WNBA Stats Scraper
Pricing
from $19.00 / 1,000 results
WNBA Stats Scraper
Scrapes official WNBA player statistics by season, season type, and stat category. Returns each player's stat line as a flat row for analysis.
Pricing
from $19.00 / 1,000 results
Rating
0.0
(0)
Developer
ParseForge
Maintained by CommunityActor stats
1
Bookmarked
12
Total users
1
Monthly active users
4 days ago
Last modified
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WNBA Stats Scraper
Scrape official WNBA player stats for any season, stat category, and game type, up to a million records per run. Get points, rebounds, assists, shooting percentages, and advanced metrics in a flat, analysis-ready table. Export to CSV, JSON, Excel, or XML.
The WNBA's official stats site holds a deep history of player performance data, but manually copying tables for analysis is slow and error-prone. This actor reads the league's public stat feeds directly, letting you pull complete leaderboards filtered by season, season type, and stat category. It returns every player's numbers in one consistent schema, ready for spreadsheets or databases.
| Who uses it | What they scrape WNBA Stats for |
|---|---|
| Sports analysts | Compare player efficiency and scoring trends across multiple WNBA seasons. |
| Fantasy sports players | Pull per-game averages to build draft rankings and identify waiver-wire pickups. |
| Journalists and bloggers | Gather official stats to support game recaps, player profiles, and league features. |
| Data scientists | Build predictive models for player performance using historical WNBA data. |
What it does
This Actor collects WNBA player statistics by season, season type, and stat category, and returns each player's stat line as a flat row.
- 🏀 Season selection: Choose any WNBA season, from the league's inaugural year to the current one.
- 📊 Stat category sorting: Pull leaderboards sorted by points, rebounds, assists, steals, blocks, shooting percentages, minutes, or efficiency.
- 📅 Season type filter: Isolate stats for the Regular Season, Playoffs, Pre Season, or All Star games.
- 🔢 Per-mode calculation: Get stats as per-game averages, season totals, or per-48-minute rates.
- 📁 Structured output: Every player row includes their name, team, and the requested stat values in a clean, flat format.
Results export to CSV, JSON, Excel, or XML, or straight from the API.
What you can do with WNBA Stats data
📈 Track scoring leaders across eras.
A basketball historian pulls per-game points for every season since 1997 to compare the league's top scorers over time.
🏆 Build a playoff performance database.
A data analyst scrapes playoff totals for all players in the last five seasons to study clutch performance in elimination games.
⭐ Scout All Star talent.
A fantasy league commissioner collects All Star game stats to create a fun, alternative scoring format for their league.
📋 Generate pre-season reports.
A sports blogger scrapes pre-season stats to write a data-backed preview of each team's new roster additions.
Why choose this scraper
| What you get | |
|---|---|
| Official WNBA data | Stats sourced directly from the league's public feeds, matching the official record books. |
| Flexible stat views | Sort by ten different stat categories and view them per game, as totals, or per 48 minutes. |
| Complete season coverage | Access data for regular season, playoffs, pre-season, and All Star games. |
| Analysis-ready format | Returns a flat table with no nested objects, making it easy to open in Excel or load into a database. |
Configure the run
Drive the Actor by selecting a season, season type, stat category, and per-mode calculation, and set a maximum number of player records to return. The Input tab lists every parameter.
A first run with the defaults:
A larger pull:
Pricing
Pay-per-result: $0.021 per result collected. You pay only for the results written to your dataset.
| Results collected | Approximate cost |
|---|---|
| 100 results | $2.10 |
| 1,000 results | $21.00 |
| 10,000 results | $210.00 |
New Apify accounts start with $5 in free credit.
Free users
Free-plan runs return up to 10 results as a preview. Upgrade your Apify plan to collect up to 1,000,000 results per run.
Run it
- Create a free Apify account with $5 in credit.
- Open the WNBA Stats Scraper.
- Set your inputs and any filters, then click Start.
- Export the results as CSV, Excel, JSON, or XML from the Dataset tab.
Run it programmatically through the Apify API (run-sync-get-dataset-items) or the ApifyClient for JavaScript and Python.
Use with AI agents (MCP)
Give an AI agent live access to WNBA Stats through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:
Then prompt it in plain language to run the scraper and read back the results.
Troubleshooting
Why am I getting no results?
Check that the season year you entered is valid and that the season type you selected has recorded stats. For example, the 2024 Pre Season may have limited data. Try a recent Regular Season with Points to verify the actor is working.
The stats look wrong or are all zeros.
Ensure you selected the correct Per Mode. If you chose a percentage stat like Field Goal % and set Per Mode to Totals, the numbers will look very small. Switch to Per Game for standard percentage displays.
The run is taking too long.
The actor scrapes one page of the leaderboard. If you set a very high maxItems, it may paginate through many pages. Lower the maxItems to speed up the run, or check your network connection.
I got an error about the season input.
The season field expects a four-digit year as a string, like '2024'. Make sure you did not include extra characters or spaces. If the season is in the future, the site may not have data yet.
FAQ
| Question | Answer |
|---|---|
| What stats can I scrape with this actor? | You can scrape points, rebounds, assists, steals, blocks, field goal percentage, three-point percentage, free throw percentage, minutes, and efficiency. You choose one stat category per run to sort the leaderboard. |
| Can I get stats for a specific player? | This actor returns the full leaderboard for your chosen stat category, not a single player lookup. You can filter the output dataset for a specific player after the run completes. |
| Does this include advanced stats like PER or win shares? | The actor pulls the ten stat categories listed in the input: points, rebounds, assists, steals, blocks, field goal percentage, three-point percentage, free throw percentage, minutes, and efficiency. It does not include derived advanced metrics. |
| How far back does the historical data go? | You can select any season year. The WNBA's official stats database includes data back to the league's first season in 1997. |
| What is the difference between Per Game, Totals, and Per 48 Minutes? | Per Game divides a player's total stat by games played. Totals gives the raw sum for the season. Per 48 Minutes scales a player's production to a full regulation game's length, useful for comparing players with different minutes. |
| Can I get both regular season and playoff stats in one run? | No, each run is for one season type. To get both, run the actor twice, once for Regular Season and once for Playoffs, and combine the datasets. |
| Does this actor require an API key or login? | No. It reads the public stat feeds from the official WNBA website, so no API key, account, or login is needed. |
| What format is the data exported in? | You can export your results in CSV, JSON, Excel, or XML formats from the Apify dataset. |
| How many records can I scrape in one run? | You can set the maximum records up to 1,000,000. The WNBA has around 150 players per season, so a single run can easily cover many seasons if you run it multiple times. |
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Browse the full ParseForge collection for more scrapers.
🆘 Need help? Email parseforge@protonmail.com with your run ID, your input, and what you expected.
⚠️ Disclaimer. This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by WNBA Enterprises, LLC. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.
