LaLiga 2019-2020 Season Player Stats
seaborn
python
matplotlib
histogram
scatterplot
barplot
countplot
violinplot
distributions
This Dataset contains information about 556 players in LaLiga during the 2019-2020 season. This dataset is from Prabhat on Kaggle and it can be used for Learning about Seaborn and basic statistical interpretations.
Motivation
This dataset is from Prabhat on Kaggle and it describes the different stats among players in LaLiga during the 2019-2020 season. With this dataset people can practice their Seaborn skills and interpretation skills with soccer data.
Data
Each row represents a player from LaLiga during the 2019-2020 Season. There are 556 rows. There are about 30 missing jersey numbers for different players. This may be due to changing teams and having multiple numbers.
Variable | Description |
---|---|
Team | Football club the player represents |
Position | Playing position (e.g., Goalkeeper, Defender) |
Shirt number | Squad shirt number |
Name | Name of the player |
Minutes played | Total minutes played |
Games played | Number of games played |
Percentage of games played | Percentage of total games the player appeared in |
Full games played | Games in which the player played the full 90 minutes |
Percentage of full games played | Percentage of full 90-minute games played |
Games started | Number of games started |
Percentage of games started | Percentage of games started out of total games |
Games where substituted | Number of games in which the player was substituted |
Percentage of games where substituted | Percentage of games in which the player was substituted |
Yellow Cards | Number of yellow cards received |
Red Cards | Number of red cards received |
Second Yellows | Number of second yellow cards (leading to red) |
Goals scored | Total goals scored |
Penalties scored | Penalty goals scored |
Own goals | Goals scored against own team |
Goals conceded while player on pitch | Goals conceded while the player was on the field |
Tackles | Total tackles attempted |
Interceptions | Interceptions made by the player |
Recoveries | Ball recoveries made |
Clearances | Number of clearances made |
Successful tackles | Number of successful tackles |
Unssuccessful tackles | Number of unsuccessful tackles |
Last man | Last-man tackles made |
Successful duels | Ground and aerial duels won |
Duels lost | Ground and aerial duels lost |
Successful aerial challenges | Aerial duels won |
Unsuccessful aerial challenges | Aerial duels lost |
Offsides | Times caught offside |
Fouls suffered | Times fouled by opponents |
Fouls committed | Fouls committed by the player |
Penalties won | Penalties won by the player |
Penalties given away | Penalties conceded by the player |
Handballs committed | Handball offenses committed |
Fouls committed per card | Ratio of fouls per card received |
Shots | Total shots taken |
Shots on target | Shots that were on target |
Assists | Total assists made |
Successful dribbles | Successful take-ons or dribbles |
Unsuccessful dribbles | Failed dribbles |
Goals scored.1 | Duplicate of “Goals scored” |
From inside the area | Goals scored from inside the penalty area |
From outside the area | Goals scored from outside the penalty area |
Goals with left foot | Goals scored with the left foot |
Goals with right foot | Goals scored with the right foot |
Penalties scored.1 | Duplicate of “Penalties scored” |
Goals scored with header | Goals scored using the head |
Goals from set piece | Goals scored from set plays |
Crosses | Crosses attempted |
Corners | Corner kicks taken |
Tackles.1 | Possibly duplicated or special category of tackles |
Duels | Total number of duels |
Man-to-man duels | Man-marking or direct player duels |
Aerial duels | Aerial challenges attempted |
Passes | Total passes attempted |
Short passes | Short-distance passes attempted |
Long passes | Long-distance passes attempted |
Through balls | Total through balls played |
Goals scored per attempt | Scoring efficiency (goals per shot) |
Questions
Interpreting Histograms, Bargraphs, Scatterplots, Countplots, and Violinplots
Using Seaborn in Python
Examining correlations and distributions
References
https://www.kaggle.com/datasets/thegreatcoder/laliga-player-stats?resource=download