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Historical International Football Data
Sports & Recreation
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About
This dataset offers an overview of international football (soccer) matches played between 1993 and 2022, culminating in the lead-up to the FIFA World Cup 2022 in Qatar. The FIFA World Cup is the globe's most prestigious football tournament, held every four years since 1930, involving a qualification phase and a tournament with 32 competing teams. France currently holds the title from the 2018 tournament [1, 2].
The dataset incorporates team strength metrics, using actual FIFA rankings and player strengths derived from the EA Sport FIFA video game [2]. It was updated on 28th August 2022 [2]. This dataset is ideal for predicting match outcomes, analysing team strengths, understanding home team advantage, and investigating the correlation between player attributes and match results [2, 3].
Columns
The dataset contains 25 columns, providing detailed information on each match:
- date: The date when the match was played [4].
- home_team: The name of the team playing at home [5].
- away_team: The name of the visiting team [5].
- home_team_continent: The continent of the home team [5].
- away_team_continent: The continent of the away team [6].
- home_team_fifa_rank: The FIFA ranking of the home team at the time of the match [6].
- away_team_fifa_rank: The FIFA ranking of the away team at the time of the match [7].
- home_team_total_fifa_points: The total FIFA points accumulated by the home team at the time of the match [8].
- away_team_total_fifa_points: The total FIFA points accumulated by the away team at the time of the match [9].
- home_team_score: The home team's full-time score, including any extra time, but excluding penalty-shootouts [10].
- away_team_score: The away team's full-time score, including any extra time, but excluding penalty-shootouts [11].
- tournament: The name of the tournament in which the match was played [12].
- city: The name of the city, town, or administrative unit where the match took place [12].
- country: The name of the country where the match was played [13].
- neutral_location: A boolean indicating whether the match was played at a neutral venue (TRUE/FALSE) [13].
- shoot_out: A boolean indicating whether the match included a penalty shootout (TRUE/FALSE) [14].
- home_team_result: The match result for the home team, including penalty-shootouts (Win, Lose, Draw) [14].
- home_team_goalkeeper_score: The FIFA game score of the highest-ranked goalkeeper of the home team [15].
- away_team_goalkeeper_score: The FIFA game score of the highest-ranked goalkeeper of the away team [15].
- home_team_mean_defense_score: The average FIFA game score of the four highest-ranked defensive players of the home team [15].
- home_team_mean_offense_score: The average FIFA game score of the four highest-ranked midfield players of the home team [16].
- home_team_mean_midfield_score: The average FIFA game score of the three highest-ranked attacking players of the home team, including wing players [16].
- away_team_mean_defense_score: The average FIFA game score of the four highest-ranked defensive players of the away team [17].
- away_team_mean_offense_score: The average FIFA game score of the four highest-ranked midfield players of the away team [17].
- away_team_mean_midfield_score: The average FIFA game score of the three highest-ranked attacking players of the away team, including wing players [18].
Distribution
The data file is typically provided in a CSV format [4, 19]. It contains 25 columns and has approximately 23,900 records [4, 5]. The matches span a date range from 8th August 1993 to 14th June 2022 [20]. While core match details are entirely present, certain FIFA game score attributes, such as goalkeeper, defense, offense, and midfield scores, have a notable percentage of missing values (e.g., around 65-68% missing) [15-18].
Usage
This dataset is well-suited for various analytical applications and use cases, including:
- Predictive modelling to forecast the likely winner of football tournaments, such as the 2022 FIFA World Cup [2].
- In-depth analysis of team strengths, breaking down performance by defense, midfield, and offense [3].
- Investigating the presence and impact of a home team advantage [3].
- Exploring the relationship between player strengths (e.g., offense players, goalkeepers) and the number of goals scored or conceded [3].
- Identifying and analysing teams with the longest winning streaks [3].
- Explaining instances where weaker teams achieve victories against stronger opponents [3].
Coverage
The dataset covers international soccer matches played globally between August 1993 and June 2022 [1, 20]. It includes matches from various cities and countries worldwide, with team continents also specified [5, 6, 12, 13]. The FIFA rankings are included up to June 2018 from one source, with more recent rankings scraped from the FIFA website. Player strength data from EA Sport FIFA game versions 15-22 are included, with older versions and FIFA 23 data scraped from other football statistics websites [3, 4].
License
CC0: Public Domain
Who Can Use It
This dataset is intended for a broad audience interested in football analytics, including:
- Data Scientists and Machine Learning Engineers for building predictive models for match outcomes.
- Sports Analysts and Statisticians for in-depth performance evaluation of teams and players.
- Researchers studying trends in international football, home advantage, or team dynamics.
- Football Enthusiasts and Journalists for gaining insights and data-driven perspectives on the sport.
Dataset Name Suggestions
- International Football Match Statistics 1993-2022
- Global Soccer Matches and Team Strengths
- FIFA World Cup Era Match Data
- Football Performance Analysis Dataset
- Historical International Football Data
Attributes
Original Data Source: Historical International Football Data
QUALITY