Flashscore Tennis Scraper: Results, Live Scores, Odds & Stats

From The Mine Works, makers of Threads Scraper and B2B Leads Finder, with over 140,000 runs across 170+ public actors.

Collect tennis matches from Flashscore for ATP, WTA, Challenger, ITF, juniors and team events, singles and doubles, as one row per match: the score and every set with tiebreak points, the winner, the result type, both players with ids, countries, links and current rankings, the tournament and surface, and live game scores with who is serving. Switch on match statistics, point by point, durations and umpire, or bookmaker odds, and they arrive in the same row. It reads the same public data feeds the Flashscore pages load, so there is no browser, no login and no cookie.

Why choose this actor?

• 200 matches in 24 seconds. On 1 Oct 2026 a run with the default settings returned 200 of that day's 385 Flashscore matches, from ATP to ITF, finished, live and scheduled, with each singles player's current ranking, from 4 requests.
• Statistics, point by point and odds in the same row. In our 1 Oct test, all 10 finished ATP and WTA singles matches of the day before came back with 34 statistics columns, every game point by point, set durations and opening and current odds from 20 UK bookmakers. The options are included in the match price.
• From $0.70 per 1,000 matches, plus a flat $0.005 per run. Matches your filters leave out, duplicates, rows past maxMatches, players with no matches and the information row are never charged.

Part of The Mine Works More tools family: Tennis Match & Player Data Scraper, Google Hotels Prices Scraper, LandWatch Scraper.

Try it in one minute

Paste this into the JSON tab of the input page and press Start. It returns 10 of yesterday's ATP and WTA matches in a few seconds.

{
  "mode": "matchesByDay",
  "days": ["yesterday"],
  "tours": ["atp", "wta"],
  "maxMatches": 10
}

There are two ways in. For matches by day, give days as today, yesterday, tomorrow, an offset such as -3 or +2, or a date such as 2026-09-28, anywhere from 7 days back to 7 days ahead (UTC days). For a player's history, set mode to playerResults and give players as Flashscore player links (https://www.flashscore.com/player/djokovic-novak/AZg49Et9/) or just the slug and id (sinner-jannik/6HdC3z4H).

Apify's free plan includes $5 of credit every month, which covers about 4,990 matches at this actor's price.

Copy to your AI assistant

themineworks/flashscore-tennis-results-scraper on Apify. It collects tennis matches from Flashscore (ATP, WTA, Challenger, ITF, juniors, team events; singles and doubles) as one row per match with score, sets, winner, players, rankings, tournament and surface, plus optional statistics, point by point, durations and umpire, and bookmaker odds. Call ApifyClient("TOKEN").actor("themineworks/flashscore-tennis-results-scraper").call(run_input={...}), then client.dataset(run["defaultDatasetId"]).list_items().items. Required: nothing (defaults to today's matches). Optional: mode ("matchesByDay" default or "playerResults"), days (array: "today", "yesterday", "tomorrow", "-3", "+2" or "2026-09-28", within 7 days of today UTC; empty means today), players (array of Flashscore player links or slug/id, for playerResults), maxMatchesPerPlayer (default 40, up to 2000), statuses (finished, live, scheduled, cancelled, postponed, abandoned), tours (atp, wta, challenger, itf, juniors, teams, exhibition, other), matchTypes (singles, doubles), tournaments (name contains), includeRankings (default true), includeStatistics, includePointByPoint, includeSummary, includeOdds (all default false), oddsCountry (default "GB"), oddsMarkets (winner, over_under, handicap, correct_score, odd_even), maxMatches (default 200, up to 50000). Rows with a _type field are information rows, not matches. Full spec: GET https://api.apify.com/v2/acts/themineworks~flashscore-tennis-results-scraper/builds/default (Bearer TOKEN), which returns inputSchema and readme. Token: https://console.apify.com/account/integrations

