Flashscore Tennis Scraper - Live Scores, Results & H2H

Scrape tennis matches from Flashscore (flashscore.com): fixtures, live scores and results for ATP, WTA, Challenger and ITF, singles and doubles. Each match comes out with its sets and tiebreaks, players and rankings, tournament and surface, plus optional match stats and head-to-head, ready to export as JSON, CSV or Excel or to call as an API. Pick the days and press Start.

Target website: flashscore.com

✨ Features of this Flashscore tennis scraper

• Tennis match extraction — fixtures, live matches and finished results with the score of every set, tiebreak points, winner, start and end time.
• Players and rankings — both sides with name, country, current ranking, photo and Flashscore profile id, for singles and doubles.
• Tournament data — tournament name, country, category (ATP, WTA, Challenger, ITF) and surface (hard, clay, grass, carpet).
• Live score details — for live matches the current set, the server and the points of the current game.
• Match stats on demand — set durations, match duration, referee and the full statistics (aces, double faults, serve and return points, break points, winners, errors).
• Head-to-head on demand — the previous meetings of the two players and the last matches of each.
• Point-by-point on demand — every game of every set with the server, the winner, whether the serve was broken, the points of the game with break, set and match points flagged, and the tiebreak points in order.
• Filters — by tour, match status, singles or doubles, tournament name, or a tournament page URL.
• Proxy support — optional; runs work without one.
• No browser required — plain requests keep runs fast and cheap.

🚀 How to scrape Flashscore tennis matches in 5 steps

1. Sign up for a free Apify account — includes $5 monthly credit.
2. Open the actor page and click Try for free.
3. Fill in the Input fields (the default tennis page works as is; choose the days and filters you want).
4. Click Start and wait for the run to complete.
5. Download results from the Output tab in JSON, CSV, or Excel format.

You can also run this actor via the Apify API or integrate it directly into your workflows using Zapier, Make, or n8n.

💰 Pricing for the Flashscore tennis scraper

This actor uses pay-per-result billing based on the compute units a run consumes.

• New Apify accounts include $5 of free monthly credit.
• The actor uses plain HTTP requests instead of a browser, so it costs significantly less to run than browser-based scrapers.
• The proxy is off by default, which keeps runs cheapest.

🖼️ Flashscore tennis scraper input screenshot

The numbers match the input fields below:

1. Flashscore tennis URLs: the tennis page, a tournament page or a match page.
2. Max matches per URL: the match limit for each start URL.
3. Days back: also scrape matches from this many days before today.
4. Days ahead: also scrape fixtures from this many days after today.
5. Tours: ATP, WTA, Challenger, ITF or Other.
6. Match status: scheduled, live or finished matches.
7. Scrape match details: add match stats and more detail to each row.
8. Include head-to-head: add the players' previous meetings.

🔧 Flashscore tennis scraper input configuration

The input form starts with the Flashscore URLs and the match limit, then the days and filters, and the two detail switches. The proxy settings are last.

Field	Type	Required	Default	Description
Flashscore tennis URLs (startUrls)	array	—	the Flashscore tennis page	The tennis page for all matches, a tour or tournament page to keep only its matches, or a match page with ?mid= for one match.
Max matches per URL (maxItems)	integer	—	5	Maximum matches saved for each start URL.
Days back (daysBack)	integer	—	0	Also scrape the matches of this many days before today (0 to 7).
Days ahead (daysAhead)	integer	—	0	Also scrape the fixtures of this many days after today (0 to 7).
Tours (tours)	array	—	all	atp, wta, challenger, itf or other.
Match status (matchStatuses)	array	—	all	scheduled, live or finished (finished includes retired and walkover).
Singles or doubles (matchType)	string	—	all	all, singles or doubles.
Tournament names (tournaments)	array	—	—	Keep only tournaments whose name contains one of these words, for example Paris or Roland Garros.
Scrape match details (scrapeDetails)	boolean	—	false	Adds set and match durations, the referee and the match statistics for matches that have started.
Include head-to-head (includeHeadToHead)	boolean	—	false	Adds the previous meetings of the two players and the last matches of each.
Include point-by-point (includePointByPoint)	boolean	—	false	Adds every game of every set with server, winner, break flag, the points of the game (0:15, 30:40...) and the tiebreak points, for matches that have started.
Proxy configuration (proxyConfiguration)	object	—	no proxy	Turn on Apify Proxy if your runs get blocked.

