecessary page loads - **Hard item cap** — `maxItems` is enforced exactly, even when a single feed returns many teams at once ### Use cases **Fantasy sports analytics:** Pull current-season standings for every league in your fantasy platform. Compare teams across multiple leagues and seasons to identify consistent performers. Schedule weekly runs to keep season totals up to date. **Betting research:** Access historical win/loss/draw records and goal tallies for any football league back through multiple seasons. Combine with match-level data to build form-based predictive models. **Data journalism:** Extract multi-season standings for any country's top division and compare year-over-year performance trends for a specific team or cluster of teams. **Sports statistics databases:** Populate or update a team statistics database for football leagues or basketball competitions. The consistent field schema makes it straightforward to normalise data across leagues. **Academic sports research:** Gather season-level outcome data for multiple leagues simultaneously to support regression analysis, ranking systems, or competitive balance research. ### Pricing and cost This actor is priced at **$1 per 1,000 results (Pay-Per-Result)**. One result equals one team row from one standings page. | League | Teams | Items per run | |--------|-------|---------------| | English Premier League | 20 teams | ~20 items | | NBA (all conferences) | 30 teams | ~60 items (teams appear once per conference group and once per division group) | | 5 leagues in one run | 20 teams each | ~100 items | No proxy costs are added on top — the actor fetches directly from Flashscore without residential or datacenter proxies. ### What this actor does not cover **Pre-aggregated data only.** This actor reads Flashscore's standings feed, which contains only the statistics that Flashscore pre-calculates at the season level. The following fields are **not available** in Flashscore standings feeds and cannot be extracted: - **Clean sheets** — not present in the standings feed; requires match-level aggregation - **Average possession** — not present in the standings feed; requires match-level data - **Shots per match** — not present in the standings feed; requires match-level data - **Player statistics** — this actor covers team-level data only - **Match odds or bookmaker lines** — not provided by Flashscore standings pages - **Live match scores** — this is a season-aggregate actor; see related actors below for live data If you need match-level statistics, see the related actors section below. ### FAQ #### Does this actor support historical seasons? Yes. Flashscore encodes season information in the URL's stageId segment. To access a historical season, navigate to that season on Flashscore, copy the URL (which will contain a stageId like `OEEq9Yvp` between the league name and `/standings/`), and provide it in `startUrls`. The actor extracts and outputs the `stage_id` and `season` fields so you can identify which season each item belongs to. #### Why is the `season` field empty for some items? Current-season URLs (e.g. `.../premier-league/standings/`) do not include a year suffix in the URL path, so the `season` field is an empty string `""`. Historical season URLs include a year slug (e.g. `.../premier-league-24-25/standings/`) from which the actor derives a label like `"2024/2025"`. To get a populated `season` field, use a historical season URL from the Flashscore interface. #### Can I run football and basketball URLs in the same job? Yes. `startUrls` accepts any mix of football and basketball standings URLs. The actor auto-detects the sport from each URL and applies the correct field set. Football items include `draws`, `goals_for`, `goals_against`, `goal_difference`; basketball items include `points_for`, `points_against`. These sport-specific fields are simply absent (not null) in items from the other sport. #### Why are clean sheets, possession, and shots not available? Flashscore's standings feeds contain only pre-aggregated season totals that appear in the visible standings table. Clean sheets, possession, and shots are not part of the standings table and are not available in the feed. Extracting these would require fetching and aggregating individual match statistics — a different data source entirely. #### Does this actor require a proxy? No. Flashscore standings pages and their feeds are accessible with a static `x-fsign` request header. No residential or datacenter proxy is needed. You are not charged for proxy bandwidth. #### Why is the `points` field absent for NBA teams? The NBA ranks teams by win percentage rather than accumulated points, so the NBA standings feed does not include a points field. The `points` field is absent from NBA output items. For basketball leagues that do use a points table (e.g. EuroLeague), the field is present. #### What does `group_name` mean? Some competitions divide teams into groups, conferences, or divisions for their standings tables. When the standings page shows multiple groups (e.g. NBA Eastern/Western conferences, or a Champions League group stage), each team item includes a `group_name` field identifying which group that row belongs to. For single-table competitions like the Premier League, `group_name` is absent. #### What does `team_slug` contain? The `team_slug` field contains the full URL path segment as returned by the Flashscore feed — for example `/team/arsenal/hA1Zm19f/`. This includes the team name component and the team ID. It is not a bare short slug. You can use it to construct a full Flashscore team URL: `https://www.flashscore.com` + `team_slug`. ### Related actors - [Flashscore: Match Listings, Scores & Fixtures](https://apify.com/extractify-labs/flashscore-extractor) — Match-level results and live scores for football and basketball - [Flashscore: Basketball Live Matches](https://apify.com/extractify-labs/flashscore-basketball-live-matches) — Live and in-progress basketball match data - [Flashscore: Basketball Match Statistics](https://apify.com/extractify-labs/flashscore-basketball-match-stats) — Per-match statistical breakdown for basketball games - [Flashscore: Team Fixtures](https://apify.com/extractify-labs/flashscore-team-fixtures) — Upcoming and past fixtures for a specific team # Actor input Schema ## `startUrls` (type: `array`): Flashscore league standings page URLs. Accepts both current season and historical season URLs. Examples: https://www.flashscore.com/football/england/premier-league/standings/ or https://www.flashscore.com/basketball/usa/nba/standings/. Each URL must contain '/standings/' in the path. ## `maxItems` (type: `integer`): Global cap on total output items across all input URLs combined. Leave empty for unlimited. Useful for testing. ## Actor input object example ```json { "startUrls": [ { "url": "https://www.flashscore.com/football/england/premier-league/standings/" }, { "url": "https://www.flashscore.com/basketball/usa/nba/standings/" } ] } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "startUrls": [ { "url": "https://www.flashscore.com/football/england/premier-league/standings/" }, { "url": "https://www.flashscore.com/basketball/usa/nba/standings/" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("extractify-labs/flashscore-team-stats").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 = { "startUrls": [ { "url": "https://www.flashscore.com/football/england/premier-league/standings/" }, { "url": "https://www.flashscore.com/basketball/usa/nba/standings/" }, ] } # Run the Actor and wait for it to finish run = client.actor("extractify-labs/flashscore-team-stats").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 '{ "startUrls": [ { "url": "https://www.flashscore.com/football/england/premier-league/standings/" }, { "url": "https://www.flashscore.com/basketball/usa/nba/standings/" } ] }' | apify call extractify-labs/flashscore-team-stats --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=extractify-labs/flashscore-team-stats", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Flashscore Team Statistics Scraper - Football & Basketball", "description": "Extract season-level team stats from Flashscore standings: wins, losses, goals, points and more. Supports football and basketball. No proxy required.", "version": "1.0", "x-build-id": "xc6XP794cj9AX5Bwc" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/extractify-labs~flashscore-team-stats/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-extractify-labs-flashscore-team-stats", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/extractify-labs~flashscore-team-stats/runs": { "post": { "operationId": "runs-sync-extractify-labs-flashscore-team-stats", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/extractify-labs~flashscore-team-stats/run-sync": { "post": { "operationId": "run-sync-extractify-labs-flashscore-team-stats", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startUrls" ], "properties": { "startUrls": { "title": "Standings URLs", "minItems": 1, "type": "array", "description": "Flashscore league standings page URLs. Accepts both current season and historical season URLs. Examples: https://www.flashscore.com/football/england/premier-league/standings/ or https://www.flashscore.com/basketball/usa/nba/standings/. Each URL must contain '/standings/' in the path.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxItems": { "title": "Maximum items", "minimum": 1, "type": "integer", "description": "Global cap on total output items across all input URLs combined. Leave empty for unlimited. Useful for testing." } } }, "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 } } } } } } } } } } ```