Key features

• Two modes. Matches by day (7 days back to 7 days ahead: results, live scores and the schedule), or a player's match history, newest first, up to 2,000 matches per player and 100 players per run.
• 22 fields on every match row, including both players as objects with Flashscore id, slug, country, link, image and, for singles, the current ATP or WTA ranking, points and previous rank. Doubles rows carry both players of each pair.
• 4 detail options, each one extra request per match and included in the match price: statistics (34 flat columns for the match plus a list per set), point by point (every game with server, break flag and point scores marked for break, set and match points), durations and umpire, and odds (opening and current, for the bookmakers Flashscore shows in the country you pick, in 5 markets).
• Filters applied before you pay: 6 statuses, 8 tour groups (ATP, WTA, Challenger, ITF, juniors, team events, exhibitions, other), singles or doubles, and tournament names.
• Current rankings for about 3,800 players: 2,290 ATP and 1,553 WTA on 1 Oct 2026, loaded with two requests per run.
• Up to 50,000 matches per run. A day on Flashscore held 385 matches on 1 Oct 2026 and 467 on 30 Sep.

How to use it

Basic: yesterday's results

{
  "days": ["yesterday"],
  "statuses": ["finished"],
  "maxMatches": 500
}

Several days, ATP and WTA singles only

{
  "days": ["-3", "-2", "-1"],
  "tours": ["atp", "wta"],
  "matchTypes": ["singles"],
  "statuses": ["finished"],
  "includeStatistics": true,
  "maxMatches": 300
}

Days are UTC days. A match that starts late in the evening in the Americas can fall on the next UTC day.

A live scoreboard for one tournament

{
  "days": ["today"],
  "statuses": ["live"],
  "tournaments": ["Beijing"]
}

Rows carry current_game_home, current_game_away and serving while a match is live. Schedule it every few minutes during play, for example with the cron */5 * * * *. Each run pays the $0.005 start fee, so a run every 5 minutes for 10 hours is 120 runs, $0.60 in start fees plus the matches.

Tomorrow's schedule with match winner odds

{
  "days": ["tomorrow"],
  "tours": ["atp", "wta"],
  "statuses": ["scheduled"],
  "includeOdds": true,
  "oddsCountry": "GB",
  "oddsMarkets": ["winner"]
}

Odds come from the bookmakers Flashscore shows in the country you pick with oddsCountry. Run it again just before play and compare opening with odds to see how the market moved.

A week of results for a model

{
  "days": ["-7", "-6", "-5", "-4", "-3", "-2", "-1"],
  "statuses": ["finished"],
  "includeStatistics": true,
  "includeSummary": true,
  "maxMatches": 3000
}

Save it as a task and schedule it weekly, for example every Monday at 06:00 UTC with 0 6 * * 1. For older matches than 7 days, use player results.

A player's last 100 matches

{
  "mode": "playerResults",
  "players": ["https://www.flashscore.com/player/djokovic-novak/AZg49Et9/"],
  "maxMatchesPerPlayer": 100
}

Player rows add player_name, player_side, opponent_name and player_won, written from the point of view of the player you asked for. On 1 Oct 2026, 40 matches of Novak Djokovic's history reached back to 27 Aug 2025.

ITF results only

{
  "days": ["today"],
  "tours": ["itf"],
  "statuses": ["finished"]
}

Input parameters

Parameter	Type	Default	What it does
mode	string	matchesByDay	matchesByDay for the matches of chosen days, or playerResults for the match history of chosen players.
days	array of strings	today	For matches by day: today, yesterday, tomorrow, an offset (-3, +2) or a date (2026-09-28). 7 days back to 7 days ahead, UTC days.
players	array of strings	none	For player results: Flashscore player links such as https://www.flashscore.com/player/sinner-jannik/6HdC3z4H/, or the slug and id (sinner-jannik/6HdC3z4H). Up to 100 per run.
maxMatchesPerPlayer	integer, 1 to 2,000	40	Most recent matches per player, newest first. About 40 matches per page.
statuses	array	all	finished, live, scheduled, cancelled, postponed, abandoned.
tours	array	all	atp, wta, challenger, itf, juniors, teams (Davis Cup, BJK Cup, United Cup), exhibition, other.
matchTypes	array	both	singles, doubles. Player results default to singles.
tournaments	array of strings	all	Keep only tournaments whose name contains one of these, such as Beijing or US Open.
includeRankings	boolean	true	Current singles ranking, points and previous rank of each player in singles matches. Two extra requests per run.
includeStatistics	boolean	false	Aces, double faults, first serve percentage, points won on serve and return, break points and more, for the match and each set.
includePointByPoint	boolean	false	Every game with the server, whether serve was broken, and each point score with break, set and match point markers.
includeSummary	boolean	false	Match duration, each set's duration and the chair umpire.
includeOdds	boolean	false	Opening and current odds from the bookmakers Flashscore shows in one country.
oddsCountry	string	GB	Two letter country code whose bookmakers to show, for example GB, DE, US, AU.
oddsMarkets	array	all	winner (match and set winner), over_under, handicap, correct_score, odd_even.
maxMatches	integer, 1 to 50,000	200	Stop after this many matches in the run. The run stops as soon as the cap is met, without reading the remaining days or players, and its summary shows reached_max_matches: true.

