Tennis Abstract Scraper — Player Profiles, Match Results & Seasonal Statistics

Extract complete tennis player data from TennisAbstract.com: career match history, per-match statistics (aces, hold %, break %, dominance ratio), tour-level and challenger seasonal summaries, and year-end Elo rankings — delivered as clean JSON on Apify.

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What it does

The Tennis Abstract Scraper is an Apify Actor that pulls structured, analysis-ready tennis data for any ATP or WTA player. Rather than leaving you to manually browse TennisAbstract.com, this Actor automates the entire data extraction pipeline and returns well-formed JSON organized into five distinct datasets:

• Player Profile — biographical and ranking data (full name, country, date of birth, playing hand, current and peak ATP rank, Elo rating, age, and playing style).
• All Match Results — every recorded match with tournament, surface, round, score, opponent details, and per-match serving / returning statistics.
• Tour-Level Seasons — year-by-year statistical summaries for ATP/WTA Tour events (win-loss, hold %, break %, aces, service/return percentages, dominance ratio).
• Challenger Seasons — the same statistical template, aggregated for Challenger-level events.
• Year-End Rankings — end-of-season ATP, WTP, and Elo rankings broken down by overall, hard-court, clay-court, and grass-court surfaces.

Each section can be toggled on or off independently, so you only pay for the data you actually need.

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Use cases

• Tennis analytics & scouting — feed match-by-match statistics into a modeling pipeline to identify performance trends, surface-specific strengths, or head-to-head patterns.
• Betting & prediction models — use hold %, break %, dominance ratio, and Elo ratings as features for match outcome or total-games predictors.
• Historical player comparison — pull profile and seasonal data for multiple players (e.g., Federer vs. Nadal vs. Djokovic) and compare career trajectories in a spreadsheet or BI tool.
• Fan & media research — quickly gather career summaries, match logs, and ranking histories without navigating the source website.
• Academic & statistical research — access structured, time-series tennis statistics for publications, theses, or data journalism projects.

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Input

Parameter	Type	Default	Description
player_name	string	Jannik Sinner	The player's name as it appears on TennisAbstract.com.
include_all_results_section	boolean	true	Fetch the complete career match log with per-match statistics.
include_tour_level_seasons_section	boolean	true	Fetch year-by-year ATP/WTA Tour-level seasonal summaries.
include_challenger_seasons_section	boolean	false	Fetch year-by-year Challenger-level seasonal summaries.
include_year_end_rankings_section	boolean	false	Fetch year-end ATP, WTP, and Elo rankings for each season.
max_results	integer	1000	Hard cap on the total number of records returned across all sections.

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Output

The Actor returns a single Player Profile record (in the default Apify dataset) containing the player's biographical and ranking data plus four embedded arrays — one for each data section that was requested:

List field	Contents
allResults	Individual match records with score, opponent details, and per-match stats (aces, break points, dominance ratio, etc.)
tourLevelSeasons	Year-by-year ATP/WTA Tour-level statistical summaries
challengerSeasons	Year-by-year Challenger-level statistical summaries
yearEndRankings	Year-end ATP, WTP, and Elo rankings broken down by surface

Each of these arrays is also written to its own dedicated Apify dataset, so you can consume either the combined profile or pull the granular records independently from the Storage tab.

Profile record

{
  "fullname": "Jannik Sinner",
  "country": "ITA",
  "dateOfBirth": "2002-08-30",
  "hand": "R",
  "backhand": "2",
  "currentRank": 1,
  "peakRank": 1,
  "peakRankDate": "2024-06-10",
  "eloRank": 1,
  "eloRating": 2485,
  "age": 23,
  "plays": "Right (two)-handed backhand"
}

