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Unlock the power of European football data

The Premier League Python library provides a unified interface to access comprehensive football data across Europe’s top 5 leagues. Whether you’re building machine learning models, analyzing team performance, or creating data-driven applications, this library gives you everything you need.

Match statistics

Access detailed match-level statistics with 100+ metrics per game, including xG, passing, defensive actions, and possession data

League standings

Retrieve current and historical league tables with comprehensive team statistics dating back decades

Player leaders

Track top scorers and assist providers across all supported leagues with detailed breakdowns

Transfer data

Monitor incoming and outgoing transfers for every team with historical transfer window data

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Supported leagues

Access data from Europe’s premier football competitions:
  • Premier League (England)
  • La Liga (Spain)
  • Serie A (Italy)
  • Bundesliga (Germany)
  • Ligue 1 (France)
  • EFL Championship (England)

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Key capabilities

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Machine learning ready

Generate ML-ready datasets with customizable historical aggregation: 
from premier_league import MatchStatistics

stats = MatchStatistics()
stats.create_dataset(
    "training_data.csv",
    lag=10,  # Aggregate last 10 games
    weights="exp",  # Exponential weighting for recent games
    params=2.0
)
The library maintains a SQLite database with complete match history since the 2017-2018 season, featuring detailed statistics broken down by player position (FW, MF, DF, GK).

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Flask API server

Deploy a production-ready REST API in seconds: 
from premier_league import run_server

run_server(
    host="0.0.0.0",
    port=8000,
    mode="production",
    workers=4
)
Built-in features include rate limiting, caching, CORS support, and comprehensive endpoints for all data types.

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AWS Lambda deployment

Deploy serverless APIs with pre-configured Lambda functions and S3 integration: 
S3_BUCKET_NAME=my-bucket python -m premier_league.lambda_functions.deploy_premier_league \
  --aws-profile my-profile \
  --region us-east-1

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Multiple export formats

Export data in the format that suits your workflow:
  • CSV - For spreadsheet analysis
  • JSON - For web applications
  • PDF - For formatted reports with color-coded sections

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Match statistics

The MatchStatistics class provides access to extensive game data with 100+ statistical fields per match: 
from premier_league import MatchStatistics
from datetime import datetime

stats = MatchStatistics()

# Get team's complete match history
arsenal_games = stats.get_team_games("Arsenal")

# Query by season and match week
week_5_games = stats.get_games_by_season("2023-2024", match_week=5)

# Get recent games with detailed stats
recent = stats.get_games_before_date(
    date=datetime(2024, 2, 1),
    limit=10,
    team="Manchester City"
)

# Update with latest data
stats.update_data_set()
Available metrics include:
  • Expected Goals (xG, xAG, PSxG)
  • Shooting (total shots, shots on target, shot/goal creating actions)
  • Passing (completion %, progressive passes, key passes)
  • Defensive (tackles, interceptions, blocks, clearances)
  • Possession (touches, carries, take-ons, dribbles)
  • Discipline (fouls, cards, offsides)
All statistics are broken down by position groups (FW, MF, DF) for granular analysis.

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League standings

The RankingTable class fetches current and historical league tables: 
from premier_league import RankingTable

# Current Premier League standings
ranking = RankingTable()
standings = ranking.get_ranking_list()

# Historical season
ranking_95 = RankingTable(target_season="1995-1996")

# Different league
serie_a = RankingTable(league="Serie A")

# Export to various formats
ranking.get_ranking_csv("standings")
ranking.get_ranking_json("standings", header="PL_2024")
ranking.get_ranking_pdf("standings")  # Color-coded with qualification zones
Historical coverage:
  • Premier League: from 1947
  • La Liga: from 1929
  • Serie A: from 1929
  • Bundesliga: from 1963
  • Ligue 1: from 1945

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Player leaders

The PlayerSeasonLeaders class tracks top performers: 
from premier_league import PlayerSeasonLeaders

# Top scorers
scorers = PlayerSeasonLeaders(stat_type='G')
top_10_scorers = scorers.get_top_stats_list(limit=10)

# Top assist providers
assists = PlayerSeasonLeaders(stat_type='A', target_season='2022-23')
top_assists = assists.get_top_stats_list(limit=10)

# Different league
ligue_1_scorers = PlayerSeasonLeaders(stat_type='G', league="Ligue 1")

# Export data
scorers.get_top_stats_csv("top_scorers", limit=20)
scorers.get_top_stats_json("top_scorers", header="PL_Scorers")
scorers.get_top_stats_pdf("top_scorers")  # Top 20 with gold highlighting
Goals data includes in-play goals and penalty breakdowns. Assists data provides clean assist counts with nationality and club information.

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Transfer data

The Transfers class provides comprehensive transfer window data: 
from premier_league import Transfers

# Current season transfers
transfers = Transfers()

# Get all teams for reference
teams = transfers.get_all_current_teams()

# Incoming transfers
arsenal_ins = transfers.transfer_in_table("Arsenal")

# Outgoing transfers
arsenal_outs = transfers.transfer_out_table("Arsenal")

# Pretty print to console
transfers.print_transfer_table("Arsenal")

# Export with type filtering
transfers.transfer_csv("Chelsea", "chelsea_transfers", transfer_type="both")
transfers.transfer_json("Liverpool", "liverpool_ins", transfer_type="in")
Historical coverage:
  • Premier League: from 1946
  • La Liga: from 1928
  • Serie A: from 1946
  • Bundesliga: from 1963
  • Ligue 1: from 1945

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Installation extras

The library supports optional dependencies for specialized features: 
# PDF export functionality
pip install premier_league[pdf]

# Flask API server
pip install premier_league[api]

# AWS Lambda deployment
pip install premier_league[lambda]

# All features
pip install premier_league[all]

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Next steps

Quickstart

Get up and running in 5 minutes with a working example

Installation

Detailed installation guide with all optional dependencies