Tennis Abstract Player Match Scraper & API

Tennis Abstract Player Match Scraper & API

Scrape ATP and WTA match histories from Tennis Abstract by player — full career results with scores, surfaces, rankings, and the serve/return stats (ace rate, dominance ratio, break points saved) that make Tennis Abstract the go-to source for tennis analytics.

Pull a player's entire match log — hundreds to over a thousand matches for long careers — normalized into one schema with rankings, scores, and serve/return stats computed directly from published point counts.

Copy to your AI assistant

Copy this block into ChatGPT, Claude, Cursor, or any LLM to start using this actor.

parsebird/tennis-abstract-match-scraper on Apify. Call: ApifyClient("TOKEN").actor("parsebird/tennis-abstract-match-scraper").call(run_input={...}), then client.dataset(run["defaultDatasetId"]).list_items().items for results. Key inputs: playerSlugs (string array, the p= parameter from a Tennis Abstract player URL, e.g. "NovakDjokovic", "IgaSwiatek"), startUrls (request list of Tennis Abstract player URLs, alternative to playerSlugs), maxItems (integer, default 100, 1-10000), surfaces (array, any of "Hard"/"Clay"/"Grass"/"Carpet", default all), fromDate/toDate (ISO "YYYY-MM-DD", inclusive). Output fields: matchId, playerSlug, playerName, playerUrl, date, tournament, tournamentUrl, surface, round, playerRank, opponent, opponentSlug, opponentUrl, opponentRank, opponentCountry, outcome ("win"/"loss"), score, dominanceRatio, aceRate, doubleFaultRate, firstServeIn, firstServeWon, secondServeWon, breakPointsSaved, duration, sourceUrl, scrapedAt. Full actor spec: fetch build via GET https://api.apify.com/v2/acts/parsebird~tennis-abstract-match-scraper (Bearer TOKEN). Get token: https://console.apify.com/account/integrations

What does Tennis Abstract Player Match Scraper do?

This Actor scrapes tennisabstract.com, the tennis analytics site run by Jeff Sackmann, pulling a player's full ATP or WTA match history and normalizing it into one consistent schema — regardless of which internal data source Tennis Abstract happens to serve it from.

• 🎾 Full career coverage — hundreds to 1,500+ matches for long careers, not just recent results
• 📊 Real serve/return stats — ace rate, double fault rate, first/second serve won, and dominance ratio, computed directly from the published point counts (not scraped from a rendered percentage that can round differently)
• 🏆 Match context — tournament, surface, round, both players' rankings at the time, score (including RET/W-O markers), and match duration
• 🔀 ATP and WTA in one actor — works identically for men's and women's players from a single input
• 🎯 Filter by surface and date — narrow to a specific era or surface (e.g. clay-court results since 2024) without post-processing
• ⏱️ Scheduling — run this Actor weekly via Apify Scheduler to keep a player's match log current as new results are published
• 🔌 API access — trigger runs and pull results programmatically via the Apify API or client libraries
• 📊 Flexible export — download results as JSON, CSV, or Excel, or query them via API

What data can you extract?

Field	Description
date / tournament / surface / round	Match context
playerRank / opponentRank	Rankings at the time of the tournament
opponent / opponentSlug / opponentUrl / opponentCountry	Opponent identity
outcome / score	"win"/"loss" and the published score, including RET/W/O markers
dominanceRatio	Return points won % ÷ serve points lost % — Tennis Abstract's headline stat for match control
aceRate / doubleFaultRate / firstServeIn / firstServeWon / secondServeWon	Serve stats, each expressed 0–1
breakPointsSaved	"saved/faced" text, e.g. "10/13"
duration	Match length, e.g. "2:20"
sourceUrl	The exact Tennis Abstract data source used for that player

Detailed serve/return stats are only published for matches Tennis Abstract charted in depth — when they're not available, those fields are null while match context (date, score, opponent, outcome) is still returned.

Input parameters

Parameter	Type	Default	Description
playerSlugs	string array	none	Player identifiers from the page p= parameter, e.g. NovakDjokovic
startUrls	request list	none	Public Tennis Abstract player or classic-player URLs
maxItems	integer	100	Global row limit from 1 to 10,000
surfaces	string array	all	Any of Hard, Clay, Grass, or Carpet
fromDate	string	none	Inclusive earliest match date, YYYY-MM-DD
toDate	string	none	Inclusive latest match date, YYYY-MM-DD
proxyConfiguration	object	direct	Optional Apify or custom proxy settings

