# WNBA Stats Scraper | Player & Team Season Statistics (`parseforge/wnba-stats-scraper`) Actor Export WNBA.com player and team season statistics: player ID, name, team, games played, minutes, points, rebounds, assists, shooting percentages and rankings. Filter by season and stat category (PTS, REB, AST, BLK, STL, FG\_PCT). CSV, Excel, JSON, XML output. - **URL**: https://apify.com/parseforge/wnba-stats-scraper.md - **Developed by:** [ParseForge](https://apify.com/parseforge) (community) - **Categories:** Other, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ![ParseForge Banner](https://github.com/ParseForge/apify-assets/blob/ad35ccc13ddd068b9d6cba33f323962e39aed5b2/banner.jpg?raw=true) ## ๐Ÿ€ WNBA Stats Scraper > ๐Ÿš€ **Export export wnba player and team statistics from the official stats api in seconds.** Export WNBA.com player and team season statistics: player ID, name, team, games played, minutes, points, rebounds, assists, shooting percentages and rankings. Filter by season and stat category (PTS, REB, AST, BLK, STL, FG_PCT). CSV, Excel, JSON, XML output. No account required for the source. > ๐Ÿ•’ **Last updated:** 2026-05-26 ยท **๐Ÿ“Š 21 fields** per record ยท **20+ years of player season statistics** ยท **WNBA (all seasons since 1997)** The WNBA Stats Scraper extracts structured records from WNBA.com. Every record captures the canonical fields you would expect from the upstream source - ready for analytics, dashboards, BI tooling, or further enrichment. The dataset spans wnba (all seasons since 1997) and exposes the same data the official source publishes - normalised, paginated, and exportable. **Who uses this data?** | Audience | Use Case | |---|---| | Sports analysts | Build longitudinal datasets for analysis | | Compliance teams | Monitor regulated entities and filings | | Journalists | Investigate public records at scale | | Data analysts | Power BI dashboards and reports | | Academic researchers | Run quantitative studies on public data | | Product teams | Embed live wnba stats records into apps | ### ๐Ÿ“‹ What the WNBA Stats Scraper does - Queries WNBA.com for the latest records - Supports targeted filtering via the input parameters (see below) - Returns structured records with 21 fields, no scraping artifacts - Handles pagination automatically up to your `maxItems` limit - Cleans HTML entities and normalises dates and identifiers - Delivers results as CSV, Excel, JSON, or XML via Apify dataset export > ๐Ÿ’ก **Why it matters:** Public-data sources rarely offer bulk export. This Actor turns the live source into a queryable dataset - useful for any team that needs wnba stats data at scale. ### ๐ŸŽฌ Full Demo _๐Ÿšง Coming soon_ ### โš™๏ธ Input
FieldTypeRequiredDescription
maxItemsintegerNoFree users: 10. Paid users: optional, max 1,000,000.
seasonstringNoWNBA season year (e.g. 2024, 2023, 2022).
seasonTypestringNoRegular Season or Playoffs.
statCategorystringNoSorting stat.
perModestringNoPer-game or totals.
**Example 1: Default run (preview)** ```json { "maxItems": 10 } ```` **Example 2: Targeted query** ```json { "maxItems": 5, "season": "2024", "statCategory": "PTS" } ``` > โš ๏ธ **Good to Know:** Free users are limited to 10 items per run. Upgrade to a paid plan to unlock up to 1,000,000 items. ### ๐Ÿ“Š Output | Field | Type | Description | |---|---|---| | ๐Ÿ”‘ Player ID `playerId` | string | - | | ๐Ÿ† Rank `rank` | string | - | | ๐Ÿ‘ค Player `player` | string | - | | ๐Ÿ”‘ Team ID `teamId` | string | - | | ๐Ÿ€ Team `team` | string | - | | ๐Ÿ“… Season `season` | string | - | | ๐Ÿ“‹ Type `seasonType` | string | - | | ๐Ÿ“Š Stat `statCategory` | string | - | | ๐ŸŽฏ GP `gamesPlayed` | string | - | | โฑ๏ธ MIN `minutes` | string | - | | ๐ŸŽฏ PTS `points` | string | - | | ๐Ÿชฃ REB `rebounds` | string | - | | ๐Ÿค AST `assists` | string | - | | ๐Ÿฅท STL `steals` | string | - | | ๐Ÿ›ก๏ธ BLK `blocks` | string | - | | ๐ŸŽฏ FG% `fgPct` | string | - | | ๐ŸŽฏ 3P% `fg3Pct` | string | - | | ๐ŸŽฏ FT% `ftPct` | string | - | | โญ EFF `eff` | string | - | | ๐Ÿ•’ Collected `scrapedAt` | string | - | | โŒ Error `error` | string | Error message if record could not be retrieved | ### โœจ Why choose this Actor | Feature | Detail | |---|---| | ๐ŸŒ No login required | Public data only - no credentials needed | | ๐Ÿ” Targeted filtering | Search by name, code, date range, type | | ๐Ÿ“Š 20+ years of player season