Name: Football Data From Transfermarkt
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Football Data From Transfermarkt

TL;DR

Clean, structured and automatically updated football data from Transfermarkt, including

60,000+ games from many seasons on all major competitions

400+ clubs from those competitions

30,000+ players from those clubs

400,000+ player market valuations historical records

1,200,000+ player appearance records from all games

and more!

What does it contain?

The dataset is composed of multiple CSV files with information on competitions, games, clubs, players and appearances that is automatically updated once a week. Each file contains the attributes of the entity and the IDs that can be used to join them together.

For example, the appearances file contains one row per player appearance, i.e. one row per player per game played. For each appearance you will find attributes such as goals, assists or yellow_cards and IDs referencing other entities within the dataset, such as player_id and game_id.

Idea: Chekout the mate data.world project Football Data from Transfermarkt for examples of how to use the resources in this dataset to create different types of analysis.

How did we build it?

The source code that maintains this dataset, as well as the data pipeline, is available in Github. On a high level, the project uses transfermarkt-scraper to pull the data from Transfermark website and a set of Python scripts and SQL to curate it and publish it here.

Idea: Watch the transfermarkt-datasets Github repository for updates on improvements and bugfixes on this dataset

What is the status?

This dataset is a live project subject to regular updates and new enhancements. The best way to find out about the different initiatives within this project and their status is to check the Issues section on transfermarkt-datasets.

Contact

The source of truth for the code and data for this project is Github and that is the best place to start a conversation, please checkout the community guidelines here.

If you have a github user I kindly ask that you post your questions there and not in the Discussion tab in this website.

Tables

Appearances

@kaggle.davidcariboo_player_scores.appearances

26.59 MB
1,669,732 rows
13 columns

CREATE TABLE appearances (
  "appearance_id" VARCHAR,
  "game_id" BIGINT,
  "player_id" BIGINT,
  "player_club_id" BIGINT,
  "player_current_club_id" BIGINT,
  "date" TIMESTAMP,
  "player_name" VARCHAR,
  "competition_id" VARCHAR,
  "yellow_cards" BIGINT,
  "red_cards" BIGINT,
  "goals" BIGINT,
  "assists" BIGINT,
  "minutes_played" BIGINT
);

Club Games

@kaggle.davidcariboo_player_scores.club_games

2.08 MB
145,182 rows
11 columns

CREATE TABLE club_games (
  "game_id" BIGINT,
  "club_id" DOUBLE,
  "own_goals" DOUBLE,
  "own_position" DOUBLE,
  "own_manager_name" VARCHAR,
  "opponent_id" DOUBLE,
  "opponent_goals" DOUBLE,
  "opponent_position" DOUBLE,
  "opponent_manager_name" VARCHAR,
  "hosting" VARCHAR,
  "is_win" BIGINT
);

Clubs

@kaggle.davidcariboo_player_scores.clubs

56.54 kB
439 rows
17 columns

CREATE TABLE clubs (
  "club_id" BIGINT,
  "club_code" VARCHAR,
  "name" VARCHAR,
  "domestic_competition_id" VARCHAR,
  "total_market_value" VARCHAR,
  "squad_size" BIGINT,
  "average_age" DOUBLE,
  "foreigners_number" BIGINT,
  "foreigners_percentage" DOUBLE,
  "national_team_players" BIGINT,
  "stadium_name" VARCHAR,
  "stadium_seats" BIGINT,
  "net_transfer_record" VARCHAR,
  "coach_name" VARCHAR,
  "last_season" BIGINT,
  "filename" VARCHAR,
  "url" VARCHAR
);

Competitions

@kaggle.davidcariboo_player_scores.competitions

11.37 kB
44 rows
11 columns

CREATE TABLE competitions (
  "competition_id" VARCHAR,
  "competition_code" VARCHAR,
  "name" VARCHAR,
  "sub_type" VARCHAR,
  "type" VARCHAR,
  "country_id" BIGINT,
  "country_name" VARCHAR,
  "domestic_league_code" VARCHAR,
  "confederation" VARCHAR,
  "url" VARCHAR,
  "is_major_national_league" BOOLEAN
);