Supported URL types:

• All tennis: https://www.flashscore.com/tennis/
• A tour: https://www.flashscore.com/tennis/atp-singles/
• A tournament: https://www.flashscore.com/tennis/atp-singles/paris/
• One match: https://www.flashscore.com/match/tennis/<player>/<player>/?mid=<match id>

📦 Flashscore tennis scraper output data

Every match is one flat record in the dataset with the keys matchId, url, startTime, endTime, status, matchType, tour, winner, note, setsHome, setsAway, sets, homeName, homeId, homeSlug, homeCountry, homeRanking, homePhoto, awayName, awayId, awaySlug, awayCountry, awayRanking, awayPhoto, tournamentId, tournamentName, tournamentUrl, tournamentCountry, category, surface, liveSet, currentServer, currentGameHome, currentGameAway, totalDurationMinutes, referee, stats, headToHead, pointByPoint, source and scrapedAt. Every record has all keys; a value the source does not carry is null. The dataset has 1 view:

• Matches — a compact table of start time, status, tour, tournament, both players, sets won, winner, surface and the match link.

Output at a glance:

Start (UTC)	Status	Tournament	Match	Sets	Score
2026-10-28 20:20	finished	Basel (hard)	Hurkacz H. v Rune H.	1-2	6-3 3-6 6-7
2026-10-29 11:10	finished	Basel (hard)	Vacherot V. v Jodar R.	2-1	7-6 2-6 7-6
2026-10-29 14:00	finished	Basel (hard)	Michelsen A. v Fils A.	1-2	6-4 3-6 6-7
2026-10-29 16:15	live	Basel (hard)	Altmaier D. v Lehecka J.	0-1	5-7 1-0
2026-10-29 18:05	scheduled	Basel (hard)	Djokovic N. v Struff J-L.	—	—

Sample output (raw JSON):

