# Speedrun.com Scraper (`crawlerbros/speedruncom-scraper`) Actor Scrape Speedrun.com â€" the largest speedrunning leaderboard and community. Search games, browse leaderboard runs, and look up world records. Returns game details, run times, runners, video proof links, and platform info. - **URL**: https://apify.com/crawlerbros/speedruncom-scraper.md - **Developed by:** [Crawler Bros](https://apify.com/crawlerbros) (community) - **Categories:** Videos, Automation, Other - **Stats:** 2 total users, 1 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 ## Speedrun.com Scraper Scrape [Speedrun.com](https://www.speedrun.com) — the world's largest speedrunning leaderboard platform with thousands of games, millions of verified runs, and active communities for every genre. Search for games, pull leaderboard positions, or browse the most recent verified submissions. ### Features - **Three data modes**: game search, category leaderboards, or recent verified runs - **Full run metadata**: time in seconds and formatted string, place on leaderboard, runner name, video proof, platform, and submission date - **Rich game data**: release year, platforms, genres, community Discord, and direct links - **Human-readable time format**: run times displayed as `h:mm:ss.mmm` or `m:ss.mmm` alongside raw seconds - **No authentication required**: uses the public Speedrun.com REST API v1 ### Use Cases - Monitor world records and top-10 leaderboard positions for popular games - Track speedrunning community activity and new verified submissions - Research game popularity across the speedrunning community - Analyze run time distributions for specific categories (Any%, 100%, etc.) - Build speedrunning news feeds and record-tracker applications ### Input | Field | Type | Description | Default | |-------|------|-------------|---------| | `mode` | Select | Data mode: `searchGames`, `leaderboard`, or `recentRuns` | `searchGames` | | `keyword` | Text | Game search keyword (mode=searchGames) | `mario` | | `gameId` | Text | Game abbreviation or ID for leaderboard/recentRuns (e.g. `sm64`, `oot`, `celeste`) | `sm64` | | `categoryId` | Text | Category ID for leaderboard mode (auto-detected if blank) | — | | `maxItems` | Integer | Maximum number of records to return (1–500) | `20` | ### Output #### Game Record | Field | Type | Description | |-------|------|-------------| | `recordType` | String | Always `"game"` | | `gameId` | String | Unique game ID on Speedrun.com | | `gameName` | String | Official game name | | `gameAbbreviation` | String | Short game abbreviation used in URLs | | `gameUrl` | String | Direct link to the game's Speedrun.com page | | `releaseYear` | Integer | Year the game was released | | `releaseDate` | String | Full release date (YYYY-MM-DD) | | `platforms` | Array | Platform names (e.g., Nintendo 64, PC) | | `genres` | Array | Genre tags (e.g., Platformer, Action) | | `discord` | String | Community Discord invite URL | | `scrapedAt` | String | ISO 8601 scrape timestamp | #### Run Record | Field | Type | Description | |-------|------|-------------| | `recordType` | String | Always `"run"` | | `runId` | String | Unique run ID | | `runUrl` | String | Direct link to the run page | | `gameId` | String | Game ID | | `gameName` | String | Game name | | `categoryId` | String | Category ID | | `category` | String | Category name (e.g., Any%, 120 Star) | | `timeSeconds` | Number | Run time in seconds (raw float) | | `time` | String | Formatted run time (e.g., `1:39:32.000`) | | `place` | Integer | Leaderboard position (leaderboard mode only) | | `runnerName` | String | Runner username(s), comma-separated for co-op | | `runnerId` | String | Runner user ID | | `platformId` | String | Platform ID the run was submitted on | | `emulated` | Boolean | Whether the run used emulation | | `videoUrl` | String | Video proof URL (YouTube, Twitch, etc.) | | `submittedAt` | String | ISO 8601 submission timestamp | | `status` | String | Run status: `verified`, `new`, or `rejected` | | `comment` | String | Runner's submission comment | | `scrapedAt` | String | ISO 8601 scrape timestamp | ### Example Output ```json { "recordType": "run", "runId": "run12345", "runUrl": "https://www.speedrun.com/run/run12345", "gameId": "o1y9wo6q", "gameName": "Super Mario 64", "categoryId": "cat001", "category": "120 Star", "timeSeconds": 6039.0, "time": "1:40:39.000", "place": 1, "runnerName": "Cheese05", "runnerId": "player1", "platformId": "n64", "emulated": false, "videoUrl": "https://www.twitch.tv/videos/123456", "submittedAt": "2026-05-01T10:00:00Z", "status": "verified", "scrapedAt": "2026-06-04T15:30:00.000000+00:00" } ```` ### FAQs **Does this require an API key?