statistics | Comprehensive coverage of wnba (all seasons since 1997) | | ๐Ÿงน Clean output | Dates normalised, HTML stripped, arrays flattened | | โšก Fast API | Direct source access - no browser overhead | | ๐Ÿ”„ Auto-pagination | Retrieves all matching results up to your maxItems | | ๐Ÿ’พ 4 export formats | CSV, Excel, JSON, XML all available | | ๐Ÿ›ก๏ธ Retry logic | Multi-attempt retry with backoff for reliability | ### ๐Ÿ“ˆ How it compares to alternatives | Method | Speed | Scale | Structured Output | Free | |---|---|---|---|---| | **This Actor** | Fast | 1,000,000 records | Yes (21 fields) | 10 free / unlimited paid | | Manual site search | Slow | Limited per session | No | Yes | | Bulk data download | Slow setup | Variable | Partial | Variable | | Custom API script | Variable | Unlimited | Requires dev work | Dev cost | ### ๐Ÿš€ How to use 1. **[Create a free Apify account](https://console.apify.com/sign-up?fpr=vmoqkp)** - includes $5 free credit 2. Open the **WNBA Stats Scraper** actor page 3. Configure your input - set filters or leave defaults 4. Set `maxItems` (10 for a quick preview, higher for bulk extraction) 5. Click **Run** and wait for the dataset to populate 6. Download your results as **CSV, Excel, JSON, or XML** ### ๐Ÿ’ผ Business use cases #### Compliance and Due Diligence Teams use wnba stats data to verify entities, monitor regulatory status, and feed downstream pipelines. #### Market Research Analysts map wnba (all seasons since 1997) to understand market structure, competitive activity, or regulatory trends. #### Lead Generation Sales teams enrich CRM records with wnba stats data to identify prospects and qualify leads. #### Investigative Journalism Reporters use bulk extracts to find patterns, anomalies, and stories hidden in public records. ### ๐Ÿ”Œ Automating WNBA Stats Scraper Connect this Actor to your existing workflows using Apify integrations: - **Make (Integromat)** - trigger a run on a schedule and push results to Google Sheets or a database - **Zapier** - automatically export new records to Airtable, Notion, or your CRM - **Slack** - get notified when a monitored entity has new activity - **Webhooks** - receive real-time notifications when a run completes ### ๐ŸŒŸ Beyond business use cases #### Academic Research Study trends, behaviours, and patterns in wnba (all seasons since 1997) records across time. #### Civic Tech and Transparency Civic-tech projects build dashboards on top of bulk extracts to surface public-interest insights. #### Education Educators use real wnba stats data to teach data analysis and domain knowledge. #### Personal Research Individuals - researchers, hobbyists, family historians - use bulk export to answer questions that no single web search can. ### ๐Ÿค– Ask an AI assistant about this scraper Have questions about how to use this Actor or interpret the data? Paste a few sample records into ChatGPT, Claude, or another AI assistant and ask it to summarise the dataset, explain fields, identify patterns, or suggest filter combinations. ### โ“ Frequently Asked Questions **๐Ÿ” What does this Actor do?** It extracts wnba stats records from WNBA.com into a clean, queryable dataset. **๐Ÿ“Š How many records are available?** 20+ years of player season statistics. **๐Ÿ”‘ Do I need an account or API key?** No. This Actor uses public sources that require no authentication. **๐Ÿ“… How up-to-date is the data?** The Actor queries the source live on every run. **๐Ÿ” Can I filter by specific fields?** Yes - see the Input section above for all supported filters. **โšก How fast is the scraper?** A typical 10-item preview completes in under 30 seconds. **๐Ÿ“„ What format is the output?** Records are stored in Apify's dataset storage and can be exported as CSV, Excel, JSON, or XML. **๐Ÿ† Why are some fields null for certain records?** Some fields are optional at the source. The Actor returns `null` rather than fabricating values. **๐Ÿ“‹ Can I run this on a schedule?** Yes - use Apify's built-in scheduler or trigger via Make / Zapier / Webhooks. **๐Ÿ’ฐ Is there a cost to use this Actor?** Free users receive 10 records per run. [Create a paid account](https://console.apify.com/sign-up?fpr=vmoqkp) to unlock up to 1,000,000 records per run. **๐ŸŒ Does it cover wnba (all seasons since 1997)?** Yes - see the coverage line above. **๐Ÿ›ก๏ธ Is this Actor compliant?