# iRacing Data Driver Stats Scraper (`jungle_synthesizer/iracing-data-driver-stats-scraper`) Actor Extract iRacing driver profiles, iRating and Safety Rating history, race results, and season standings. Look up drivers by customer ID, fetch a specific race session, pull leaderboards by category, or browse recent race results. - **URL**: https://apify.com/jungle\_synthesizer/iracing-data-driver-stats-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Sports, Business, Lead generation - **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 ## iRacing Data Driver Stats Scraper Extract iRacing driver profiles, iRating and Safety Rating history, race results, and season standings — no iRacing account required. Data is sourced from the iracingdata.com public API (`iracing6-backend.herokuapp.com`), an open community aggregator that mirrors iRacing session and leaderboard data. The actor supports four scrape modes to cover the most common use cases. --- ### What you get Each record includes a `record_type` field indicating which mode produced it: | `record_type` | Description | |---------------|-------------| | `recent_race` | Summary of the most recently completed races across all series | | `leaderboard_entry` | Top-N drivers by iRating within a category | | `race_result` | Per-driver result row for a specific race session | | `driver_profile` | Career stats for a specific driver (by cust_id) | #### Key fields - **cust_id** — iRacing customer ID (stable primary key) - **display_name** — driver display name - **irating / irating_after / irating_delta** — iRating before and after a race - **license_class** — Rookie / D / C / B / A / Pro (derived from license_level) - **safety_rating / safety_rating_after** — SR as a 0-4.99 float - **cpi** — corners-per-incident score - **finish_position, laps_complete, incidents, champ_points** — race result metrics - **track_name, car_name, season_name** — session context - **event_strength_of_field** — average iRating of all participants in the session --- ### Input #### Mode: `recent` (default) Returns the most recently completed race sessions across all series. ```json { "mode": "recent", "maxItems": 15 } ```` `maxItems` caps the number of session summaries returned (max 200). #### Mode: `leaderboard` Returns the top-N drivers by iRating for a category. ```json { "mode": "leaderboard", "leaderboardCategory": "oval", "maxItems": 15 } ``` Valid categories: `oval`, `road`, `dirt_oval`, `dirt_road`, `sports_car`, `formula_car`, `combined`. Each run returns up to 100 entries (the full top-100 for that category). #### Mode: `by_session` Fetches all per-driver results for a specific iRacing subsession ID. Returns one record per driver per session type (Practice, Qualifying, Race). ```json { "mode": "by_session", "subsessionId": 85685577, "maxItems": 50 } ``` Find subsession IDs from the `recent` mode output or from iRacing session URLs. #### Mode: `by_driver` Look up career stats for specific drivers by their iRacing customer ID. ```json { "mode": "by_driver", "custIds": ["33988", "374558"], "maxItems": 10 } ``` Note: The iracingdata.com backend indexes drivers on-demand. If a driver isn't in their database yet, they are queued and no record is returned for that run. Run again later. *** ### Output format Output is a flat dataset (one JSON object per record). Arrays are not used — all data is scalar. Example `leaderboard_entry` record: ```json { "record_type": "leaderboard_entry", "rank": 1, "cust_id": 33988, "display_name": "Justin Brooks", "irating": 11205, "leaderboard_category": "oval", "scraped_at": "2026-05-12T11:27:31.000Z" } ``` Example `race_result` record: ```json { "record_type": "race_result", "cust_id": 818442, "display_name": "Joosep Laiksoo", "irating": 3084, "irating_after": 3131, "irating_delta": 47, "license_class": "B", "safety_rating": 4.57, "finish_position": 0, "laps_complete": 6, "incidents": 0, "track_name": "Sonoma Raceway", "car_name": "FIA Cross Car", "season_name": "FIA Cross Car Championship - 2026 Season 2", "start_time_utc": "2026-05-12T10:45:00Z" } ``` *** ### Use cases - **League management** — pull weekly standings and results for championship tracking - **Sim coaching** — track driver iRating and SR progression over sessions - **Content creation** — weekly stats packages for YouTube / Twitch streams - **DFS / esports modelling** — historical iRating trajectories and race result data - **Discord bots / leaderboards** — live top-N iRating feeds by category *** ### Pricing Pay-per-event: $0.10 per run start + $0.001 per record scraped. A leaderboard pull of 100 drivers costs ~$0.20. A full race session with 30 drivers across Practice/Qualifying/Race costs ~$0.19. *** ### Data source Data comes from the iracingdata.com community aggregator (`iracing6-backend.herokuapp.com`), not directly from iRacing's servers. No iRacing account or credentials are required. The backend updates leaderboards approximately every 2 hours and ingests race results continuously. # 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. ## `mode` (type: `string`): What to scrape. 