• Description/Objectives
  • Methods – Python/R Studio
  • Code + Visuals


As a soccer fan, I was intrigued by the 2020-2021 season as it was a very thrilling one. Hence, I decided to analyze the player’s performance as well as some interesting data points which I considered could bring value to the reader. Though this is a very generic statistical analysis, I’m working on developing further this model through Jupyter Notebooks.


For the study of the dataset I used Jupyter Notebook to code by combining Python and R scripts.

*Datset provided by the English Premier League Data Science Association

#Let’s start by importing the necessary python packages

#We’ll read the csv document to visualize the data points

#Let’s dive into the first question… Who were the Top 10 Goal Kings of last season?

#Based on the results, Harry Kane (Tottenham) was deemed “Goal King of the season” with a total of 23 goals. There was a 10 goal difference between him and Alexandre Lacazette (Arsenal), 10th player on the run for the award.

#Now that we have the top goalscorers… Who were the top assistants of the season?

#According to graph above, the Assist King of the season is Harry Kane (Tottenham) with 14 assists. Kevin De Bruyne (Manchester City) and Bruno Fernandes (Manchester United) followed him with 12 assists.

Harry Kane is both the Goal King and Assist King of this season.

#Let’s study the amount of goals scored by each team last season

Manchester City was the leading team when it came to scoring goals this season, a great factor on their journey to conquer the 2020-2021 League Trophy

#Let’s do the same for assists now

Manchester City was the leading team in assists as well as goals.

#Now that offensive stats have been covered, let’s discuss defensive matters… Who were the defensive players that accumulated more red cards last season?

Lewis Dunk (Brighton) is the DF player who had the most amount of red cards on the 20-21 season, with a total of 2, followed by 7 yellow cards

#Now that we counted red cards, let’s do the same with yellow cards

Harry Maguire (Manchester United) is the player who has the most yellow cards of this season. With more than 10 yellow cards.

#Now that we know individual players cards, let’s study the averages correlated with players nationalities

It looks like the players originally from Mali are the ones that accumulated more cards last season

#Now, let’s take a look on the diversity of the league and study what are the most repeated nationalities in the league

We find a total of 58 total countries represented, being England (192 players), France (31) and Brasil (27) the countries that export more players to the league

#Let’s dive on the player’s age, and see who are the oldest players in the league

Willy Cabarello (Chelsea) was the oldest player of this season. It’s important to remark that his role as a goalkeeper was of a bench player for this year’s Champions League winners, Chelsea.

#Who are the players that attempt the most amount of passes per season?

Andrew Robertson (Liverpool) was the player with the most passes attempted, with a total of 3200. He was followed by his fellow teammate Trent Alexander-Arnold (Liverpool)whom attempted 2900 passes

#Now that we know the passing attempt, let’s discover the percentage of passes completed successfully

Here’s the top 25 of players with the highest percentages of passes successfully completed through out the season. Although the yellow-graph players have perfect percentages, we would have to further study the amount of games played compared to the rest of the players ranked.

#Let’s visualize density plots in order to study the relationship between games and players starting them

#Diving further into visuals, let’s study the highest penalty attempt-goal ratios of the league

The players in yellow are the ones with perfect ratios of attempt-goal, meaning that they’ve scored every chance they took of scoring a goal

#Finally, let’s prepare a correlation graph of the dataset

This has been an extensive study of the 2020-2021 premier league season through statistics, the project has allowed me to understand better the performance of the players and enhance my python skills to provide visualization of statistics to football lovers.

-Alfredo S.

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