# Tennis Player Match History: Results, H2H, Stats & Odds (`keelwright/tennis-player-history`) Actor Full match history of any tennis player from Flashscore: every result with tournament, surface, round, opponent and score, plus head-to-head, match statistics and opening and closing bookmaker odds. ATP, WTA, Challenger and ITF. - **URL**: https://apify.com/keelwright/tennis-player-history.md - **Developed by:** [Keelwright](https://apify.com/keelwright) (community) - **Categories:** Sports, Developer tools - **Security:** Limited permissions - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $6.00 / 1,000 matches This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## Tennis Player Match History: results, head-to-head, stats and odds Get the complete match history of any tennis player from Flashscore as clean JSON, CSV or Excel: every match with **date, tournament, surface, round, opponent, score, sets and games**, seen from the player's side. Covers **ATP, WTA, Challenger and ITF**, singles, doubles and mixed, with tour-level results back to the late 1990s. Add **head-to-head filters, match statistics and opening and closing bookmaker odds** when you need them. - **A whole career in under a minute.** Roger Federer's 1,570 singles matches (1998 to 2021) come back in about 50 seconds, each with its round. - **Head-to-head in one run.** Put one player in **Players** and another in **Opponents** to get every meeting, such as all 60 Djokovic vs Nadal matches (31-29, as in the official record). - **Titles and win-loss records for free.** A player summary counts titles, finals, wins and losses by surface, year and tour. Federer's comes out at 103 titles from 157 finals, the same as the official record. - **Rounds you can sort by.** R128 to the final, Q1 to Q3 in qualifying and RR for group stages, next to Flashscore's own round name. - **Statistics and odds on request.** Over 20 statistics for the match and each set (aces, double faults, serve and return points, break points, winners, unforced errors, distance covered), match and set durations, and opening and closing odds from up to 20 bookmakers per country. - **Only new matches.** Run it on a schedule and get each player's new results only. ### What can I use tennis match history for? - **Betting models and backtesting**: results with opening and closing odds, the favourite and implied probabilities, to test strategies and closing line value. - **Player analysis and scouting**: form, surface splits, records against one opponent, serve and return statistics over a season or a whole career. - **Elo and rating systems**: a clean, ordered list of results with walkovers and retirements flagged. - **Fantasy, tipping and prediction games**: recent form and head-to-head for any matchup. - **Journalism, content and research**: career milestones, title counts and season records for articles, social posts and academic work. ### How to get a tennis player's match history 1. Click **Try for free**. 2. Type the **Players**: names such as `Carlos Alcaraz` or `Swiatek`, or Flashscore player URLs. 3. Optionally pick **singles, doubles or mixed**, a **date range** (`2024-01-01`, or a period such as `12 months`), **opponents** for head-to-head, **surfaces**, **tours** or **main draw only**. 4. Tick **Match statistics and duration** and **Bookmaker odds** if you want them. 5. Click **Start** and download the results as JSON, CSV, Excel or HTML, or read them through the API. Two players with the same name? The log names the other players it found. Paste the Flashscore URL of the one you mean. ### Input examples The last 20 matches of two players: ```json { "players": ["Carlos Alcaraz", "Aryna Sabalenka"], "maxMatchesPerPlayer": 20 } ``` A head-to-head on the ATP tour, main draw only, with statistics and odds: ```json { "players": ["Novak Djokovic"], "opponents": ["Rafael Nadal"], "tours": ["atp"], "mainDrawOnly": true, "includeStatistics": true, "includeOdds": true } ``` One season on one surface: ```json { "players": ["Iga Swiatek"], "dateFrom": "2024-01-01", "dateTo": "2024-12-31", "surfaces": ["clay"] } ``` A doubles specialist's last 12 months, by player URL: ```json { "players": ["https://www.flashscore.com/player/arevalo-marcelo/zLNFemL9/"], "matchTypes": ["doubles"], "dateFrom": "12 months" } ``` ### What data do you get? Every row is one match of one player, newest first. Results, scores and statistics read from that player's side: `player` first, then `opponent`. | Field | What it holds | | ---------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `player` | The player you asked for: Flashscore id, short and full name, country and link | | `matchId`, `url` | Flashscore match id and link | | `date` | Start time (ISO 8601, UTC) | | `tour`, `matchType` | ATP, WTA, Challenger Men/Women, ITF Men/Women or Exhibition; `singles`, `doubles` or `mixed` | | `tournament` | Name, country, main draw or qualification, surface, indoor, category, ids and link | | `round`, `roundCode` | Round as Flashscore names it (*Quarter-finals*) and as a short code: `R128` to `R16`, `QF`, `SF`, `F`, `Q1` to `Q3`, `RR` | | `partner`, `opponent` | Doubles partner (empty in singles); the opponent's name and players with ids, countries and links | | `result`, `resultType` | `won` or `lost`; `normal`, `retired`, `walkover` or `awarded` | | `status`, `statusDetail` | `finished` and Flashscore's wording (*Finished*, *Finished / retired*, *Walkover*) | | `score`, `sets` | The score from the player's side (`6-7(7) 7-6(2) 6-3 6-4`, empty for a walkover) and each set's games and tiebreak points | | `setsWon`, `setsLost`, `gamesWon`, `gamesLost` | Totals from the player's side | | `note` | Flashscore's note, such as *Alcaraz Carlos - withdrawn.* | | `durationMinutes` | With **Match statistics and duration**: match duration; each set's duration is in `sets` | | `statistics` | With **Match statistics and duration**: over 20 statistics for the match and each set | | `odds` | With **Bookmaker odds**: closing and opening match winner prices per bookmaker, best price, averages, implied probability and the favourite; optionally every market | | `missingDetails` | Parts you asked for that could not be loaded for this match | #### Output example A row with the default settings: ```json { "player": { "id": "UkhgIFEq", "name": "Alcaraz C.", "fullName": "Alcaraz Carlos", "country": "Spain", "url": "https://www.flashscore.com/player/alcaraz-garfia-carlos/UkhgIFEq/" }, "matchId": "nBSdhTc4", "url": "https://www.flashscore.com/match/tennis/nBSdhTc4/", "date": "2026-10-06T09:15:00.000Z", "tour": "ATP", "matchType": "singles", "tournament": { "name": "Tokyo", "country": "Japan", "stage": "Main draw", "surface": "hard", "indoor": false, "category": "ATP - Singles", "id": "KEoT9gX7", "stageId": "6Lja5eNc", "url": "https://www.flashscore.com/tennis/atp-singles/tokyo/" }, "round": "Final", "roundCode": "F", "partner": null, "opponent": { "name": "Lehecka J.", "players": [ { "id": "6PlgfXKR", "name": "Lehecka J.", "country": "Czech Republic", "url": "https://www.flashscore.com/player/lehecka-jiri/6PlgfXKR/" } ] }, "result": "won", "resultType": "normal", "status": "finished", "statusDetail": "Finished", "score": "7-6(4) 6-4", "sets": [ { "player": 7, "opponent": 6, "tiebreakPlayer": 7, "tiebreakOpponent": 4 }, { "player": 6, "opponent": 4, "tiebreakPlayer": null, "tiebreakOpponent": null } ], "setsWon": 2, "setsLost": 0, "gamesWon": 13, "gamesLost": 10, "note": null, "scrapedAt": "2026-10-21T15:31:55.049Z" } ``` A match with statistics and odds (lists shortened with "…"): ```json { "player": { "id": "6HdC3z4H", "name": "Sinner J.", "fullName": "Sinner Jannik", "country": "Italy", "url": "…" }, "matchId": "n5DWLXD5", "url": "https://www.flashscore.com/match/tennis/n5DWLXD5/", "date": "2026-07-12T15:10:00.000Z", "tour": "ATP", "matchType": "singles", "tournament": { "name": "Wimbledon", "country": "United Kingdom", "stage": "Main draw", "surface": "grass", "…": "…" }, "round": "Final", "roundCode": "F", "partner": null, "opponent": { "name": "Zverev