Game Events

@kaggle.davidcariboo_player_scores.game_events

42.13 MB
1,012,265 rows
10 columns

CREATE TABLE game_events (
  "game_event_id" VARCHAR,
  "date" TIMESTAMP,
  "game_id" BIGINT,
  "minute" BIGINT,
  "type" VARCHAR,
  "club_id" BIGINT,
  "player_id" BIGINT,
  "description" VARCHAR,
  "player_in_id" DOUBLE,
  "player_assist_id" DOUBLE
);

Game Lineups

@kaggle.davidcariboo_player_scores.game_lineups

90.03 MB
2,191,911 rows
10 columns

CREATE TABLE game_lineups (
  "game_lineups_id" VARCHAR,
  "date" TIMESTAMP,
  "game_id" BIGINT,
  "player_id" BIGINT,
  "club_id" BIGINT,
  "player_name" VARCHAR,
  "type" VARCHAR,
  "position" VARCHAR,
  "number" VARCHAR,
  "team_captain" BIGINT
);

Games

@kaggle.davidcariboo_player_scores.games

3.71 MB
72,591 rows
23 columns

CREATE TABLE games (
  "game_id" BIGINT,
  "competition_id" VARCHAR,
  "season" BIGINT,
  "round" VARCHAR,
  "date" TIMESTAMP,
  "home_club_id" DOUBLE,
  "away_club_id" DOUBLE,
  "home_club_goals" DOUBLE,
  "away_club_goals" DOUBLE,
  "home_club_position" DOUBLE,
  "away_club_position" DOUBLE,
  "home_club_manager_name" VARCHAR,
  "away_club_manager_name" VARCHAR,
  "stadium" VARCHAR,
  "attendance" DOUBLE,
  "referee" VARCHAR,
  "url" VARCHAR,
  "home_club_formation" VARCHAR,
  "away_club_formation" VARCHAR,
  "home_club_name" VARCHAR,
  "away_club_name" VARCHAR,
  "aggregate" VARCHAR,
  "competition_type" VARCHAR
);

Players

@kaggle.davidcariboo_player_scores.players

3.44 MB
32,471 rows
23 columns

CREATE TABLE players (
  "player_id" BIGINT,
  "first_name" VARCHAR,
  "last_name" VARCHAR,
  "name" VARCHAR,
  "last_season" BIGINT,
  "current_club_id" BIGINT,
  "player_code" VARCHAR,
  "country_of_birth" VARCHAR,
  "city_of_birth" VARCHAR,
  "country_of_citizenship" VARCHAR,
  "date_of_birth" TIMESTAMP,
  "sub_position" VARCHAR,
  "position" VARCHAR,
  "foot" VARCHAR,
  "height_in_cm" DOUBLE,
  "contract_expiration_date" TIMESTAMP,
  "agent_name" VARCHAR,
  "image_url" VARCHAR,
  "url" VARCHAR,
  "current_club_domestic_competition_id" VARCHAR,
  "current_club_name" VARCHAR,
  "market_value_in_eur" DOUBLE,
  "highest_market_value_in_eur" DOUBLE
);

Player Valuations

@kaggle.davidcariboo_player_scores.player_valuations

2.49 MB
494,505 rows
5 columns

CREATE TABLE player_valuations (
  "player_id" BIGINT,
  "date" TIMESTAMP,
  "market_value_in_eur" BIGINT,
  "current_club_id" BIGINT,
  "player_club_domestic_competition_id" VARCHAR
);

Transfers

@kaggle.davidcariboo_player_scores.transfers

1.43 MB
78,616 rows
10 columns

CREATE TABLE transfers (
  "player_id" BIGINT,
  "transfer_date" TIMESTAMP,
  "transfer_season" VARCHAR,
  "from_club_id" BIGINT,
  "to_club_id" BIGINT,
  "from_club_name" VARCHAR,
  "to_club_name" VARCHAR,
  "transfer_fee" DOUBLE,
  "market_value_in_eur" DOUBLE,
  "player_name" VARCHAR
);