Output example

{
  "matchId": "8b315f1b0539ee246e6b5aaca9d70c9bc5ec9acd",
  "playerSlug": "NovakDjokovic",
  "playerName": "Novak Djokovic",
  "playerUrl": "https://www.tennisabstract.com/cgi-bin/player.cgi?p=NovakDjokovic",
  "date": "2026-06-29",
  "tournament": "Wimbledon",
  "tournamentUrl": "https://www.tennisabstract.com/cgi-bin/tourney.cgi?t=2026-540/Wimbledon",
  "surface": "Grass",
  "round": "SF",
  "playerRank": 8,
  "opponent": "Jannik Sinner",
  "opponentSlug": "JannikSinner",
  "opponentUrl": "https://www.tennisabstract.com/cgi-bin/player.cgi?p=JannikSinner",
  "opponentRank": 1,
  "opponentCountry": "ITA",
  "outcome": "loss",
  "score": "6-4 6-4 6-4",
  "dominanceRatio": 0.551,
  "aceRate": 0.076,
  "doubleFaultRate": 0.029,
  "firstServeIn": 0.638,
  "firstServeWon": 0.761,
  "secondServeWon": 0.342,
  "breakPointsSaved": "10/13",
  "duration": "2:20",
  "sourceUrl": "https://www.tennisabstract.com/cgi-bin/player-classic.cgi?p=NovakDjokovic",
  "scrapedAt": "2026-07-28T06:00:00.000Z"
}

Download results in JSON, CSV, or Excel directly from the Apify Console, or pull them programmatically via the API.

Use cases

• Tennis analytics and modeling — build match-outcome or serve-performance models from real point-count-derived stats
• Scouting and opponent prep — pull a player's full surface-specific record before a matchup
• Content and media — power head-to-head graphics, career trend charts, or surface breakdowns
• Betting research — analyze dominance ratio and serve trends across surfaces and date ranges
• Historical research — full career logs for long-retired and active players alike

How it works

1. Go to the Tennis Abstract Player Match Scraper page on Apify Store
2. Click Try for free — new users get a free trial to test the Actor before paying
3. Enter one or more player slugs (e.g. NovakDjokovic, IgaSwiatek) or paste player URLs into startUrls
4. Optionally filter by surface and date range, and set maxItems to cap the total rows
5. Click Start — the Actor fetches the player's full match log and normalizes every row
6. When the run finishes, download your data as JSON, CSV, or Excel, or fetch it via the API

Use with the Apify API

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("parsebird/tennis-abstract-match-scraper").call(run_input={
    "playerSlugs": ["IgaSwiatek", "ArynaSabalenka"],
    "surfaces": ["Clay"],
    "fromDate": "2024-01-01",
    "maxItems": 200,
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['date']} {item['tournament']} {item['round']} - {item['playerName']} vs {item['opponent']}: {item['outcome']} {item['score']}")

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('parsebird/tennis-abstract-match-scraper').call({
    playerSlugs: ['IgaSwiatek', 'ArynaSabalenka'],
    surfaces: ['Clay'],
    fromDate: '2024-01-01',
    maxItems: 200,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.log(`${item.date} ${item.tournament} ${item.round} - ${item.playerName} vs ${item.opponent}: ${item.outcome} ${item.score}`);
});

See the Apify API documentation for full reference, or the Actor's API tab for ready-to-run request snippets in more languages.

How much does it cost to run?

This Actor uses Pay-per-event pricing — you only pay for match rows actually returned, with no separate platform rental fee.

Plan	Price per event	Price per 1,000
Free	$0.00699	$6.99
Bronze	$0.00599	$5.99
Silver	$0.00599	$5.99
Gold	$0.00499	$4.99

One match-scraped event is charged for each match row successfully normalized and pushed to the dataset. A full career pull for a long-tenured player (~1,000 matches) costs about $7.00 on the Free plan or $5.00 on Gold. Start with a low maxItems on the free trial to preview a player's data before pulling their full history.

FAQ

How do I scrape a player's full match history, not just recent results? Leave maxItems at a high value (up to 10,000) and don't set fromDate — the Actor pulls the player's complete logged match history by default, not just their most recent matches.

Does this work for both men's and women's players? Yes, from the same input. Tennis Abstract serves ATP and WTA data through different internal endpoints with different quirks; this Actor detects which one a given player needs and normalizes the result identically either way.

Why is tournamentUrl sometimes null? Tennis Abstract's tournament-link format is only reliably reconstructable from the data source used for most men's matches. Rather than guess and risk a broken link, tournamentUrl is left null when we can't construct it with confidence — every other match field is unaffected.

Why are some serve/return stats null? Tennis Abstract only publishes detailed serve/return stats for matches it charted in depth. Every match includes date, score, opponent, and outcome regardless; the rate stats populate when the source has them.

Can I filter by surface or date range? Yes. Set surfaces to any of Hard, Clay, Grass, Carpet, and/or fromDate/toDate to restrict to a specific era.

Can I schedule recurring runs? Yes. Use Apify's Scheduler to run this Actor weekly and pick up new matches as a player's season progresses.

Is it legal to scrape Tennis Abstract? Tennis Abstract publishes match data for public viewing without a login or paywall. You're responsible for complying with the site's terms of use for your specific use case. See Apify's blog post on the legality of web scraping for general background.

Can I access results via API? Yes. Every run's dataset is available through the Apify API and client libraries (Python, JavaScript) — see the Actor's API tab for ready-made snippets.

Something not working? Open an issue on the Actor's Issues tab in Apify Console — the ParseBird team monitors it directly.

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