A.", "players": ["…"] }, "result": "won", "resultType": "normal", "status": "finished", "statusDetail": "Finished", "score": "6-7(7) 7-6(2) 6-3 6-4", "sets": [ { "player": 6, "opponent": 7, "tiebreakPlayer": 7, "tiebreakOpponent": 9, "durationMinutes": 65 }, { "player": 7, "opponent": 6, "tiebreakPlayer": 7, "tiebreakOpponent": 2, "durationMinutes": 64 }, { "player": 6, "opponent": 3, "tiebreakPlayer": null, "tiebreakOpponent": null, "durationMinutes": 49 }, { "player": 6, "opponent": 4, "tiebreakPlayer": null, "tiebreakOpponent": null, "durationMinutes": 50 } ], "setsWon": 3, "setsLost": 1, "gamesWon": 25, "gamesLost": 20, "note": null, "durationMinutes": 228, "statistics": { "match": { "aces": { "player": 15, "opponent": 17 }, "doubleFaults": { "player": 2, "opponent": 2 }, "firstServePointsWon": { "player": { "percent": 80, "won": 70, "total": 87 }, "opponent": { "percent": 72, "won": 76, "total": 105 } }, "breakPointsConverted": { "player": { "won": 2, "total": 5 }, "opponent": { "won": 0, "total": 1 } }, "winners": { "player": 58, "opponent": 49 }, "unforcedErrors": { "player": 25, "opponent": 45 }, "distanceCoveredMetres": { "player": 2591, "opponent": 2441 }, "…": "…" }, "set1": "…", "set2": "…", "set3": "…", "set4": "…" }, "odds": { "countries": ["GB", "US-NJ"], "bookmakers": ["bet365", "Betfred", "Unibetuk", "…"], "matchWinner": { "best": { "player": 1.22, "opponent": 5 }, "average": { "player": 1.187, "opponent": 4.759 }, "averageOpening": { "player": 1.213, "opponent": 4.21 }, "impliedProbability": { "player": 0.8004, "opponent": 0.1996 }, "favourite": "player", "byBookmaker": [ { "bookmaker": "bet365", "player": 1.18, "opponent": 5, "playerOpening": 1.2, "opponentOpening": 4.8 }, "…" ] }, "markets": [ { "market": "total-games", "period": "match", "bookmaker": "bet365", "selections": [ { "selection": "over", "odds": 1.83, "opening": 1.83, "active": true, "line": 37.5, "unit": "games" }, { "selection": "under", "odds": 1.83, "opening": 1.83, "active": true, "line": 37.5, "unit": "games" }, "…" ] }, "…" ] }, "scrapedAt": "2026-10-21T15:26:17.398Z" } ``` #### Player summary Each run also saves a free summary for each player and match type, built from the rows of that run. Find it in the run's **Output** tab or in the key-value store under `PLAYER_SUMMARY`: ```json [ { "player": { "id": "GrsQDFC0", "name": "Federer R.", "fullName": "Federer Roger", "country": "Switzerland", "url": "…" }, "matchType": "singles", "firstMatch": "1998-07-06T09:00:00.000Z", "lastMatch": "2021-07-07T15:25:00.000Z", "matches": 1552, "won": 1270, "lost": 282, "winRate": 0.818, "walkovers": 18, "titles": 103, "finals": 157, "bySurface": { "grass": { "matches": 220, "won": 191, "lost": 29, "winRate": 0.868 }, "clay": { "matches": 284, "won": 216, "lost": 68, "winRate": 0.761 }, "hard": { "matches": 1015, "won": 834, "lost": 181, "winRate": 0.822 }, "unknown": { "matches": 33, "won": 29, "lost": 4, "winRate": 0.879 } }, "byYear": { "1998": { "matches": 5, "won": 2, "lost": 3, "winRate": 0.4 }, "…": "…" }, "byTour": { "ATP": { "matches": 1526, "won": 1252, "lost": 274, "winRate": 0.82 }, "Exhibition": { "matches": 25, "won": 17, "lost": 8, "winRate": 0.68 }, "…": "…" } } ] ``` Walkovers are counted on their own and left out of the win rates. Titles and finals need **Round** turned on (the default) and leave out exhibitions. A Davis Cup tie has no surface on Flashscore, so it counts as `unknown`. ### How much does it cost? You pay only for the matches you get (pay per event); Apify platform usage is included. | What | Price | | ----------------------------- | ------------------------ | | Match | $6.00 per 1,000 matches | | Match with statistics or odds | $12.00 per 1,000 matches | | Run start | $0.05 per 1,000 runs | A match costs the higher price only when it comes with statistics or odds. An old match that Flashscore has no statistics or odds for costs the lower price, even with those options on. Examples: - The last 20 matches of two players: about **$0.24**. - Roger Federer's whole singles career (1,570 matches): about **$9.40**. - Djokovic vs Nadal, all 60 meetings with statistics and odds: about **$0.64** (the 14 meetings before 2009 have neither, so they cost the lower price). Cap any run with **Max results** or **Latest matches per player**, or with the maximum cost per run in the run options; the run stops cleanly at the limit. Apify's free plan includes $5 of monthly credit, enough for about 830 matches. ### Tips - **Names or URLs.