Name: Soccer Universe
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Soccer Universe

This comprehensive football dataset, derived primarily from Transfermarkt, serves as a valuable resource for football enthusiasts, offering structured information on competitions, clubs, and players. With over 60,000 games across major global competitions, the dataset delves into the performance metrics of 400+ clubs and detailed statistics for more than 30,000 players.

Structured in CSV files, each with unique IDs, users can seamlessly join datasets to perform in-depth analyses. The dataset encompasses market values, historical valuations, and detailed player statistics, including physical attributes, contract statuses, and individual performances. A specialized Python-based web scraper ensures consistent updates, with data meticulously processed through Python scripts and SQL databases.

To use the dataset effectively, users are encouraged to understand the relevant files, join datasets using unique IDs, and leverage compatible software tools like Python's pandas or R's ggplot2 for analysis. The guide emphasizes the potential for fantasy football predictions, tracking player value over time, assessing market value versus performance, and exploring the impact of cards on match outcomes.

Research ideas include player performance analysis for fantasy football or recruitment purposes, studying market value trends for economic insights, evaluating club performance for strategic decision-making, developing predictive models for match outcomes, and conducting social network analysis to understand interactions among clubs and players.

Acknowledging the dataset's unknown license, users are encouraged to credit the original authors, particularly David Cereijo, if used in research. The dataset's dedication to accessibility is evident through active discussions on GitHub for improvements and bug fixes.

In conclusion, this football dataset offers a wealth of information, empowering users to explore diverse analyses and research ideas, bridging the gap between structured data and the dynamic world of football.

Tables

Club Games New

@kaggle.willianoliveiragibin_soccer_universe.club_games_new

4.37 MB
123,076 rows
2 columns

CREATE TABLE club_games_new (
  "game_id_club_id_own_goals_own_position_own_manager_nam_c86a4306" VARCHAR  -- Game Id,club Id,own Goals,own Position,own Manager Name,opponent Id,opponent Goals,opponent Position,opponent Manager Name,hosting,is Win,
  "unnamed_1" VARCHAR  -- Unnamed: 1
);

Clubs New

@kaggle.willianoliveiragibin_soccer_universe.clubs_new

35.54 kB
411 rows
2 columns

CREATE TABLE clubs_new (
  "club_id_club_code_name_domestic_competition_id_total_m_94fe1a60" VARCHAR  -- Club Id,club Code,name,domestic Competition Id,total Market Value,squad Size,average Age,foreigners Number,foreigners Percentage,national Team Players,stadium Name,stadium Seats,net Transfer Record,coach Name,last Season,url,
  "unnamed_1" VARCHAR  -- Unnamed: 1
);

Competitions New

@kaggle.willianoliveiragibin_soccer_universe.competitions_new

5.43 kB
43 rows
2 columns

CREATE TABLE competitions_new (
  "competition_id_competition_code_name_sub_type_type_cou_9226d3dc" VARCHAR  -- Competition Id,competition Code,name,sub Type,type,country Id,country Name,domestic League Code,confederation,url,
  "unnamed_1" VARCHAR  -- Unnamed: 1
);

Game Events New

@kaggle.willianoliveiragibin_soccer_universe.game_events_new

13.52 MB
559,962 rows
2 columns

CREATE TABLE game_events_new (
  "game_id_minute_type_club_id_player_id_description_player_in_id" VARCHAR,
  "unnamed_1" VARCHAR  -- Unnamed: 1
);

Games New

@kaggle.willianoliveiragibin_soccer_universe.games_new

6.63 MB
61,538 rows
2 columns

CREATE TABLE games_new (
  "game_id_competition_id_season_round_date_home_club_id__196af9e0" VARCHAR  -- Game Id,competition Id,season,round,date,home Club Id,away Club Id,home Club Goals,away Club Goals,home Club Position,away Club Position,home Club Manager Name,away Club Manager Name,stadium,attendance,referee,url,home Club Name,away Club Name,aggregate,competition Type,
  "unnamed_1" VARCHAR  -- Unnamed: 1
);

Players New

@kaggle.willianoliveiragibin_soccer_universe.players_new

3.51 MB
28,459 rows
2 columns

CREATE TABLE players_new (
  "player_id_first_name_last_name_name_last_season_curren_5c1a3db3" VARCHAR  -- Player Id,first Name,last Name,name,last Season,current Club Id,player Code,country Of Birth,city Of Birth,country Of Citizenship,date Of Birth,sub Position,position,foot,height In Cm,market Value In Eur,highest Market Value In Eur,contract Expiration Date,agent Name,image Url,url,current Club Domestic Competition Id,current Club Name,
  "unnamed_1" VARCHAR  -- Unnamed: 1
);

Player Valuations New

@kaggle.willianoliveiragibin_soccer_universe.player_valuations_new

7.39 MB
424,323 rows
2 columns

CREATE TABLE player_valuations_new (
  "player_id_last_season_datetime_date_dateweek_market_va_458de692" VARCHAR  -- Player Id,last Season,datetime,date,dateweek,market Value In Eur,n,current Club Id,player Club Domestic Competition Id,
  "unnamed_1" VARCHAR  -- Unnamed: 1
);