Data
International-football-results

International-football-results

active ARFF CC0: Public Domain Visibility: public Uploaded 24-03-2022 by Elif Ceren Gok
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Context Well, what happened was that I was looking for a semi-definite easy-to-read list of international football matches and couldn't find anything decent. So I took it upon myself to collect it for my own use. I might as well share it. Content This dataset includes 41,586 results of international football matches starting from the very first official match in 1972 up to 2019. The matches range from FIFA World Cup to FIFI Wild Cup to regular friendly matches. The matches are strictly men's full internationals and the data does not include Olympic Games or matches where at least one of the teams was the nation's B-team, U-23 or a league select team. results.csv includes the following columns: date - date of the match hometeam - the name of the home team awayteam - the name of the away team homescore - full-time home team score including extra time, not including penalty-shootouts awayscore - full-time away team score including extra time, not including penalty-shootouts tournament - the name of the tournament city - the name of the city/town/administrative unit where the match was played country - the name of the country where the match was played neutral - TRUE/FALSE column indicating whether the match was played at a neutral venue Note on team and country names: For home and away teams the current name of the team has been used. For example, when in 1882 a team who called themselves Ireland played against England, in this dataset, it is called Northern Ireland because the current team of Northern Ireland is the successor of the 1882 Ireland team. This is done so it is easier to track the history and statistics of teams. For country names, the name of the country at the time of the match is used. So when Ghana played in Accra, Gold Coast in the 1950s, even though the names of the home team and the country don't match, it was a home match for Ghana. This is indicated by the neutral column, which says FALSE for those matches, meaning it was not at a neutral venue. Acknowledgements The data is gathered from several sources including but not limited to Wikipedia, fifa.com, rsssf.com and individual football associations' websites. Inspiration Some directions to take when exploring the data: Who is the best team of all time Which teams dominated different eras of football What trends have there been in international football throughout the ages - home advantage, total goals scored, distribution of teams' strength etc Can we say anything about geopolitics from football fixtures - how has the number of countries changed, which teams like to play each other Which countries host the most matches where they themselves are not participating in How much, if at all, does hosting a major tournament help a country's chances in the tournament Which teams are the most active in playing friendlies and friendly tournaments - does it help or hurt them The world's your oyster, my friend. Contribute If you notice a mistake or the results are being updated fast enough for your liking, you can fix that by submitting a pull request.

9 features

datestring15196 unique values
0 missing
home_teamstring308 unique values
0 missing
away_teamstring305 unique values
0 missing
home_scorenumeric26 unique values
0 missing
away_scorenumeric22 unique values
0 missing
tournamentstring112 unique values
0 missing
citystring2011 unique values
0 missing
countrystring266 unique values
0 missing
neutralnominal2 unique values
0 missing

19 properties

41586
Number of instances (rows) of the dataset.
9
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
2
Number of numeric attributes.
1
Number of nominal attributes.
11.11
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
Average class difference between consecutive instances.
22.22
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
11.11
Percentage of nominal attributes.
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
1
Number of binary attributes.

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