[
  {
    "matchId": "lljX5Uwp",
    "url": "https://www.flashscore.com/match/tennis/hurkacz-hubert-jPfeGTme/rune-holger-rXC2E7I7/?mid=lljX5Uwp",
    "startTime": "2026-10-28T20:20:00.000Z",
    "endTime": "2026-10-28T22:16:52.000Z",
    "status": "finished",
    "matchType": "singles",
    "tour": "atp",
    "winner": "away",
    "note": null,
    "setsHome": 1,
    "setsAway": 2,
    "sets": [
      {
        "set": 1,
        "homeGames": 6,
        "awayGames": 3,
        "homeTiebreak": null,
        "awayTiebreak": null,
        "durationMinutes": 34
      },
      {
        "set": 2,
        "homeGames": 3,
        "awayGames": 6,
        "homeTiebreak": null,
        "awayTiebreak": null,
        "durationMinutes": 29
      },
      {
        "set": 3,
        "homeGames": 6,
        "awayGames": 7,
        "homeTiebreak": 7,
        "awayTiebreak": 9,
        "durationMinutes": 57
      }
    ],
    "homeName": "Hurkacz H.",
    "homeId": "jPfeGTme",
    "homeSlug": "hurkacz-hubert",
    "homeCountry": "Poland",
    "homeRanking": 154,
    "homePhoto": "https://static.flashscore.com/res/image/data/fg7OyO7k-xEfD5uDB.png",
    "awayName": "Rune H.",
    "awayId": "rXC2E7I7",
    "awaySlug": "rune-holger",
    "awayCountry": "Denmark",
    "awayRanking": 63,
    "awayPhoto": "https://static.flashscore.com/res/image/data/MamwNzme-tSf4B4RM.png",
    "tournamentId": "t8icmqob",
    "tournamentName": "Basel",
    "tournamentUrl": "https://www.flashscore.com/tennis/atp-singles/basel/",
    "tournamentCountry": "Switzerland",
    "category": "ATP - Singles",
    "surface": "hard",
    "liveSet": null,
    "currentServer": null,
    "currentGameHome": null,
    "currentGameAway": null,
    "totalDurationMinutes": 120,
    "referee": "Absolu M.",
    "stats": [
      {
        "period": "Match",
        "group": "Service",
        "name": "Aces",
        "home": "18",
        "away": "5"
      },
      {
        "period": "Match",
        "group": "Service",
        "name": "Double Faults",
        "home": "2",
        "away": "4"
      },
      {
        "period": "Match",
        "group": "Service",
        "name": "1st serve percentage",
        "home": "78%",
        "away": "60%"
      }
    ],
    "headToHead": {
      "homeLastMatches": [
        {
          "matchId": "lljX5Uwp",
          "date": "2026-10-28T20:20:00.000Z",
          "tournament": "Basel",
          "surface": "hard",
          "home": "Hurkacz H.",
          "away": "Rune H.",
          "score": "1:2",
          "winner": "away"
        }
      ],
      "awayLastMatches": [
        {
          "matchId": "lljX5Uwp",
          "date": "2026-10-28T20:20:00.000Z",
          "tournament": "Basel",
          "surface": "hard",
          "home": "Hurkacz H.",
          "away": "Rune H.",
          "score": "1:2",
          "winner": "away"
        }
      ],
      "headToHead": [
        {
          "matchId": "lljX5Uwp",
          "date": "2026-10-28T20:20:00.000Z",
          "tournament": "Basel",
          "surface": "hard",
          "home": "Hurkacz H.",
          "away": "Rune H.",
          "score": "1:2",
          "winner": "away"
        }
      ]
    },
    "pointByPoint": [
      {
        "set": 1,
        "homeGames": 6,
        "awayGames": 3,
        "winner": "home",
        "games": [
          {
            "game": 1,
            "homeGames": 1,
            "awayGames": 0,
            "server": "home",
            "winner": "home",
            "brokeServe": false,
            "points": [
              {
                "score": "0:15",
                "markers": []
              },
              {
                "score": "15:15",
                "markers": []
              }
            ]
          },
          {
            "game": 2,
            "homeGames": 1,
            "awayGames": 1,
            "server": "away",
            "winner": "away",
            "brokeServe": false,
            "points": [
              {
                "score": "0:15",
                "markers": []
              },
              {
                "score": "15:15",
                "markers": []
              }
            ]
          }
        ],
        "tiebreak": null
      },
      {
        "set": 2,
        "homeGames": 3,
        "awayGames": 6,
        "winner": "away",
        "games": [
          {
            "game": 1,
            "homeGames": 0,
            "awayGames": 1,
            "server": "away",
            "winner": "away",
            "brokeServe": false,
            "points": [
              {
                "score": "15:0",
                "markers": []
              },
              {
                "score": "15:15",
                "markers": []
              }
            ]
          },
          {
            "game": 2,
            "homeGames": 1,
            "awayGames": 1,
            "server": "home",
            "winner": "home",
            "brokeServe": false,
            "points": [
              {
                "score": "15:0",
                "markers": []
              },
              {
                "score": "30:0",
                "markers": []
              }
            ]
          }
        ],
        "tiebreak": null
      }
    ],
    "source": "https://www.flashscore.com/tennis/",
    "scrapedAt": "2026-10-29T17:29:57.966Z"
  }
]

🔁 Scrape Flashscore tennis results and fixtures on a schedule

Use Apify Schedules to run the scraper every day: set Days back to 1 to collect yesterday's finished matches, or Days ahead to 1 to collect the next day's fixtures. Matches that were saved in an earlier run are saved again, so remove duplicates by matchId when you merge runs.

🐍 How to scrape Flashscore tennis with Python, JavaScript or the API

Run the actor programmatically with the official Apify clients. Replace <YOUR_API_TOKEN> with the token from your Apify Console.