** Names go through Flashscore's player search. Accents and case don't matter, and a surname alone works for well-known players. For an exact pick, use the player URL. - **Dates are in UTC.** Use a date (`2025-01-01`) or a period back from today (`6 months`, `2 years`). - **Coverage follows Flashscore.** Tour-level results go back to the late 1990s; Challenger and ITF results cover fewer early years. Statistics exist for most tour-level matches since about 2018 (Grand Slams since about 2012), odds for most matches since about 2010. A part that Flashscore doesn't have for a match is `null`. - **More bookmakers.** The UK has the most (about 7 to 9 for older matches, up to 20 for recent ones). Add the US, Italy or Spain to compare more; each extra country adds one request per match. - **Team events and exhibitions** (Davis Cup, Laver Cup, Hopman Cup) are included, usually without a round. Pick tours to leave exhibitions out. - **Walkovers and retirements** are kept and flagged in `resultType`. A walkover has no score. - **Doubles** rows name the `partner`. A deciding match tiebreak written like a set (10-8) is left out of the games totals. - **Collect new results on a schedule.** Turn on **Only new matches** and [schedule](https://docs.apify.com/platform/schedules) the run daily or weekly. Each run returns only the matches the last one didn't. - **Integrations.** Send results to Google Sheets, Slack, Zapier, Make or your own webhook with Apify [integrations](https://apify.com/integrations), or call the Actor through the [API](https://docs.apify.com/api/v2). ### FAQ **How far back does the history go?** Tour-level matches go back to the late 1990s: Roger Federer's history starts with his first ATP match in July 1998. Lower-level events cover fewer early years. **Does it include each player's ranking at the time of the match?** No. Flashscore shows only current rankings, so rankings at the time of past matches are not part of the data. **How fast is it?** About 30 matches per second with the default settings, so a 1,500-match career takes under a minute. Statistics and odds add one or two requests per match: the 60 Djokovic vs Nadal matches with both take about 40 seconds. **Do I need a proxy?** No. Flashscore answers Apify's servers directly. The proxy option is there in case that changes. **Is it legal to scrape Flashscore?** This Actor collects publicly available sports data: results, statistics, published odds and the public names of professional athletes. It does not log in or collect private information. Check the source's terms and your local laws for your use case, especially for commercial use. **Something is missing or broken?** Open an issue in the **Issues** tab with the run link, and it will be looked at. *Tennis Player Match History is an independent tool. It is not affiliated with, endorsed by or connected to Flashscore or Livesport s.r.o., the ATP or the WTA. Odds are shown for information only.* # Actor input Schema ## `players` (type: `array`): Names (Carlos Alcaraz, Iga Swiatek, Djokovic) or Flashscore player URLs (https://www.flashscore.com/player/djokovic-novak/AZg49Et9/). When a name fits several players, the best known one is used and the log lists the others; paste a URL to pick a specific player. ## `matchTypes` (type: `array`): Which of the player's matches to get. Singles when empty. ## `maxMatchesPerPlayer` (type: `integer`): Only each player's latest N matches that fit the filters (per match type). 