Transfers - Premier League

Overview

The Transfers class provides comprehensive access to player transfer data for professional football teams across Europe’s top 5 leagues. It enables tracking both incoming and outgoing transfers for any team in a given season.

Transfer data includes player names, positions, dates, and the clubs involved in each transfer, supporting seasons from the 1920s-1960s onwards depending on the league.

Installation

from premier_league import Transfers

Initialization

transfers = Transfers(
    target_season="2023-2024",
    league="Premier League",
    cache=True
)

Parameters

target_season

str

default:"None"

Specific season in format “YYYY-YYYY” (e.g., “2023-2024”). If None, uses current season

league

str

default:"premier league"

League to scrape transfer data for. Options:

“Premier League” (England)
“La Liga” (Spain)
“Serie A” (Italy)
“Bundesliga” (Germany)
“Ligue 1” (France)

cache

bool

default:"True"

Whether to cache scraped data for faster subsequent access

Quick Start

from premier_league import Transfers

# Get current season transfers
transfers = Transfers(league="Premier League")

# Print transfer table for a team
transfers.print_transfer_table("Chelsea")

Core Methods

print_transfer_table()

Print formatted transfer tables (both incoming and outgoing) for a specified team.

transfers = Transfers(
    league="Premier League",
    target_season="2023-2024"
)

transfers.print_transfer_table("Arsenal")

Output:

Arsenal >> Transfers 2023-2024 In:
+--------+------------------+----------+----------------------+
| Date   | Name             | Position | Club                 |
+--------+------------------+----------+----------------------+
| 07/01  | Declan Rice      | MF       | West Ham United      |
| 07/15  | Kai Havertz       | FW       | Chelsea              |
+--------+------------------+----------+----------------------+

Arsenal >> Transfers 2023-2024 Out:
+--------+------------------+----------+----------------------+
| Date   | Name             | Position | Club                 |
+--------+------------------+----------+----------------------+
| 06/30  | Granit Xhaka     | MF       | Bayer Leverkusen     |
+--------+------------------+----------+----------------------+

Parameters

team

str

required

Name of the team (fuzzy matching supported)

Raises

TeamNotFoundError: If the specified team is not found in the current season

transfer_in_table()

Get incoming transfers for a specific team as a structured list.

transfers = Transfers(league="Bundesliga")

incoming = transfers.transfer_in_table("Bayern Munich")

# First row is headers
headers = incoming[0]
print(headers)  # ['Date', 'Name', 'Position', 'Club']

# Process each transfer
for transfer in incoming[1:]:
    date, player_name, position, from_club = transfer
    print(f"{player_name} joined from {from_club}")

Parameters

team

str

required

Name of the team

Returns

List[List[str]]: Nested list where:

First row: ['Date', 'Name', 'Position', 'Club']
Subsequent rows: Individual transfer data

Column Structure

Date: Transfer date in MM/DD format
Name: Player name
Position: Player position (FW, MF, DF, GK)
Club: Previous club the player joined from

Raises

TeamNotFoundError: If the team is not found

transfer_out_table()

Get outgoing transfers for a specific team as a structured list.

transfers = Transfers(
    league="Ligue 1",
    target_season="2022-2023"
)

outgoing = transfers.transfer_out_table("PSG")

print("Players who left PSG:")
for transfer in outgoing[1:]:
    date, player_name, position, to_club = transfer
    print(f"{player_name} ({position}) → {to_club}")

Parameters

team

str

required

Name of the team

Returns

List[List[str]]: Nested list with same structure as transfer_in_table()

Column Structure

Date: Transfer date in MM/DD format
Name: Player name
Position: Player position
Club: New club the player transferred to

Raises

TeamNotFoundError: If the team is not found

transfer_csv()

Export transfer data to a CSV file.

transfers = Transfers(league="Serie A")

# Export both transfers in and out
transfers.transfer_csv(
    team="Juventus",
    file_name="juventus_transfers",
    transfer_type="both"
)

# Export only incoming transfers
transfers.transfer_csv(
    team="Inter Milan",
    file_name="inter_incoming",
    transfer_type="in"
)

