WTA Rankings Scraper

hipersoft/wta-rankings-scraper

Scrape official WTA tennis rankings: singles and doubles, current or any past week. Rank, points, movement, tournaments played, player name, country, birth date and age. Filter by country, top-N. Export CSV, JSON or Excel.

Run this scraper →See the API call

Total users

Monthly users

Total runs

Per ranking row

$0.003

Last rebuilt

Oct 26, 2026

Overview

WTA Rankings Scraper exports the official WTA tennis rankings, both singles and doubles, for the current week or any past week. Every row has the rank, ranking points, weekly movement, tournaments played, player name, country, date of birth and age at that date. Get the top 10, the top 100 or all 1,500+ ranked players, filter by country, and export to CSV, Excel or JSON.

What does WTA Rankings Scraper do?

🎾 Singles and doubles WTA rankings.
🗓️ Historical rankings: any past ranking week, so you can rebuild rankings history for analysis.
🌍 Country filter: e.g. the top American, Spanish or Chinese players.
🔢 Top N or everyone, from the top 10 to the full ranking list.
👤 Player details: country, date of birth, age at the ranking date and profile link.

What data can you scrape?

Field	Description
`rankingType`	`singles` or `doubles`
`rankingDate`	Ranking week (YYYY-MM-DD)
`ranking`	Rank
`points`	Ranking points
`movement`	Change since the previous week
`tournamentsPlayed`	Tournaments counted
`playerId`, `name`, `firstName`, `lastName`	Player
`country`	3-letter country code
`dateOfBirth`, `age`	Birth date and age at the ranking date
`profileUrl`	WTA player page

Use cases

Sports betting and fantasy tennis: player strength features and ranking trends.
Sports journalism and data viz: top-10 history, national rankings and rising stars.
Tennis analytics: ranking trajectories, age curves and points distribution.
Apps and websites: keep ranking tables up to date with a weekly schedule.

How to scrape WTA rankings

Click Try for free to open WTA Rankings Scraper in Apify Console.
Choose singles and/or doubles.
Optionally add past ranking dates, a country and Top N.
Click Start and download the rankings as CSV, Excel or JSON.

Input

Example input

{
  "rankingTypes": ["singles", "doubles"],
  "rankingDates": ["2024-01-08", "2025-01-06"],
  "countryCode": "",
  "maxRank": 100
}

Field	Description
Rankings	Singles and/or doubles.
Ranking dates	Past weeks (YYYY-MM-DD). Empty = current ranking.
Country	3-letter country code filter.
Top N	Number of players (0 = all ranked players).

Output

{
  "rankingType": "singles",
  "ranking": 1,
  "points": 9880,
  "movement": 0,
  "tournamentsPlayed": 18,
  "rankingDate": "2024-01-08",
  "playerId": "326408",
  "name": "Iga Swiatek",
  "country": "POL",
  "dateOfBirth": "2001-05-31",
  "age": 22,
  "profileUrl": "https://www.wtatennis.com/players/326408/iga-swiatek"
}

How much does it cost?

WTA Rankings Scraper uses pay-per-row pricing: a small fixed price per ranked player, with automatic discounts on higher Apify plans. The full top 100 costs a fraction of a dollar. See the Pricing tab for the exact price.

More tennis and sports data

TennisExplorer Scraper: ATP/WTA match results, fixtures, odds and head-to-heads.
Action Network Odds Scraper: betting lines and public betting splits.
ESPN Sports Scraper: scores, schedules and standings.

FAQ

How far back do historical rankings go? Many years. Enter any past date and you get the ranking valid that week.

When are rankings updated? The WTA publishes new rankings every Monday. Schedule the scraper weekly to keep your data current.

Can I get only one country's players? Yes. Use the 3-letter code, e.g. USA, ESP, CHN.

Is the ATP (men's) ranking included? This actor covers the WTA. For men's match results and fixtures, see the TennisExplorer Scraper.

What formats can I export? CSV, Excel, JSON, XML, HTML and RSS, or read the results through the Apify API.

Can I integrate WTA Rankings Scraper with other apps? WTA Rankings Scraper can be connected with almost any cloud service or web app thanks to integrations on the Apify platform. It works with Make, Zapier, Slack, Airbyte, GitHub, Google Drive and many more, plus the Apify API, JS/Python clients and MCP. Or use webhooks to trigger an action whenever a run finishes.

Notes

Original clean-room implementation. Returns only public data; you are responsible for compliance with the WTA's terms. Not affiliated with the WTA.

Input

Field	Type	Description
`rankingTypes` Rankings	array	Singles and/or doubles rankings. Default: `["singles"]`
`rankingDates` Ranking dates (optional)	array	Past ranking weeks to fetch, as YYYY-MM-DD (e.g. 2024-01-08). Rankings are published on Mondays; any date returns the ranking valid that week. Leave empty for the current ranking.
`countryCode` Country (optional)	string	Only players from this country, as a 3-letter code: USA, GBR, ESP, FRA, CZE, POL, CHN…
`maxRank` Top N	integer	How many ranked players to return (e.g. 100 for the top 100). With a country filter, the top N players of that country. 0 means everyone ranked (1,500+). Default: `100`
`proxyConfiguration` Proxy configuration	object	Not required for normal use. Default: `{"useApifyProxy": false}`

API

curl -X POST "https://api.apify.com/v2/acts/hipersoft~wta-rankings-scraper/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
  "rankingTypes": [
    "singles"
  ]
}'

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("hipersoft/wta-rankings-scraper").call(run_input={
    "rankingTypes": [
        "singles"
    ]
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('hipersoft/wta-rankings-scraper').call({
  "rankingTypes": [
    "singles"
  ]
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Pricing

Event	Price	Paid plans from
Ranking row One ranked player row in the dataset.	$0.003	$0.0015

You pay only for what the run returns. Set a maximum cost per run and it stops cleanly at that limit.

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