** No. The Speedrun.com API (`www.speedrun.com/api/v1`) is fully public and requires no authentication for read-only data. **What game abbreviations can I use?** Common examples: `sm64` (Super Mario 64), `oot` (Ocarina of Time), `celeste` (Celeste), `minecraft` (Minecraft: Java Edition), `portal2` (Portal 2). You can find a game's abbreviation in its Speedrun.com URL. **What is the difference between leaderboard and recentRuns modes?** `leaderboard` returns the top N ranked runs for the first (or specified) category of a game, ordered by time. `recentRuns` returns the most recently verified runs across all games, ordered by submission date. **How are co-op runs handled?** Co-op runs list all runner names joined by a comma in the `runnerName` field. **Are all times comparable?** Only runs within the same game and category are directly comparable. Times use the primary timing method set by the game's moderators (real time, in-game time, etc.). **What is the rate limit?** The Speedrun.com API enforces a rate limit with HTTP 420 responses. This scraper automatically waits and retries when rate-limited. # Actor input Schema ## `mode` (type: `string`): What to fetch. ## `keyword` (type: `string`): Game name to search for (mode=searchGames). ## `gameId` (type: `string`): Speedrun.com game ID or abbreviation (mode=leaderboard). Example: smb1, sm64, mkwii. ## `categoryId` (type: `string`): Speedrun.com category ID. Leave empty to fetch the first (main) category. ## `maxItems` (type: `integer`): Maximum number of records to return. ## Actor input object example ```json { "mode": "searchGames", "keyword": "mario", "gameId": "sm64", "maxItems": 20 } ``` # Actor output Schema ## `items` (type: `string`): Speedrun records, games, and leaderboards from speedrun.com. # 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": "searchGames", "keyword": "mario", "gameId": "sm64", "maxItems": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("crawlerbros/speedruncom-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": "searchGames", "keyword": "mario", "gameId": "sm64", "maxItems": 20, } # Run the Actor and wait for it to finish run = client.actor("crawlerbros/speedruncom-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": "searchGames", "keyword": "mario", "gameId": "sm64", "maxItems": 20 }' | apify call crawlerbros/speedruncom-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=crawlerbros/speedruncom-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Speedrun.com Scraper", "description": "Scrape Speedrun.com â€\" the largest speedrunning leaderboard and community. Search games, browse leaderboard runs, and look up world records. Returns game details, run times, runners, video proof links, and platform info.", "version": "0.1", "x-build-id": "2HkLrHVjdaHgsXVmi" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/crawlerbros~speedruncom-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-crawlerbros-speedruncom-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/crawlerbros~speedruncom-scraper/runs": { "post": { "operationId": "runs-sync-crawlerbros-speedruncom-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/crawlerbros~speedruncom-scraper/run-sync": { "post": { "operationId": "run-sync-crawlerbros-speedruncom-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "searchGames", "leaderboard", "recentRuns" ], "type": "string", "description": "What to fetch.", "default": "searchGames" }, "keyword": { "title": "Game keyword", "type": "string", "description": "Game name to search for (mode=searchGames).", "default": "mario" }, "gameId": { "title": "Game ID or abbreviation", "type": "string", "description": "Speedrun.com game ID or abbreviation (mode=leaderboard). Example: smb1, sm64, mkwii.", "default": "sm64" }, "categoryId": { "title": "Category ID (mode=leaderboard)", "type": "string", "description": "Speedrun.com category ID. Leave empty to fetch the first (main) category." }, "maxItems": { "title": "Max items", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of records to return.", "default": 20 } } }, "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 } } } } } } } } } } ```