# Export only outgoing transfers
transfers.transfer_csv(
    team="AC Milan",
    file_name="milan_outgoing",
    transfer_type="out"
)

Parameters

team

str

required

Name of the team

file_name

str

required

Name of the CSV file (without .csv extension)

transfer_type

Literal['in', 'out', 'both']

default:"both"

Type of transfers to export:

"in": Only incoming transfers
"out": Only outgoing transfers
"both": Both incoming and outgoing (creates separate sections)

Raises

TeamNotFoundError: If the team is not found

transfer_json()

Export transfer data to a JSON file.

transfers = Transfers(
    league="La Liga",
    target_season="2023-2024"
)

# Export to JSON
transfers.transfer_json(
    team="Real Madrid",
    file_name="real_madrid_transfers",
    transfer_type="both"
)

Parameters

team

str

required

Name of the team

file_name

str

required

Name of the JSON file (without .json extension)

transfer_type

Literal['in', 'out', 'both']

default:"both"

Type of transfers to export

Raises

TeamNotFoundError: If the team is not found

get_all_current_teams()

Get a list of all teams in the specified league and season.

transfers = Transfers(
    league="Premier League",
    target_season="2023-2024"
)

teams = transfers.get_all_current_teams()
print(f"Teams in Premier League 2023-2024: {len(teams)}")
for team in sorted(teams):
    print(f"  - {team}")

Returns

List[str]: List of all team names in the league for the specified season

find_team()

Find the exact team name from a partial or case-insensitive match.

transfers = Transfers(league="Bundesliga")

# Fuzzy search
team = transfers.find_team("bayern")  # Returns "Bayern Munich"
print(team)

team = transfers.find_team("dortmund")  # Returns "Borussia Dortmund"
print(team)

team = transfers.find_team("xyz")  # Returns None
print(team)

Parameters

target_team

str

required

Team name or partial identifier (case-insensitive)

Returns

str or None: Exact team name if found, None otherwise

Supported Leagues & Data Availability

Premier League
La Liga
Serie A
Bundesliga
Ligue 1

Country: England
Available from: 1946-1947 season

transfers = Transfers(
    league="Premier League",
    target_season="1992-1993"  # First PL season
)

Country: Spain
Available from: 1928-1929 season

transfers = Transfers(
    league="La Liga",
    target_season="2015-2016"
)

Country: Italy
Available from: 1946-1947 season

transfers = Transfers(
    league="Serie A",
    target_season="2018-2019"
)

Country: Germany
Available from: 1963-1964 season

transfers = Transfers(
    league="Bundesliga",
    target_season="2019-2020"
)

Country: France
Available from: 1945-1946 season

transfers = Transfers(
    league="Ligue 1",
    target_season="2021-2022"
)

Advanced Examples

Analyze Transfer Activity

from premier_league import Transfers

transfers = Transfers(
    league="Premier League",
    target_season="2023-2024"
)

# Get all teams
teams = transfers.get_all_current_teams()

# Analyze transfer activity
transfer_stats = []

for team in teams:
    transfers_in = transfers.transfer_in_table(team)
    transfers_out = transfers.transfer_out_table(team)
    
    transfer_stats.append({
        'team': team,
        'incoming': len(transfers_in) - 1,  # Exclude header
        'outgoing': len(transfers_out) - 1,
        'net': (len(transfers_in) - 1) - (len(transfers_out) - 1)
    })

# Sort by most active
transfer_stats.sort(key=lambda x: x['incoming'] + x['outgoing'], reverse=True)

print("Most Active Transfer Teams:\n")
for stat in transfer_stats[:5]:
    print(f"{stat['team']}:")
    print(f"  In: {stat['incoming']}, Out: {stat['outgoing']}, Net: {stat['net']}")

Track Specific Position

from premier_league import Transfers

transfers = Transfers(league="Serie A")