The input form in Apify Console starts with yesterday filled in. Runs started through the API or an AI assistant get only what you send, plus the defaults above, so an empty input returns up to 200 of today's matches.

What data do you get?

One row per match. Fields Flashscore has no value for are left out of that row rather than sent as null: a scheduled match has no score, and only live matches carry serving.

The match: record_type (always match), match_id, match_url, start_time, end_time, status (finished, live, scheduled, cancelled, postponed or abandoned), status_detail (such as Set 2 while live), result_type (completed, retired, walkover or cancelled), match_type and note (Flashscore's remark, such as "Played indoor.").

The tournament: tour, category, tournament, tournament_header, tournament_country, surface, qualification, tournament_id and tournament_url.

The players: home_player and away_player as display names, and home and away as objects with name, id, slug, country, country_id, short_code, url and image_url. Singles players also get ranking, ranking_points, previous_ranking and ranking_list. In doubles, each side adds partner_name, partner_id, partner_country, partner_country_id and partner_image_url.

The result: winner (home or away), winner_name, sets_home, sets_away, score (from the home player's side, with the tiebreak loser's points in brackets) and sets, a list with each set's games and tiebreak points. Live matches add current_game_home, current_game_away and serving.

With the options on: statistics (a list of period, group, name and both values, in Flashscore's own text such as 75% (27/36)) and flat stat_..._home and stat_..._away columns for the whole match; point_by_point; duration, duration_minutes, set_durations and umpire; odds_country and odds, a list of bookmaker, market, scope (full time or a set) and selections with current and opening odds.

Player results add player_id, player_name, player_side, opponent_name and player_won.

Run rows: every run that delivers matches ends with one _type: "info" row, and a run that delivers none adds one that says why. They are never charged. Filter on _type to keep only matches.

What we saw in the 200 rows of our 1 Oct 2026 run (today's matches, taken at 09:07 UTC), so you can plan for it:

• 114 matches were scheduled, 63 finished, 20 live and 3 cancelled. score was present on 82 rows and winner on 58; a walkover has a winner but no score.
• 82 rows were ITF, 70 Challenger, 32 ATP and 16 WTA; 40 were doubles.
• umpire is often missing even with includeSummary on: it was present on 1 of our 10 detailed matches. duration was on all 10.
• Statistics and point by point exist only where Flashscore has them. A match without them keeps its row without those fields, and the run summary counts it in details_missing.

Stable fields for automations

These 15 fields were present in every one of the 290 match rows we sampled on 1 Oct 2026 (200 by day, 10 with every option, 80 from player results). Their names will not change, so a Sheet, Zap, Make scenario or n8n flow can map to them safely.

Field	What it is
match_id	Flashscore match id. Use it as the unique key.
match_url	Link to the match on Flashscore
start_time	Scheduled start, ISO 8601 in UTC
status	finished, live, scheduled, cancelled, postponed or abandoned
status_detail	Flashscore's status text, such as Finished or Set 2
match_type	singles or doubles
tour	atp, wta, challenger, itf, juniors, teams, exhibition or other
tournament	Tournament name, such as Beijing (China)
tournament_country	Country of the tournament
surface	Court surface, such as hard or clay
home_player	First listed player or pair, as a display name
away_player	Second listed player or pair
home	First player's object with id, country, link and, for singles, ranking
away	Second player's object
scraped_at	When the row was collected, ISO 8601 in UTC

Output examples

Real rows from our 1 Oct 2026 runs, trimmed where marked. Values are as Flashscore gives them.