** The Actor accesses only publicly available data, in line with the source's published terms of service. ### ๐Ÿ”Œ Integrate with any app Export data directly from the Apify platform to: **Spreadsheets & Databases** Google Sheets - Microsoft Excel - Airtable - Notion - PostgreSQL - MySQL - MongoDB **Automation & Workflows** Make (Integromat) - Zapier - n8n - Pipedream - Activepieces **Cloud Storage** AWS S3 - Google Cloud Storage - Azure Blob Storage - Dropbox **APIs & Webhooks** REST API - Webhooks - Apify API ### ๐Ÿ”— Recommended Actors | Actor | Description | |---|---| | [OurAirports Global Airport Database Scraper](https://apify.com/parseforge/ourairports-scraper) | Export worldwide airport data including ICAO/IATA codes | | [FINRA BrokerCheck Scraper](https://apify.com/parseforge/finra-brokercheck-scraper) | Extract broker and firm registration data from FINRA | | [USPTO Patent Assignments Scraper](https://apify.com/parseforge/uspto-patent-assignments-scraper) | Extract USPTO patent ownership and assignment records | > ๐Ÿ’ก **Pro Tip:** browse the complete [ParseForge collection](https://apify.com/parseforge) for more public-data scrapers. *** Need help? Visit the [Apify Discord community](https://discord.gg/jyEM2PRvMU) or open a support ticket. **Disclaimer:** This Actor accesses publicly available data from WNBA.com in compliance with the source's terms of service. Data is provided as-is for informational purposes. Verify all records against the official source before relying on them for legal or business decisions. # Actor input Schema ## `maxItems` (type: `integer`): Free users: 10. Paid users: optional, max 1,000,000. ## `season` (type: `string`): WNBA season year (e.g. 2024, 2023, 2022). ## `seasonType` (type: `string`): Regular Season or Playoffs. ## `statCategory` (type: `string`): Sorting stat. ## `perMode` (type: `string`): Per-game or totals. ## Actor input object example ```json { "maxItems": 10, "season": "2024", "seasonType": "Regular Season", "statCategory": "PTS", "perMode": "PerGame" } ``` # 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 = { "maxItems": 10, "season": "2024" }; // Run the Actor and wait for it to finish const run = await client.actor("parseforge/wnba-stats-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "maxItems": 10, "season": "2024", } # Run the Actor and wait for it to finish run = client.actor("parseforge/wnba-stats-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "maxItems": 10, "season": "2024" }' | apify call parseforge/wnba-stats-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parseforge/wnba-stats-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "WNBA Stats Scraper | Player & Team Season Statistics", "description": "Export WNBA.com player and team season statistics: player ID, name, team, games played, minutes, points, rebounds, assists, shooting percentages and rankings. Filter by season and stat category (PTS, REB, AST, BLK, STL, FG_PCT). CSV, Excel, JSON, XML output.", "version": "0.1", "x-build-id": "NyczmBzF47lcZivai" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parseforge~wnba-stats-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parseforge-wnba-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parseforge~wnba-stats-scraper/runs": { "post": { "operationId": "runs-sync-parseforge-wnba-stats-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parseforge~wnba-stats-scraper/run-sync": { "post": { "operationId": "run-sync-parseforge-wnba-stats-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 1000000, "type": "integer", "description": "Free users: 10. Paid users: optional, max 1,000,000." }, "season": { "title": "Season", "type": "string", "description": "WNBA season year (e.g. 2024, 2023, 2022)." }, "seasonType": { "title": "Season Type", "enum": [ "Regular Season", "Playoffs", "Pre Season", "All Star" ], "type": "string", "description": "Regular Season or Playoffs.", "default": "Regular Season" }, "statCategory": { "title": "Stat Category", "enum": [ "PTS", "REB", "AST", "STL", "BLK", "FG_PCT", "FG3_PCT", "FT_PCT", "MIN", "EFF" ], "type": "string", "description": "Sorting stat.", "default": "PTS" }, "perMode": { "title": "Per Mode", "enum": [ "PerGame", "Totals", "Per48" ], "type": "string", "description": "Per-game or totals.", "default": "PerGame" } } }, "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 } } } } } } } } } } ```