# Find all striker signings
teams = transfers.get_all_current_teams()

striker_signings = []

for team in teams:
    transfers_in = transfers.transfer_in_table(team)
    
    for transfer in transfers_in[1:]:
        date, name, position, from_club = transfer
        if position == "FW":
            striker_signings.append({
                'player': name,
                'to': team,
                'from': from_club,
                'date': date
            })

print(f"Total striker signings in Serie A: {len(striker_signings)}\n")
for signing in striker_signings[:10]:
    print(f"{signing['player']}: {signing['from']} → {signing['to']}")

Compare Seasons

from premier_league import Transfers

team_name = "Manchester United"
seasons = ["2021-2022", "2022-2023", "2023-2024"]

for season in seasons:
    transfers = Transfers(
        league="Premier League",
        target_season=season,
        cache=True
    )
    
    transfers_in = transfers.transfer_in_table(team_name)
    transfers_out = transfers.transfer_out_table(team_name)
    
    print(f"\n{team_name} - {season}:")
    print(f"  Signings: {len(transfers_in) - 1}")
    print(f"  Departures: {len(transfers_out) - 1}")
    
    if len(transfers_in) > 1:
        print("\n  Key Signings:")
        for transfer in transfers_in[1:4]:  # Top 3
            print(f"    - {transfer[1]} from {transfer[3]}")

Export League-Wide Data

from premier_league import Transfers
import os

league = "La Liga"
season = "2023-2024"

# Create output directory
output_dir = f"transfers/{league.replace(' ', '_').lower()}/{season}"
os.makedirs(output_dir, exist_ok=True)

transfers = Transfers(
    league=league,
    target_season=season
)

# Export for all teams
teams = transfers.get_all_current_teams()

for team in teams:
    safe_name = team.replace(" ", "_").replace("/", "_")
    
    # Export as CSV
    transfers.transfer_csv(
        team=team,
        file_name=f"{output_dir}/{safe_name}",
        transfer_type="both"
    )
    
    # Export as JSON
    transfers.transfer_json(
        team=team,
        file_name=f"{output_dir}/{safe_name}",
        transfer_type="both"
    )
    
    print(f"✓ Exported {team}")

print(f"\nAll transfers exported to {output_dir}/")

Identify Transfer Patterns

from premier_league import Transfers
from collections import Counter

transfers = Transfers(
    league="Premier League",
    target_season="2023-2024"
)

teams = transfers.get_all_current_teams()

# Track which leagues teams are buying from
source_leagues = []

for team in teams:
    transfers_in = transfers.transfer_in_table(team)
    
    for transfer in transfers_in[1:]:
        from_club = transfer[3]
        source_leagues.append(from_club)

# Count most common source clubs
common_sources = Counter(source_leagues).most_common(10)

print("Most Common Transfer Sources (2023-2024):\n")
for club, count in common_sources:
    print(f"{club}: {count} players")

Generate Transfer Report

from premier_league import Transfers
from datetime import datetime

def generate_transfer_report(league, season, team):
    """Generate a comprehensive transfer report"""
    
    transfers = Transfers(
        league=league,
        target_season=season
    )
    
    # Get data
    transfers_in = transfers.transfer_in_table(team)
    transfers_out = transfers.transfer_out_table(team)
    
    # Generate report
    report = []
    report.append(f"{'='*60}")
    report.append(f"TRANSFER REPORT: {team}")
    report.append(f"League: {league}")
    report.append(f"Season: {season}")
    report.append(f"Generated: {datetime.now().strftime('%Y-%m-%d %H:%M')}")
    report.append(f"{'='*60}\n")
    
    # Summary
    report.append("SUMMARY:")
    report.append(f"  Total Incoming: {len(transfers_in) - 1}")
    report.append(f"  Total Outgoing: {len(transfers_out) - 1}")
    report.append(f"  Net Transfer Activity: {(len(transfers_in) - 1) - (len(transfers_out) - 1)}\n")
    
    # Incoming
    report.append("INCOMING TRANSFERS:")
    if len(transfers_in) > 1:
        for transfer in transfers_in[1:]:
            report.append(f"  [{transfer[0]}] {transfer[1]} ({transfer[2]}) from {transfer[3]}")
    else:
        report.append("  None")
    
    report.append("\nOUTGOING TRANSFERS:")
    if len(transfers_out) > 1:
        for transfer in transfers_out[1:]:
            report.append(f"  [{transfer[0]}] {transfer[1]} ({transfer[2]}) to {transfer[3]}")
    else:
        report.append("  None")
    
    report.append(f"\n{'='*60}")
    