'by\_driver': look up drivers by cust\_id. 'by\_session': fetch all results for a specific subsession. 'leaderboard': top-N iRatings by category. 'recent': most recently completed races. ## `custIds` (type: `array`): iRacing customer IDs to look up (used when mode=by\_driver). E.g. \[33988, 374558]. ## `subsessionId` (type: `integer`): iRacing subsession (race) ID to fetch all driver results for (used when mode=by\_session). ## `leaderboardCategory` (type: `string`): Category for leaderboard mode. One of: oval, road, dirt\_oval, dirt\_road, sports\_car, formula\_car, combined. ## `maxItems` (type: `integer`): Maximum number of records to return. For leaderboard mode this caps the top-N list. For recent mode this caps the number of race sessions. ## 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...", "mode": "recent", "custIds": [], "leaderboardCategory": "road", "maxItems": 15 } ``` # 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...", "mode": "recent", "leaderboardCategory": "road", "maxItems": 15 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/iracing-data-driver-stats-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...", "mode": "recent", "leaderboardCategory": "road", "maxItems": 15, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/iracing-data-driver-stats-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...", "mode": "recent", "leaderboardCategory": "road", "maxItems": 15 }' | apify call jungle_synthesizer/iracing-data-driver-stats-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/iracing-data-driver-stats-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "iRacing Data Driver Stats Scraper", "description": "Extract iRacing driver profiles, iRating and Safety Rating history, race results, and season standings. Look up drivers by customer ID, fetch a specific race session, pull leaderboards by category, or browse recent race results.", "version": "0.1", "x-build-id": "wqEa9WJdHjny5urxg" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~iracing-data-driver-stats-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-iracing-data-driver-stats-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~iracing-data-driver-stats-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-iracing-data-driver-stats-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~iracing-data-driver-stats-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-iracing-data-driver-stats-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", "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." }, "mode": { "title": "Scrape Mode", "enum": [ "by_driver", "by_session", "leaderboard", "recent" ], "type": "string", "description": "What to scrape. 'by_driver': look up drivers by cust_id. 'by_session': fetch all results for a specific subsession. 'leaderboard': top-N iRatings by category. 'recent': most recently completed races.", "default": "recent" }, "custIds": { "title": "Driver Customer IDs", "type": "array", "description": "iRacing customer IDs to look up (used when mode=by_driver). E.g. [33988, 374558].", "items": { "type": "string" }, "default": [] }, "subsessionId": { "title": "Subsession ID", "type": "integer", "description": "iRacing subsession (race) ID to fetch all driver results for (used when mode=by_session)." }, "leaderboardCategory": { "title": "Leaderboard Category", "enum": [ "oval", "road", "dirt_oval", "dirt_road", "sports_car", "formula_car", "combined" ], "type": "string", "description": "Category for leaderboard mode. One of: oval, road, dirt_oval, dirt_road, sports_car, formula_car, combined.", "default": "road" }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of records to return. For leaderboard mode this caps the top-N list. For recent mode this caps the number of race sessions.", "default": 15 } } }, "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 } } } } } } } } } } ```