Python (pip install apify-client):

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")

run = client.actor("confidential_gnat/flashscore-tennis-scraper").call(run_input={
    "startUrls": [{"url": "https://www.flashscore.com/tennis/"}],
    "maxItems": 50,
    "daysBack": 1,
    "tours": ["atp", "wta"],
    "matchStatuses": ["finished"],
    "scrapeDetails": True,
})

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

JavaScript (npm install apify-client):

import { ApifyClient } from 'apify-client';

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

const run = await client.actor('confidential_gnat/flashscore-tennis-scraper').call({
    startUrls: [{ url: 'https://www.flashscore.com/tennis/' }],
    maxItems: 50,
    daysBack: 1,
    tours: ['atp', 'wta'],
    matchStatuses: ['finished'],
    scrapeDetails: true,
});

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

cURL — start a run and wait for the dataset:

curl -X POST "https://api.apify.com/v2/acts/confidential_gnat~flashscore-tennis-scraper/run-sync-get-dataset-items?token=<YOUR_API_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"startUrls": [{"url": "https://www.flashscore.com/tennis/"}], "maxItems": 50, "daysBack": 1, "tours": ["atp", "wta"], "matchStatuses": ["finished"], "scrapeDetails": true}'

💡 What you can use Flashscore tennis data for

• Building tennis results and fixtures databases for rankings, Elo ratings and form models.
• Training and backtesting match prediction models on sets, tiebreaks, surface and head-to-head.
• Powering live score widgets, Discord or Telegram bots and fantasy tennis tools.
• Tracking player form by surface, tournament and ranking over time.
• Feeding sports media, newsletters and betting research with the day's matches and stats.

The data is typically used by sports analysts, data scientists, betting researchers, fantasy platforms and sports publishers.

⚠️ Limitations of the Flashscore tennis scraper

• Seven days either side — Flashscore lists about a week back and a week ahead, so older results are not available.
• No round and no odds — the round of the tournament and betting odds are not part of the output.
• Details start with the match — statistics and set durations exist only for live and finished matches, not for scheduled ones.
• Point-by-point is game level — it lists the points of each game as scores (the point that won the game is not listed) and does not carry shot types, aces or timestamps. Some old or minor matches have no point-by-point.
• Doubles pairs — a doubles side is one record with both player names joined, for example Estevez J./Ratti L..

❓ Flashscore tennis scraper FAQ

Can I scrape Flashscore legally?

The actor only collects match data that is already publicly visible on Flashscore, with no login, paywall or private content. Scraping publicly available data is generally considered lawful (see hiQ Labs v. LinkedIn), but you are responsible for complying with Flashscore's Terms of Service and applicable laws.

What data does the Flashscore tennis scraper return?

Each match has its status, start and end time, sets and tiebreaks, winner, both players with country and ranking, the tournament with its category and surface, and for live matches the current set, server and game score. With Scrape match details you also get set durations, the referee and match statistics, with Include head-to-head the previous meetings and recent matches of the players, and with Include point-by-point every game of every set.

How many matches can I scrape from one Flashscore URL?

Max matches per URL limits the saved matches for each start URL, counted across all the days you selected. A normal day lists several hundred tennis matches including ITF events, so use the tour, status and tournament filters to narrow it down.

Do I need a proxy to scrape flashscore.com?

No. The input defaults to no proxy and runs worked without one in testing. Turn on Apify Proxy only if your runs start getting blocked.

How do I scrape Flashscore tennis with Python?

Use the Python example above: it starts the actor with your input and iterates over the dataset items.

Can I run this Flashscore tennis scraper on a schedule?

Yes. Create an Apify Schedule for the actor and set Days back to 1 to receive the previous day's results on every run.

What output formats are supported?

JSON, CSV, Excel, XML and RSS, either from the Output tab or through the Apify API.

Why are some stats and durations empty?

Statistics, set durations and the referee only exist once a match has started, so scheduled matches return null for them. Some lower-level ITF matches also have no statistics on Flashscore.

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💬 Support & contact

If you encounter any issues or have questions, please open an issue.

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