    # Print and save
    report_text = "\n".join(report)
    print(report_text)
    
    # Save to file
    filename = f"{team.replace(' ', '_')}_transfer_report_{season.replace('-', '_')}.txt"
    with open(filename, 'w') as f:
        f.write(report_text)
    
    print(f"\nReport saved to {filename}")

# Generate report
generate_transfer_report(
    league="Serie A",
    season="2023-2024",
    team="Napoli"
)

Find Inter-League Transfers

from premier_league import Transfers

# Track transfers between leagues
pl_transfers = Transfers(league="Premier League", target_season="2023-2024")
laliga_transfers = Transfers(league="La Liga", target_season="2023-2024")

pl_teams = pl_transfers.get_all_current_teams()
laliga_teams = laliga_transfers.get_all_current_teams()

print("Transfers from La Liga to Premier League:\n")

for pl_team in pl_teams:
    transfers_in = pl_transfers.transfer_in_table(pl_team)
    
    for transfer in transfers_in[1:]:
        date, name, position, from_club = transfer
        # Check if from_club is a La Liga team
        from_laliga = any(laliga_team.lower() in from_club.lower() for laliga_team in laliga_teams)
        
        if from_laliga:
            print(f"{name} ({position}): {from_club} → {pl_team}")

Error Handling

from premier_league import Transfers, TeamNotFoundError

transfers = Transfers(
    league="Bundesliga",
    target_season="2023-2024"
)

# Handle team not found
try:
    transfers.print_transfer_table("Invalid Team Name")
except TeamNotFoundError as e:
    print(f"Error: {e}")
    print("\nAvailable teams:")
    teams = transfers.get_all_current_teams()
    for team in sorted(teams):
        print(f"  - {team}")

# Use fuzzy matching
team_search = "bayern"
matched_team = transfers.find_team(team_search)

if matched_team:
    print(f"\nFound: {matched_team}")
    transfers.print_transfer_table(matched_team)
else:
    print(f"No team found matching '{team_search}'")

Use the find_team() method for fuzzy matching when you’re unsure of the exact team name. It performs case-insensitive substring matching.

The module automatically handles multi-word club names and special formatting in transfer data, providing clean and consistent output.

Some historical seasons may have incomplete transfer data. Always verify data completeness for critical analysis.

Get Started

Core Modules

Guides

​Overview

​Installation

​Initialization

​Parameters

​Quick Start

​Core Methods

​print_transfer_table()

​Parameters

​Raises

​transfer_in_table()

​Parameters

​Returns

​Column Structure

​Raises

​transfer_out_table()

​Parameters

​Returns

​Column Structure

​Raises

​transfer_csv()

​Parameters

​Raises

​transfer_json()

​Parameters

​Raises

​get_all_current_teams()

​Returns

​find_team()

​Parameters

​Returns

​Supported Leagues & Data Availability

​Advanced Examples

​Analyze Transfer Activity

​Track Specific Position

​Compare Seasons

​Export League-Wide Data

​Identify Transfer Patterns

​Generate Transfer Report

​Find Inter-League Transfers

​Error Handling

Overview

Installation

Initialization

Parameters

Quick Start

Core Methods

print_transfer_table()

Parameters

Raises

transfer_in_table()

Parameters

Returns

Column Structure

Raises

transfer_out_table()

Parameters

Returns

Column Structure

Raises

transfer_csv()

Parameters

Raises

transfer_json()

Parameters

Raises

get_all_current_teams()

Returns

find_team()

Parameters

Returns

Supported Leagues & Data Availability

Advanced Examples

Analyze Transfer Activity

Track Specific Position

Compare Seasons

Export League-Wide Data

Identify Transfer Patterns

Generate Transfer Report

Find Inter-League Transfers

Error Handling