WTA Singles, Doubles & Race Rankings Finder
Get the official WTA singles, doubles, or Race to the Finals rankings with points, nationality, and player profile links, filterable by player name.
Open in Apify Store$0.99 / 1K on Free
Short answer
WTA Singles, Doubles & Race Rankings Finder is an Apify Store Actor that returns 9 published output fields, including playerName, nationality, ranking, points. It lists $0.99 per 1,000 results on the Free plan (pay per event), $0.49 on the Business plan. It takes 14 input settings; one is required (mode). Last updated Nov 11, 2026.
From the public Store listing and published build schema, synced 2026-11-12.What it returns
9 fields from the published dataset schema. Export as JSON, CSV or Excel, or read the dataset through the Apify API.
playerNamenationalityrankingpointsmovementtournamentNameroundresultprofileUrl
Input
| Setting | Type | Required | Default | What it does |
|---|---|---|---|---|
| mode | string | Yes | rankings | Choose rankings, player profiles, match history, or the tournament calendar. |
| rankingType | string | No | singles | Singles, doubles, Race to the WTA Finals singles, or Race to the WTA Finals doubles. Also used to resolve names in profiles and matches modes. |
| rankingDate | string | No | – | Historical rankings as of a Monday from 2001 onward. Leave empty for the latest published rankings. |
| searchQuery | string | No | – | Filter rankings by name, or resolve players for profiles and matches modes. |
| nationality | string | No | – | Three-letter country code such as USA, POL, or KAZ. |
| playerIds | array | No | – | Profiles and matches modes. Paste WTA player IDs or profile URLs, one per line or comma-separated. |
| year | integer | No | – | Matches mode only. Limit match history to one season, for example 2026. |
| fromDate | string | No | – | Tournaments mode. Start of the calendar window; leave empty for the last 7 days. |
| toDate | string | No | – | Tournaments mode. End of the calendar window; leave empty for the next 14 days. |
| level | string | No | all | Tournaments mode. Filter by WTA tournament tier. |
Show the other 4 settings
| Setting | Type | Required | Default | What it does |
|---|---|---|---|---|
| surface | string | No | all | Tournaments mode. Filter by court surface. |
| includeTournamentMatches | boolean | No | false | Tournaments mode. Add the match list for every returned tournament. |
| includeRankingHistory | boolean | No | false | Player profiles mode. Add up to 52 weeks of singles, doubles and Race ranking history. |
| maxItems | integer | No | 50 | Stop after this many records. Each ranking table has at most about 1,800 players. |
Example input
Built from the input form's published example values and defaults.
{
"mode": "rankings",
"rankingType": "singles",
"level": "all",
"surface": "all",
"includeTournamentMatches": false,
"includeRankingHistory": false,
"maxItems": 3
} Run it from code or an AI agent
The same run through the Apify API, with the example input. You need an Apify API token; the run is billed to your account at the Store price.
Python
from apify_client import ApifyClient
client = ApifyClient("<YOUR_APIFY_TOKEN>")
run_input = {
"mode": "rankings",
"rankingType": "singles",
"level": "all",
"surface": "all",
"includeTournamentMatches": False,
"includeRankingHistory": False,
"maxItems": 3
}
run = client.actor("dataspryva/wta-singles-doubles-and-race-rankings-finder").call(run_input=run_input)
if run is None:
raise RuntimeError("The Actor run was not found.")
for item in client.dataset(run.default_dataset_id).iterate_items():
print(item) pip install apify-client
JavaScript
import { ApifyClient } from "apify-client";
const client = new ApifyClient({ token: "<YOUR_APIFY_TOKEN>" });
const input = {
"mode": "rankings",
"rankingType": "singles",
"level": "all",
"surface": "all",
"includeTournamentMatches": false,
"includeRankingHistory": false,
"maxItems": 3
};
const run = await client.actor("dataspryva/wta-singles-doubles-and-race-rankings-finder").call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items); npm install apify-client
cURL
curl -X POST "https://api.apify.com/v2/actors/dataspryva~wta-singles-doubles-and-race-rankings-finder/run-sync-get-dataset-items" -H "Authorization: Bearer $APIFY_TOKEN" -H "Content-Type: application/json" -d '{"mode":"rankings","rankingType":"singles","level":"all","surface":"all","includeTournamentMatches":false,"includeRankingHistory":false,"maxItems":3}' Waits for the run and returns the dataset items (runs over 300 seconds return HTTP 408; start an async run instead).
