Datasets:
license: mit
task_categories:
- text-classification
language:
- en
tags:
- football
- classification
size_categories:
- 10K<n<100K
The ID column links tables in X_train, with Y_train and Y_train_supp. The same holds true for the test data.
Input team data sets comprise the following 3 identifier columns:
ID, LEAGUE and TEAM_NAME (note that LEAGUE and TEAM_NAME are not included in the test data) The following 25 statistics, which are aggregated by sum, average and standard deviation.
'TEAM_ATTACKS' 'TEAM_BALL_POSSESSION' 'TEAM_BALL_SAFE' 'TEAM_CORNERS' 'TEAM_DANGEROUS_ATTACKS' 'TEAM_FOULS' 'TEAM_GAME_DRAW' 'TEAM_GAME_LOST' 'TEAM_GAME_WON' 'TEAM_GOALS' 'TEAM_INJURIES' 'TEAM_OFFSIDES' 'TEAM_PASSES' 'TEAM_PENALTIES' 'TEAM_REDCARDS' 'TEAM_SAVES' 'TEAM_SHOTS_INSIDEBOX' 'TEAM_SHOTS_OFF_TARGET' 'TEAM_SHOTS_ON_TARGET', 'TEAM_SHOTS_OUTSIDEBOX' 'TEAM_SHOTS_TOTAL' 'TEAM_SUBSTITUTIONS' 'TEAM_SUCCESSFUL_PASSES' 'TEAM_SUCCESSFUL_PASSES_PERCENTAGE' 'TEAM_YELLOWCARDS' Input player data sets comprise the following 3 identifier columns:
ID, LEAGUE and TEAM_NAME, POSITION and PLAYER_NAME (note that LEAGUE, TEAM_NAME, and PLAYER_NAME are not included in the test data) 52 statistics, which are aggregated by sum, average and standard deviation. They are similar to the team statistics though more fine-grained.