allResults — sample match record

{
    "rawDate": "20260629",
    "tourn": "Wimbledon",
    "surf": "Grass",
    "level": "G",
    "wl": "W",
    "rank": "1",
    "seed": "1",
    "entry": "",
    "round": "F",
    "score": "6-7(7) 7-6(2) 6-3 6-4",
    "maxSets": 5,
    "opponent": "Alexander Zverev",
    "opponentRanking": "3",
    "opponentSeed": "2",
    "opponentEntry": "",
    "opponentHand": "R",
    "opponentBirthDate": "19970420",
    "opponentHeight": 198,
    "opponentCountry": "GER",
    "opponentActive": false,
    "aces": 15,
    "dfs": 2,
    "pts": 136,
    "firsts": 87,
    "fwon": 70,
    "swon": 32,
    "games": 22,
    "saved": 1,
    "chances": 1,
    "oaces": 17,
    "odfs": 2,
    "opts": 139,
    "ofirsts": 105,
    "ofwon": 76,
    "oswon": 20,
    "ogames": 21,
    "osaved": 3,
    "ochances": 5,
    "opponentBackhand": "2",
    "chartlink": "20260712-M-Wimbledon-F-Jannik_Sinner-Alexander_Zverev",
    "pslink": "",
    "whserver": "",
    "matchid": "2026-540-603",
    "wh": "",
    "roundnum": "",
    "matchnum": "",
    "dominanceRatio": 1.24,
    "aceRate": 11,
    "doubleFaultRate": 1.5,
    "firstServePercentage": 64,
    "firstServePointsWon": 80.5,
    "secondServePointsWon": 65.3,
    "breakPointOpportunitiesSaved": 1,
    "durationTime": "03:46:00",
    "matchDate": "2026-06-29",
    "opponentBirthDateObj": "1997-04-20",
    "winner": "Player",
    "loser": "Alexander Zverev"
  }

tourLevelSeasons — sample seasonal summary

{
  "year": 2024,
  "matchesPlayed": 70,
  "matchesWon": 63,
  "matchesLost": 7,
  "matchWinningPercentage": 90.0,
  "setW-L": "128-32",
  "setWinningPercentage": 80.0,
  "gameW-L": "680-340",
  "gameWinningPercentage": 66.7,
  "tiebreakWonLossRecord": "18-6",
  "tiebreakWinningPercentage": 75.0,
  "numberOfMatchesWithTheNextStats": 65,
  "holdPercentage": 84.3,
  "breakPercentage": 31.2,
  "aceRate": 8.1,
  "doubleFaultRate": 2.4,
  "firstServePercentage": 63.5,
  "firstServePointsWon": 79.4,
  "secondServePointsWon": 55.8,
  "servicePointsWon": 70.2,
  "returnPointsWon": 42.1,
  "totalPointsWon": 56.8,
  "dominanceRatio": 1.42,
  "best": "Won Australian Open"
}

challengerSeasons — sample challenger summary

{
  "year": 2020,
  "matchesPlayed": 22,
  "matchesWon": 17,
  "matchesLost": 5,
  "matchWinningPercentage": 77.3,
  "setW-L": "38-14",
  "setWinningPercentage": 73.1,
  "gameW-L": "240-170",
  "gameWinningPercentage": 58.5,
  "tiebreakWonLossRecord": "8-3",
  "tiebreakWinningPercentage": 72.7,
  "numberOfMatchesWithTheNextStats": 20,
  "holdPercentage": 79.5,
  "breakPercentage": 27.8,
  "aceRate": 6.2,
  "doubleFaultRate": 2.9,
  "firstServePercentage": 61.0,
  "firstServePointsWon": 74.8,
  "secondServePointsWon": 52.1,
  "servicePointsWon": 66.3,
  "returnPointsWon": 38.5,
  "totalPointsWon": 52.9,
  "dominanceRatio": 1.15,
  "best": "Won Challenger final"
}

yearEndRankings — sample ranking record

{
  "year": 2024,
  "atpRank": 1,
  "wtpRank": 1,
  "eloRank": 1,
  "elo": 2485,
  "hEloRank": 1,
  "hElo": 2510,
  "cEloRank": 2,
  "cElo": 2460,
  "gEloRank": 1,
  "gElo": 2520
}

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Notes & behavior

• No login required. The Actor accesses public player pages on TennisAbstract.com.
• Data freshness. Data is scraped on-demand at the time of the run; results reflect the state of TennisAbstract.com when the Actor executes.
• Rate limiting. The Actor uses Apify's built-in charge system to stay within the host site's rate limits and avoid disruptions.
• Max results cap. Setting max_results stops data collection once the threshold is reached, regardless of how many records remain on the source page.
• Section toggles. Disable sections you don't need to reduce compute time and API cost.

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