EPL Dataset 2022/2023 (Update Every Week)
Weekly Updated 2022/2023 Premier League Dataset
@kaggle.acothaha_epl_dataset_20222023_update_every_week
Weekly Updated 2022/2023 Premier League Dataset
@kaggle.acothaha_epl_dataset_20222023_update_every_week
The Premier League (legal name: The Football Association Premier League Limited) is the highest level of the men's English football league system. Contested by 20 clubs, it operates on a system of promotion and relegation with the English Football League (EFL). Seasons typically run from August to May with each team playing 38 matches (playing all 19 other teams both home and away). Most games are played on Saturday and Sunday afternoons, with occasional weekday evening fixtures. (Wikipedia)
Arguably, English Premier League is the biggest football league on earth. It is home to some of the most successful and popular Football teams, including Manchester United, Liverpool, Arsenal and Chelsea. The league is known for its high level of competition and attracts top talent from around the globe. In addition, the Premier League has a huge following, with with an astounding broadcast in 212 territories to 643 million homes and a potential TV audience of 4.7 billion
This dataset is collected using webscraping from several websites (mainly premierleague.com) and currently there are 2 files that you can utilize:
EPL_2022_2023_(date).json
This dataset contains the information of every match in EPL 2022/2023 so far
match_id
: The unique match id for each matchevent
: the events (commentary) while the match is happeningmatchweek
: the matchweek of the matchteam1_name
: The home team nameteam1_startings
: The home starting 11team1_subs
: The home team subtitution playersteam1_stat
: The home team statistics (Possession%, Shots on target, Shots, Touches, Passes, Tackles, Clearences, Corners, Offsides, Yellow cards, Foul conceded)team2_name
: The away team nameteam2_startings
: The away starting 11team2_subs
: The away team subtitution playersteam2_stat
: The away team statistics (Possession%, Shots on target, Shots, Touches, Passes, Tackles, Clearences, Corners, Offsides, Yellow cards, Foul conceded)player_info.csv
This dataset contains the information of each player in EPL 2022/2023
player_name
: The name of the playerteam
: The team that the player play inbirthday
: The date of birth of the playerposition
: The position of the playerThis dataset is inspired by the film "Moneyball" which make me want to build a dataset that can be utilized to do a football analytics by looking at several information especially the event (Commentary) and one thing that I can provide to you my fellow data enthusiasts is the weekly update of the dataset which happens (hopefully) every monday.
Please feel free to give feedback on the dataset, what can be improved, what data should be added, etc.
CREATE TABLE player_info (
"unnamed_0" BIGINT -- Unnamed: 0,
"player_name" VARCHAR,
"team" VARCHAR,
"birthday" TIMESTAMP,
"position" VARCHAR
);
Anyone who has the link will be able to view this.