# CrossFit Games & Open Leaderboard Scraper (`jungle_synthesizer/crossfit-games-leaderboard-scraper`) Actor Scrape athlete leaderboard data from the official CrossFit Games API. Covers the Open, Quarterfinals, Semifinals, and Games across all years and divisions. Returns per-athlete rank, score, region, affiliate, and per-workout scores. - **URL**: https://apify.com/jungle\_synthesizer/crossfit-games-leaderboard-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Sports, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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 ## CrossFit Games & Open Leaderboard Scraper Scrape athlete leaderboard data from the **official CrossFit API** at `c3po.crossfit.com`. Covers all four competition types across all available years, divisions, and regions — returns per-athlete rank, score, affiliate, and per-workout scores. ### What it scrapes - **CrossFit Open** — all years (2011–present), ~177,000 athletes per year per division - **CrossFit Games** — annual Games leaderboard - **Quarterfinals** — the stage between Open and Semifinals - **Semifinals** — regional Semifinals leaderboard - All **divisions**: Men, Women, Masters (35–39 through 60+), Teen Boys/Girls, Team - Both **Rx** and **scaled** leaderboards - All **regions** or filtered by specific region ID ### Output fields | Field | Description | |-------|-------------| | `competition` | Competition type: `open`, `games`, `quarterfinals`, `semifinals` | | `year` | Competition year (e.g. 2024) | | `division_id` | Division numeric ID | | `division_name` | Division name (e.g. "Men", "Women 35-39") | | `scaled` | True if scaled leaderboard | | `overall_rank` | Athlete's overall rank in this division | | `overall_score` | Athlete's overall score (raw points) | | `competitor_id` | CrossFit athlete ID | | `competitor_name` | Athlete full name | | `first_name` / `last_name` | Split name fields | | `gender` | M / F | | `age` | Athlete age | | `height` | Height with units (e.g. "172 cm") | | `weight` | Weight with units (e.g. "190 lb") | | `country_code` | ISO 2-letter country code | | `country_name` | Country of origin | | `region_id` / `region_name` | Region (e.g. "Europe", "North America") | | `affiliate_id` / `affiliate_name` | CrossFit box/affiliate | | `workout_scores` | JSON array of per-WOD scores: rank, scoreDisplay, scaled flag, breakdown, time | | `is_judged` | True if at least one workout was judged | ### Input | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `competition` | string | `open` | Competition type: `open`, `games`, `quarterfinals`, `semifinals` | | `year` | integer | `2024` | Competition year (2011–2030) | | `division` | integer | `1` | Division ID (1=Men, 2=Women, 3-14=Masters, 17-20=Teens, 30=Team) | | `scaled` | boolean | `false` | Fetch scaled leaderboard instead of Rx | | `region` | integer | `0` | Region filter (0 = worldwide) | | `startPage` | integer | `1` | First page to fetch (50 athletes/page) | | `endPage` | integer | — | Last page to fetch (omit for all pages) | | `maxItems` | integer | `10` | Cap on total rows returned | ### Division ID reference | ID | Division | |----|----------| | 1 | Men | | 2 | Women | | 3 | Men 35-39 | | 4 | Women 35-39 | | 5 | Men 40-44 | | 6 | Women 40-44 | | 7 | Men 45-49 | | 8 | Women 45-49 | | 9 | Men 50-54 | | 10 | Women 50-54 | | 11 | Men 55-59 | | 12 | Women 55-59 | | 13 | Men 60+ | | 14 | Women 60+ | | 17 | Teen Boys 16-17 | | 18 | Teen Girls 16-17 | | 19 | Teen Boys 14-15 | | 20 | Teen Girls 14-15 | | 30 | Team | ### Usage examples **Scrape the top 50 Men from the 2024 CrossFit Open (one page):** ```json { "competition": "open", "year": 2024, "division": 1, "maxItems": 50 } ```` **Scrape the full Women 35-39 division from the 2023 Open:** ```json { "competition": "open", "year": 2023, "division": 4, "scaled": false } ``` **Scrape just pages 100-110 of the 2024 Open Men Rx (partial/resume pull):** ```json { "competition": "open", "year": 2024, "division": 1, "startPage": 100, "endPage": 110 } ``` **Scrape the CrossFit Games 2024 Men leaderboard:** ```json { "competition": "games", "year": 2024, "division": 1 } ``` ### Notes - Large Open competitions have up to **3,545 pages** (~177,000 athletes). Use `startPage`/`endPage` for partial pulls, or set `maxItems` to cap results. - The API is **public** — no authentication required, no proxy needed. - Rate limited to ~2 requests/second (polite default). Full Open divisions take approximately 30 minutes. - All data comes from the **official CrossFit c3po.crossfit.com API** — the same source powering the games.crossfit.com leaderboard site. # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `competition` (type: `string`): CrossFit competition type: open, games, quarterfinals, or semifinals ## `year` (type: `integer`): Competition year (e.g. 2024). Defaults to the most recent Open year. ## `division` (type: `integer`): Division numeric ID. 1=Men, 2=Women, 3=Men 35-39, 4=Women 35-39, 5=Men 40-44, 6=Women 40-44, 7=Men 45-49, 8=Women 45-49, 9=Men 50-54, 10=Women 50-54, 11=Men 55-59, 12=Women 55-59, 13=Men 60+, 14=Women 60+, 17=Teen Boys 16-17, 18=Teen Girls 16-17, 19=Teen Boys 14-15, 20=Teen Girls 14-15, 30=Team. Default: 1 (Men). ## `scaled` (type: `boolean`): Set to true to fetch scaled leaderboard instead of Rx. ## `region` (type: `integer`): Region filter ID. 0 = worldwide (all regions). Set to a specific region ID to filter. ## `startPage` (type: `integer`): First leaderboard page to fetch (1-indexed). Use with endPage for partial pulls. ## `endPage` (type: `integer`): Last leaderboard page to fetch. Omit to fetch all pages up to totalPages or maxItems. ## `maxItems` (type: `integer`): Maximum number of leaderboard rows to return across all pages. ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "competition": "open", "year": 2024, "division": 1, "startPage": 1, "maxItems": 10 } ``` # 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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "competition": "open", "year": 2024, "division": 1, "scaled": false, "region": 0, "startPage": 1, "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/crossfit-games-leaderboard-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "competition": "open", "year": 2024, "division": 1, "scaled": False, "region": 0, "startPage": 1, "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/crossfit-games-leaderboard-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "competition": "open", "year": 2024, "division": 1, "scaled": false, "region": 0, "startPage": 1, "maxItems": 10 }' | apify call jungle_synthesizer/crossfit-games-leaderboard-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/crossfit-games-leaderboard-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "CrossFit Games & Open Leaderboard Scraper", "description": "Scrape athlete leaderboard data from the official CrossFit Games API. Covers the Open, Quarterfinals, Semifinals, and Games across all years and divisions. Returns per-athlete rank, score, region, affiliate, and per-workout scores.", "version": "0.1", "x-build-id": "OUc8cbTfeCcndX0f0" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~crossfit-games-leaderboard-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-crossfit-games-leaderboard-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/jungle_synthesizer~crossfit-games-leaderboard-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-crossfit-games-leaderboard-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/jungle_synthesizer~crossfit-games-leaderboard-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-crossfit-games-leaderboard-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": [ "competition", "year", "division" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "competition": { "title": "Competition type", "enum": [ "open", "games", "quarterfinals", "semifinals" ], "type": "string", "description": "CrossFit competition type: open, games, quarterfinals, or semifinals" }, "year": { "title": "Year", "type": "integer", "description": "Competition year (e.g. 2024). Defaults to the most recent Open year." }, "division": { "title": "Division ID", "type": "integer", "description": "Division numeric ID. 1=Men, 2=Women, 3=Men 35-39, 4=Women 35-39, 5=Men 40-44, 6=Women 40-44, 7=Men 45-49, 8=Women 45-49, 9=Men 50-54, 10=Women 50-54, 11=Men 55-59, 12=Women 55-59, 13=Men 60+, 14=Women 60+, 17=Teen Boys 16-17, 18=Teen Girls 16-17, 19=Teen Boys 14-15, 20=Teen Girls 14-15, 30=Team. Default: 1 (Men)." }, "scaled": { "title": "Scaled division", "type": "boolean", "description": "Set to true to fetch scaled leaderboard instead of Rx." }, "region": { "title": "Region ID", "type": "integer", "description": "Region filter ID. 0 = worldwide (all regions). Set to a specific region ID to filter." }, "startPage": { "title": "Start page", "type": "integer", "description": "First leaderboard page to fetch (1-indexed). Use with endPage for partial pulls." }, "endPage": { "title": "End page (optional)", "type": "integer", "description": "Last leaderboard page to fetch. Omit to fetch all pages up to totalPages or maxItems." }, "maxItems": { "title": "Max items", "type": "integer", "description": "Maximum number of leaderboard rows to return across all pages." } } }, "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 } } } } } } } } } } ```