A finished ATP match with every option on (local run for 30 Sep; the category and header fields, most statistics columns, all but one game of point by point and all but one of 56 odds lines are trimmed)

{
  "record_type": "match",
  "match_id": "YBGg3Lr2",
  "match_url": "https://www.flashscore.com/match/tennis/YBGg3Lr2/",
  "start_time": "2026-09-30T11:10:00.000Z",
  "end_time": "2026-09-30T13:01:04.000Z",
  "status": "finished",
  "status_detail": "Finished",
  "result_type": "completed",
  "match_type": "singles",
  "tour": "atp",
  "tournament": "Beijing (China)",
  "tournament_country": "China",
  "surface": "hard",
  "qualification": false,
  "home_player": "Borges N.",
  "away_player": "Djokovic N.",
  "home": {
    "name": "Borges N.",
    "id": "hzbEPIOa",
    "country": "Portugal",
    "url": "https://www.flashscore.com/player/borges-nuno/hzbEPIOa/",
    "ranking": 49,
    "ranking_points": 1070,
    "previous_ranking": 48,
    "ranking_list": "ATP"
  },
  "away": {
    "name": "Djokovic N.",
    "id": "AZg49Et9",
    "country": "Serbia",
    "url": "https://www.flashscore.com/player/djokovic-novak/AZg49Et9/",
    "ranking": 11,
    "ranking_points": 2980,
    "previous_ranking": 12,
    "ranking_list": "ATP"
  },
  "winner": "away",
  "winner_name": "Djokovic N.",
  "sets_home": 0,
  "sets_away": 2,
  "score": "3-6 6-7(2)",
  "sets": [
    { "set": 1, "home": 3, "away": 6 },
    { "set": 2, "home": 6, "away": 7, "tiebreak_home": 2, "tiebreak_away": 7 }
  ],
  "statistics": [
    { "period": "Match", "group": "Service", "name": "Aces", "home": "3", "away": "8" }
  ],
  "stat_aces_home": "3",
  "stat_aces_away": "8",
  "stat_first_serve_points_won_home": "75% (27/36)",
  "stat_first_serve_points_won_away": "88% (42/48)",
  "stat_break_points_converted_home": "0/2",
  "stat_break_points_converted_away": "1/2",
  "point_by_point": [
    {
      "set": 1, "game": 2, "games_home": 0, "games_away": 2, "server": "home", "winner": "away", "break": true,
      "points": [{ "score": "0:15" }, { "score": "15:15" }, { "score": "30:15" }, { "score": "30:30" }, { "score": "30:40", "marker": "break_point" }]
    }
  ],
  "duration": "1:52",
  "duration_minutes": 112,
  "set_durations": [{ "set": 1, "duration": "0:43" }, { "set": 2, "duration": "1:09" }],
  "umpire": "Lahyani M.",
  "odds_country": "GB",
  "odds": [
    {
      "bookmaker_id": 625, "bookmaker": "Unibetuk", "market": "HOME_AWAY", "scope": "FULL_TIME",
      "selections": [{ "side": "home", "odds": 3.3, "opening": 2.75 }, { "side": "away", "odds": 1.34, "opening": 1.42 }]
    }
  ],
  "scraped_at": "2026-10-01T13:42:27.469Z"
}

A live match, with the game score and server (platform run, 1 Oct 2026 at 09:07 UTC, trimmed)

{
  "match_id": "0bIo5sEk",
  "start_time": "2026-10-01T07:55:00.000Z",
  "status": "live",
  "status_detail": "Set 2",
  "tour": "atp",
  "tournament": "Beijing (China)",
  "home_player": "Shang J.",
  "away_player": "Baez S.",
  "sets_home": 0,
  "sets_away": 1,
  "score": "5-7 3-2",
  "current_game_home": "30",
  "current_game_away": "30",
  "serving": "home"
}

A doubles match: both players of each pair (platform run, 1 Oct 2026, trimmed)

