Padel Statistics API - Padel API

Professional padel generates detailed statistics for every match. The Padel API organizes this data at three levels: match, player, and pair. Each level answers different questions.

Match Stats

Point-by-point breakdown: serve %, break points, streaks, set-by-set data.

Player Stats

Career aggregates: win rate, titles, finals, best round.

Pair Stats

Combined performance: how a specific duo performs together.

Match statistics

The most granular level. Every match with available data includes stats for both teams, broken down by set.

curl -X GET \
  'https://padelapi.org/api/matches/{match_id}/stats' \
  -H 'Authorization: Bearer YOUR_API_TOKEN'

A match stats response includes overall totals plus per-set breakdowns:

{
  "id": 1216,
  "match": {
    "total_points_won": { "team_1": "50%", "team_2": "50%" },
    "break_points_converted": { "team_1": "33%", "team_2": "22%" },
    "longest_streak": { "team_1": "5", "team_2": "7" },
    "won_on_1st_serve": { "team_1": "67%", "team_2": "65%" },
    "won_on_2nd_serve": { "team_1": "54%", "team_2": "55%" },
    "total_won_on_serve": { "team_1": "66%", "team_2": "64%" },
    "total_won_on_return": { "team_1": "36%", "team_2": "34%" },
    "service_games": { "team_1": "15", "team_2": "15" },
    "return_games": { "team_1": "15", "team_2": "15" }
  },
  "set_1": { ... },
  "set_2": { ... },
  "set_3": { ... }
}

Available metrics per set

Metric	Description
`total_points_won`	Percentage of total points won
`break_points_converted`	Break point conversion rate
`longest_streak`	Longest consecutive points won
`aces`	Number of aces
`double_faults`	Number of double faults
`won_on_1st_serve`	Win % on first serve
`won_on_2nd_serve`	Win % on second serve
`total_won_on_serve`	Overall serve win %
`won_on_1st_return`	Win % returning first serve
`won_on_2nd_return`	Win % returning second serve
`total_won_on_return`	Overall return win %
`service_games`	Number of service games played
`return_games`	Number of return games played

Set-by-set data lets you track momentum shifts. A team winning 77% on serve in set 3 after 59% in set 1 tells a story that the match total alone doesn’t.

Player statistics

Career-level aggregates for any player. Useful for comparing trajectories, building rankings models, or analyzing form over specific periods.

curl -X GET \
  'https://padelapi.org/api/players/{player_id}/stats' \
  -H 'Authorization: Bearer YOUR_API_TOKEN'

{
  "id": 65,
  "matches_played": 160,
  "matches_won": 147,
  "win_percentage": 91.88,
  "sets_won": 303,
  "sets_lost": 49,
  "avg_sets_per_match": 2.2,
  "games_won": 2062,
  "games_lost": 1186,
  "avg_games_per_match": 20.3,
  "titles": 23,
  "finals": 30,
  "semifinals": 33,
  "best_round": 1
}

Filtering by date range

Player stats accept after_date and before_date parameters to calculate stats over a specific period. This is useful for season-by-season comparisons or tracking form over time.

# Stats for the 2025 season only
curl -X GET \
  'https://padelapi.org/api/players/65/stats?after_date=2025-01-01&before_date=2025-12-31' \
  -H 'Authorization: Bearer YOUR_API_TOKEN'

Filtering by round

Use the round parameter to isolate performance at specific tournament stages.

# Stats in finals only
curl -X GET \
  'https://padelapi.org/api/players/65/stats?round=1' \
  -H 'Authorization: Bearer YOUR_API_TOKEN'

Round value	Stage
`1`	Final
`2`	Semifinal
`4`	Quarterfinal
`8`	Round of 16
`16`	Round of 32
`32`	Round of 64

Comparing a player’s win percentage in early rounds vs finals reveals how they perform under pressure. Some players dominate early rounds but underperform in decisive matches, and vice versa.