0 means the whole career that fits the dates. ## `dateFrom` (type: `string`): Only matches on or after this day (UTC). A date such as 2024-01-01, or a period back from today such as 12 months. Empty means the whole career; tour-level results go back to the late 1990s. ## `dateTo` (type: `string`): Only matches on or before this day (UTC). Empty means up to today. ## `opponents` (type: `array`): Only matches against these players: names (Jannik Sinner, Sinner) or Flashscore player URLs. With one player above and one here you get their head-to-head. ## `surfaces` (type: `array`): Only matches on these surfaces. Leave empty for all. ## `tours` (type: `array`): Only these levels. ATP and WTA include Grand Slams, Davis Cup, Billie Jean King Cup, United Cup and the Olympics. Leave empty for all. ## `mainDrawOnly` (type: `boolean`): Leave out qualifying matches. ## `includeRound` (type: `boolean`): The round, as Flashscore names it (Quarter-finals) and as a short code (R128 … R16, QF, SF, F, Q1-Q3 in qualifying, RR for group stages). Turn off for faster runs. ## `includeStatistics` (type: `boolean`): Aces, double faults, first serve %, points won on serve and return, break points saved and converted, winners, unforced errors and more, for the match and each set, plus the match and set durations. Flashscore has statistics for most tour-level matches since about 2018 and Grand Slams since about 2012. ## `includeOdds` (type: `boolean`): Opening and closing match-winner odds from each bookmaker, with the best and average price, the implied win probability and who was the favourite. Available for most matches since about 2010. ## `oddsMarkets` (type: `string`): Match winner only, or every market Flashscore lists: set winner, total games, game and set handicaps, correct score. ## `oddsCountries` (type: `array`): Bookmakers differ by country. The United Kingdom has the most for past matches (about 7-9 from 2010 on, up to 20 for recent ones). Each extra country adds one request per match. ## `onlyNew` (type: `boolean`): Save only matches that an earlier run with the same settings did not return. Use it with a schedule (for example daily) to collect each player's new results without paying for old rows again. ## `maxItems` (type: `integer`): Stop after this many rows in total. 0 means no limit. A long career has 1,000-1,600 singles matches. ## `maxConcurrency` (type: `integer`): How many requests run at the same time. ## `proxyConfiguration` (type: `object`): Not needed in most cases: Flashscore answers Apify's servers directly. Turn it on only if runs start failing with "blocked". ## Actor input object example ```json { "players": [ "Carlos Alcaraz", "Aryna Sabalenka" ], "matchTypes": [ "singles" ], "maxMatchesPerPlayer": 20, "opponents": [], "surfaces": [], "tours": [], "mainDrawOnly": false, "includeRound": true, "includeStatistics": false, "includeOdds": false, "oddsMarkets": "matchWinner", "oddsCountries": [ "GB" ], "onlyNew": false, "maxItems": 10000, "maxConcurrency": 10, "proxyConfiguration": { "useApifyProxy": false } } ``` # Actor output Schema ## `matches` (type: `string`): No description ## `playerSummary` (type: `string`): No description ## `summary` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "players": [ "Carlos Alcaraz", "Aryna Sabalenka" ], "maxMatchesPerPlayer": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("keelwright/tennis-player-history").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "players": [ "Carlos Alcaraz", "Aryna Sabalenka", ], "maxMatchesPerPlayer": 20, } # Run the Actor and wait for it to finish run = client.actor("keelwright/tennis-player-history").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "players": [ "Carlos Alcaraz", "Aryna Sabalenka" ], "maxMatchesPerPlayer": 20 }' | apify call keelwright/tennis-player-history --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,keelwright/tennis-player-history" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/qBRL8SPjtRDbh45oq/builds/mcMZg4baGroiEKi7M/openapi.json