{
  "match_id": "YeUevI3d",
  "status": "finished",
  "result_type": "completed",
  "match_type": "doubles",
  "tour": "atp",
  "tournament": "Beijing (China)",
  "home_player": "Cash R./Erler A.",
  "away_player": "Luz O./Matos R.",
  "home": { "name": "Cash R.", "id": "8fvnhGme", "country": "USA", "partner_name": "Erler A.", "partner_id": "buoHUFzo", "partner_country": "Austria" },
  "away": { "name": "Luz O.", "id": "nokgCiD2", "country": "Brazil", "partner_name": "Matos R.", "partner_id": "vTTQuqa9", "partner_country": "Brazil" },
  "winner": "home",
  "winner_name": "Cash R./Erler A.",
  "score": "7-6(6) 7-6(10)",
  "sets": [
    { "set": 1, "home": 7, "away": 6, "tiebreak_home": 8, "tiebreak_away": 6 },
    { "set": 2, "home": 7, "away": 6, "tiebreak_home": 12, "tiebreak_away": 10 }
  ]
}

A player results row, seen from the player you asked for (local run, 1 Oct 2026, trimmed)

{
  "match_id": "YBGg3Lr2",
  "start_time": "2026-09-30T11:10:00.000Z",
  "tournament": "Beijing (China)",
  "surface": "hard",
  "home_player": "Borges N.",
  "away_player": "Djokovic N.",
  "score": "3-6 6-7(2)",
  "player_id": "AZg49Et9",
  "player_name": "Djokovic N.",
  "player_side": "away",
  "opponent_name": "Borges N.",
  "player_won": true
}

score stays written from the home player's side in player results too; use player_side to read it from the player's side.

The information row at the end of a run (platform run, 1 Oct 2026, never charged)

{
  "_type": "info",
  "delivered": 200,
  "message": "200 matches delivered. This row is informational: it is never billed.",
  "schedule_tip": "Want this refreshed automatically? Apify Console -> this Actor -> Schedules -> Add schedule -> pick how often (e.g. daily) -> Save. It reruns with the same input on autopilot, no code required.",
  "review_tip": "Found this useful? A quick Store review helps other buyers find it: https://apify.com/themineworks/flashscore-tennis-results-scraper#reviews",
  "scraped_at": "2026-10-01T09:07:32.155Z"
}

Pricing

Pay per event: you are charged for each match saved to your dataset, plus a flat fee once per run. The detail options are included in the match price. The match price drops as your Apify plan goes up.

Event	Free plan	Bronze (Starter)	Silver (Scale)	Gold and above (Business)
match-scraped, per match	$0.001	$0.0009	$0.0008	$0.0007
Per 1,000 matches	$1.00	$0.90	$0.80	$0.70
run-start, per run	$0.005	$0.005	$0.005	$0.005

• Start fee: a flat $0.005 per run, charged once when the run starts, whatever memory you choose. It is our own run-start event, not Apify's per GB start charge, so a bigger memory setting does not raise it.
• Never charged: matches your filters leave out, matches past maxMatches, the same match found twice, empty days, players with no matches, refused pages and the information rows.
• Included at no extra cost: rankings, statistics, point by point, durations, umpire, odds and the datacenter proxies. You pay nothing for platform compute on top of these prices.
• Spending cap: if you set a maximum cost per run in Apify, the actor stops adding matches once that budget is used, so you never receive rows past your cap.
• No price change is scheduled. These prices have applied since 1 Oct 2026. The Pricing tab always shows the rate for your own plan; if this table and the Pricing tab ever disagree, the Pricing tab is right.

Worked examples on the Free plan: the 467 matches Flashscore listed for 30 Sep 2026 would cost $0.467 plus $0.005, so $0.472. On Gold, 1,000 matches cost $0.705 with the start fee.

FAQ

What is Flashscore? Flashscore is a live score and results site run by Livesport. For tennis it lists every match from the ATP and WTA tours down to ITF and junior events, with live scores, statistics and odds.

How many matches can I get? Up to 50,000 per run. A single day held 385 matches on 1 Oct 2026 and 467 on 30 Sep; ATP and WTA together are a small part of that. In player results, up to 2,000 matches per player and 100 players per run.

How do I know whether maxMatches cut my run short? Read the run summary in the key-value record OUTPUT. reached_max_matches is true when the run delivered exactly maxMatches matches and stopped there, and stop_reason then reads "reached maxMatches (N)". Days and players after that point are not read and do not appear in the summary's days or players lists. If reached_max_matches is false, the run delivered everything your days, players and filters allowed: on 1 Oct 2026 a run for today with maxMatches: 2000 delivered all 380 listed matches and reported false.

