# 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:** 4 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $19.00 / 1,000 results 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 ![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 } } } } } } } } } } ```