MCP (AI agents)
{
"mcpServers": {
"apify": {
"url": "https://mcp.apify.com?tools=dataspryva/wta-singles-doubles-and-race-rankings-finder",
"headers": {
"Authorization": "Bearer <YOUR_APIFY_TOKEN>"
}
}
}
} Adds this Actor as a tool in an MCP client that takes a remote server URL (Cursor, VS Code, Claude Code) through Apify's hosted MCP server. OAuth sign-in also works without the header. Clients that only start local servers can wrap the URL with npx mcp-remote.
What a run costs
The result rate falls on higher Apify plans. Each figure is the published per-result rate times the number of results.
| Apify plan | Per 1,000 | 10,000 results | 100,000 results |
|---|---|---|---|
| Free plan | $0.99 | $9.90 | $99 |
| Starter plan | $0.82 | $8.20 | $82 |
| Scale plan | $0.66 | $6.60 | $66 |
| Business plan | $0.49 | $4.90 | $49 |
- Every run also has a start event, charged per GB of memory (minimum one): $0.10 on Free, $0.03 on Business. At its default memory of 4 GB a run starts at $0.40 on Free. Fewer, larger runs keep this small.
- The Free plan includes $5 of monthly usage (Apify pricing, checked 2026-11-11); at the Free rate that covers at most about 5,050 results, less start events and platform usage.
- Worked example: 10,000 results in one run on the Free plan cost $10.30 ($9.90 for results + $0.40 start), plus Apify platform usage (compute), billed separately by Apify.
- Pay per event. Platform usage (compute) is billed by Apify on top of the event prices. Compare other tools in the cost estimator.
What people use it for
- review player rankings
- look up match results
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Questions people ask
How much does WTA Singles, Doubles & Race Rankings Finder cost?
The published result rate depends on your Apify plan: $0.99 per 1,000 on Free, $0.82 per 1,000 on Starter, $0.66 per 1,000 on Scale, $0.49 per 1,000 on Business. So 10,000 results cost about $9.90 on the Free plan and $4.90 on Business, plus a start fee of $0.10 per run per GB of memory on Free. Platform usage is billed separately.
What data does WTA Singles, Doubles & Race Rankings Finder return?
Its published output schema lists 9 fields: playerName, nationality, ranking, points, movement, tournamentName, round, result, profileUrl. A listed field is not guaranteed to be filled in every row.
What input does WTA Singles, Doubles & Race Rankings Finder need?
Required: mode. Optional settings include rankingType, rankingDate, searchQuery, nationality, playerIds, year.
How do I run WTA Singles, Doubles & Race Rankings Finder from Python or the API?
Use the Apify API client: in Python, ApifyClient(token).actor("dataspryva/wta-singles-doubles-and-race-rankings-finder").call(run_input=...), then read the run's default dataset (run.default_dataset_id); in JavaScript the same call is client.actor("dataspryva/wta-singles-doubles-and-race-rankings-finder").call(input). Without a client, POST the input JSON to https://api.apify.com/v2/actors/dataspryva~wta-singles-doubles-and-race-rankings-finder/run-sync-get-dataset-items with your API token. Ready-to-paste code with the example input is on this page.
Sources
- WTA Singles, Doubles & Race Rankings Finder on Apify Store
- Published build with input and output schema (JSON)
Cite this page
Scraper Finder. "WTA Singles, Doubles & Race Rankings Finder." https://scraperfinder.com/catalogue/wta-singles-doubles-and-race-rankings-finder/ (data checked 2026-11-12).
Run WTA Singles, Doubles & Race Rankings Finder
$0.99 per 1,000 results. Paste the example input above, set your target query, then export the dataset.