How far back can I go? Day lists cover 7 days back to 7 days ahead, as on Flashscore. For older matches use player results: 40 matches of Novak Djokovic's history reached back 13 months on 1 Oct 2026.

How fresh are live scores? As fresh as Flashscore's feed at the moment of the request. For a running scoreboard, schedule the actor every few minutes and filter on statuses: ["live"].

Do I need a Flashscore account, cookies or a proxy? No. The actor reads the public data feeds the Flashscore pages load for every visitor, with no login, through Apify datacenter proxies that are included in the price. In our 1 Oct 2026 runs every request was answered on the first attempt (54 of 54).

Why is there no round field? Round names such as quarter-final are not in the lists this actor reads, so there is no round field. qualification tells you whether the match is in qualifying.

Are rankings from the day of the match? No. Rankings are the current singles lists (2,290 ATP and 1,553 WTA players on 1 Oct 2026), not the ranking on the day of an old match. Doubles players get no ranking.

Why do some matches have no statistics? Statistics, point by point and the umpire exist only where Flashscore has them. A match without them keeps its row without those fields, and the run summary in the key-value record OUTPUT counts it in details_missing.

What if Flashscore refuses requests? Each request is tried up to 4 times. If six requests in a row are refused, the run stops and adds an information row saying so; nothing is charged for refused pages, and matches already delivered stay in your dataset. If a feed answers that its access code is out of date, the actor reads a fresh one from www.flashscore.com once and carries on.

Does it follow robots.txt? Yes. Every address is checked against the host's robots.txt, read fresh at the start of each run. The data feeds live on hosts that serve no robots.txt (global.flashscore.ninja answers 404, the odds host 418), which under Google's rules means no restrictions. The actor does not open the /tennis/finished/ or /tennis/live/ pages that www.flashscore.com's robots.txt asks crawlers to skip.

Can I run it on a schedule? Yes. Save your input as a task, then add a schedule in Apify Console under Schedules: daily for results, every few minutes during play for live scores. Each scheduled run is billed like a manual one, including the $0.005 start fee; the schedule itself costs nothing.

Which formats can I export? JSON, CSV, Excel, XML, RSS or HTML from the run's Storage tab, or through the Apify API. For spreadsheets, use the flat stat_..._home and stat_..._away columns; nested lists such as sets and odds are split into numbered columns in CSV and Excel.

Can I use it from Claude, ChatGPT or another AI assistant?

• Connector URL: https://mcp.apify.com/?tools=themineworks/flashscore-tennis-results-scraper.
• Claude: Settings > Connectors > Add custom connector, paste the URL, sign in with Apify.
• ChatGPT: developer mode, add an MCP connector with the URL, sign in with Apify.
• Cursor or VS Code: add it as an HTTP MCP server with that URL.
• Claude Code: claude mcp add -t http flashscore-tennis-results-scraper "https://mcp.apify.com/?tools=themineworks/flashscore-tennis-results-scraper".

Is it legal to scrape Flashscore? The actor collects only public match data and follows robots.txt. You are responsible for following Flashscore's terms of use. Those terms restrict copying and reuse of its content and database without consent, so check that your use fits, and ask Livesport before you republish. This is general information, not legal advice.

Integrations

• Google Sheets: send each run's matches to a sheet with Apify's Google Sheets integration.
• Make, Zapier and n8n: start a run and read the matches with the official Apify modules and nodes, for example to post each day's results to a team chat.
• Webhooks: have Apify call your URL when a run finishes, then fetch the dataset.
• API: start runs and read results over HTTP, or with the Python and JavaScript clients.
• MCP clients: Claude, ChatGPT, Cursor and other MCP clients can call the actor through https://mcp.apify.com.

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• GitHub Trending Scraper

Support

Found a bug or need a field we do not return? Open an issue in the Issues tab. Want another sport or data source? Email dmineworks@gmail.com.

This actor is an independent tool and is not affiliated with, endorsed by or sponsored by Flashscore or Livesport s.r.o. Flashscore is a trademark of its owner.

Flashscore Tennis Scraper turns any day's tennis, or any player's history, into one clean row per match with scores, rankings and optional statistics, point by point and odds, from $0.70 per 1,000 matches.