Pair statistics

Padel is a doubles sport, and individual numbers only tell part of the story. Pair stats measure how two specific players perform together.

curl -X GET \
  'https://padelapi.org/api/pairs/{player_1_id}-{player_2_id}/stats' \
  -H 'Authorization: Bearer YOUR_API_TOKEN'

{
  "id": "65-66",
  "matches_played": 302,
  "matches_won": 276,
  "win_percentage": 91.39,
  "sets_won": 567,
  "sets_lost": 101,
  "avg_sets_per_match": 2.21,
  "games_won": 3892,
  "games_lost": 2341,
  "avg_games_per_match": 20.64,
  "titles": 43,
  "finals": 57,
  "semifinals": 62,
  "best_round": 1
}

Pair stats also support after_date, before_date, and round filters, just like player stats.

What pair stats reveal

The gap between a player’s individual stats and their pair stats exposes partner chemistry. A player with an 80% win rate overall but 90% with a specific partner suggests that pairing is greater than the sum of its parts. Compare pairs across:

Win percentage to find the most dominant duos
Titles vs finals to measure conversion rate in decisive matches
Average games per match as a proxy for match difficulty (lower = more dominant wins)

Common use cases

Building a player comparison dashboard

Combine player stats with date filters to create season-by-season comparisons:

import requests

API_TOKEN = "YOUR_API_TOKEN"
HEADERS = {"Authorization": f"Bearer {API_TOKEN}"}
BASE_URL = "https://padelapi.org/api"

player_id = 65
seasons = [
    ("2023-01-01", "2023-12-31"),
    ("2024-01-01", "2024-12-31"),
    ("2025-01-01", "2025-12-31"),
]

for start, end in seasons:
    response = requests.get(
        f"{BASE_URL}/players/{player_id}/stats",
        headers=HEADERS,
        params={"after_date": start, "before_date": end}
    )
    stats = response.json()
    print(f"{start[:4]}: {stats['matches_won']}/{stats['matches_played']} "
          f"({stats['win_percentage']}%) - {stats['titles']} titles")

Analyzing serve dominance in a match

Extract serve and return metrics to understand match dynamics:

response = requests.get(
    f"{BASE_URL}/matches/1216/stats",
    headers=HEADERS
)
stats = response.json()

for set_key in ["set_1", "set_2", "set_3"]:
    if set_key in stats:
        s = stats[set_key]
        print(f"{set_key}: Team 1 serve {s['total_won_on_serve']['team_1']} "
              f"| Team 2 serve {s['total_won_on_serve']['team_2']}")

Tips

Not all matches have stats

Match statistics depend on official data availability. Major and P1 tournaments typically have full stats coverage, while lower-level tournaments may not. Check the response before assuming data exists.

Player IDs can change

When two player records are merged, the API returns a 302 redirect to the canonical player. Handle redirects in your HTTP client to avoid broken references.

Use Padel Analyst for exploration

Before writing code, you can explore stats interactively using Padel Analyst. Ask questions like “What’s Coello’s win percentage in finals?” or “Show me match stats for the latest Major final” to find what you need.

Next steps

Your First API Call

Get set up with authentication and basic requests

API Reference

Full endpoint documentation with parameters and responses

Padel Analyst

Explore stats in natural language with AI assistants

Guides

Match Stats

Player Stats

Pair Stats

​Match statistics

​Available metrics per set

​Player statistics

​Filtering by date range

​Filtering by round

​Pair statistics

​What pair stats reveal

​Common use cases

​Building a player comparison dashboard

​Analyzing serve dominance in a match

​Tips

​Next steps

Your First API Call

API Reference

Padel Analyst

Match statistics

Available metrics per set

Player statistics

Filtering by date range

Filtering by round

Pair statistics

What pair stats reveal

Common use cases

Building a player comparison dashboard

Analyzing serve dominance in a match

Tips

Next steps