# Cricsheet Ball-by-Ball Match Data Scraper (`jungle_synthesizer/cricsheet-ball-by-ball-match-data-scraper`) Actor Downloads and parses Cricsheet's ball-by-ball cricket match archives (Test, ODI, T20I, IPL, BBL and more). Returns one record per delivery with match metadata, innings, over, batter, bowler, runs, wicket, and extras — the highest-granularity cricket analytics dataset available. - **URL**: https://apify.com/jungle\_synthesizer/cricsheet-ball-by-ball-match-data-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Sports, AI, Education - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 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. 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 ## Cricsheet Ball-by-Ball Match Data Scraper Downloads and parses Cricsheet's open ball-by-ball cricket match archives. Returns one record per delivery — match metadata, innings, over, batter, bowler, runs scored, wickets, and extras — for every format in the Cricsheet dataset. Cricsheet is the de-facto open cricket dataset used by fantasy platforms, betting models, and academic researchers. It covers Test, ODI, T20I, IPL, BBL, and dozens of other competitions. This actor flattens the archive into queryable per-delivery rows, which is the highest-granularity cricket analytics format available. ### What you get Each output record represents a single ball bowled: | Field | Description | |-------|-------------| | `match_id` | Cricsheet unique match identifier | | `competition` | Competition name (e.g. Indian Premier League) | | `format` | Match type (test, odi, t20) | | `match_date` | Date of the match (YYYY-MM-DD) | | `venue` | Ground name and city | | `team_a` / `team_b` | Both teams | | `batting_team` | Which team is batting in this innings | | `toss_winner` | Team that won the toss | | `result` | Match result | | `innings` | Innings number (1 or 2) | | `over` | Over number (0-indexed) | | `ball` | Ball within the over | | `batter` | Batter facing | | `non_striker` | Non-striking batter | | `bowler` | Bowler | | `runs_batter` | Runs off the bat | | `runs_extras` | Extra runs | | `runs_total` | Total runs from this delivery | | `wicket_kind` | How the wicket fell (caught, bowled, lbw, run_out...) | | `wicket_player_out` | Player dismissed (empty if no wicket) | | `extras_type` | Type of extra (wides, noball, byes, legbyes) | ### Input | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `matchFormat` | string | `t20s` | Format archive to download: `all`, `tests`, `mdms`, `odis`, `t20s`, `t20is`, `ipl`, `bbl` | | `maxMatches` | integer | 5 | Maximum matches to process. Leave blank for the full archive. | | `maxItems` | integer | 100 | Maximum delivery records to return. | #### Format options - `all` — every match in the Cricsheet database (~22,000 matches, 141 MB) - `tests` — Test matches only (~900 matches) - `mdms` — Multi-day matches (~2,100 matches) - `odis` — One-day internationals (~3,100 matches) - `t20s` — T20 leagues worldwide (~5,400 matches) - `t20is` — T20 internationals only (~320 matches) - `ipl` — Indian Premier League - `bbl` — Big Bash League ### Usage notes **Scale.** A full `all` run with no `maxMatches` cap returns millions of delivery records. For most analytics use cases, select a specific format and set reasonable caps. **Resumable runs.** `maxItems` caps the total deliveries emitted. `maxMatches` controls how many matches are parsed before stopping — useful when you need complete match records rather than a truncated mid-match stream. **Attribution.** Cricsheet data is released under the Open Database License (ODbL). Give credit to [Cricsheet.org](https://cricsheet.org) when you publish work derived from this data. ### Data source [Cricsheet.org](https://cricsheet.org) — a community cricket data project providing ball-by-ball data for international and major T20 league cricket since 2005. The archive is updated regularly as new matches are played. # 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. ## `matchFormat` (type: `string`): Filter by match format: all, tests, mdms (multi-day), odis, t20s, t20is, ipl, bbl. Default: t20s ## `maxMatches` (type: `integer`): Maximum number of matches to process. Leave blank for all matches in the selected format. ## `maxItems` (type: `integer`): Maximum number of ball-by-ball delivery records to return. ## 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...", "matchFormat": "t20s", "maxMatches": 5, "maxItems": 100 } ```` # 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...", "matchFormat": "t20s", "maxMatches": 5, "maxItems": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/cricsheet-ball-by-ball-match-data-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...", "matchFormat": "t20s", "maxMatches": 5, "maxItems": 100, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/cricsheet-ball-by-ball-match-data-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...", "matchFormat": "t20s", "maxMatches": 5, "maxItems": 100 }' | apify call jungle_synthesizer/cricsheet-ball-by-ball-match-data-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/cricsheet-ball-by-ball-match-data-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Cricsheet Ball-by-Ball Match Data Scraper", "description": "Downloads and parses Cricsheet's ball-by-ball cricket match archives (Test, ODI, T20I, IPL, BBL and more). Returns one record per delivery with match metadata, innings, over, batter, bowler, runs, wicket, and extras — the highest-granularity cricket analytics dataset available.", "version": "0.1", "x-build-id": "bmOxKc2r97omEYYFq" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~cricsheet-ball-by-ball-match-data-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-cricsheet-ball-by-ball-match-data-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~cricsheet-ball-by-ball-match-data-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-cricsheet-ball-by-ball-match-data-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~cricsheet-ball-by-ball-match-data-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-cricsheet-ball-by-ball-match-data-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": [ "matchFormat" ], "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." }, "matchFormat": { "title": "Match Format", "enum": [ "all", "tests", "mdms", "odis", "t20s", "t20is", "ipl", "bbl" ], "type": "string", "description": "Filter by match format: all, tests, mdms (multi-day), odis, t20s, t20is, ipl, bbl. Default: t20s" }, "maxMatches": { "title": "Max Matches", "type": "integer", "description": "Maximum number of matches to process. Leave blank for all matches in the selected format." }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of ball-by-ball delivery records to return." } } }, "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 } } } } } } } } } } ```