Euro 2024 Player Analysis

This project is a comprehensive analysis of player statistics from the Euro 2024 tournament. It was completed as a final project for a Data Analyst course at John Bryce College.

Project Overview

The objective of this project is to provide an in-depth analysis of player data from the Euro 2024 tournament. The analysis focuses on various aspects such as player performance, market value, player attributes, and positional data. Through this project, we aim to uncover insights about player characteristics, team compositions, and overall trends within the tournament.

Data

The data used in this project was sourced from Kaggle and includes a file named euro2024_players.xlsx which contains detailed player statistics for the Euro 2024 tournament.

Analysis and Visualizations

Below are some of the key questions analyzed in this project with corresponding visualizations:

• Relationship Between Caps and Goals
  Analyzing the relationship between the number of appearances (caps) and goals scored by players across different positions.

  

• Distribution of Players by Dominant Foot
  This pie chart shows the distribution of players based on their dominant foot (right, left, or both).

  

• Violin Plot of Player Heights by Position
  The violin plot represents the distribution of player heights across different positions.

  

• Distribution of Player Ages
  This histogram depicts the age distribution of players, with an overlay of the normal distribution curve to illustrate the spread and central tendency.

  

• Top 10 Clubs by Market Value
  A bar chart displaying the top 10 clubs with the highest market value based on the players participating in Euro 2024.

  

• Top 10 Players by Market Value
  This chart shows the top 10 players by market value.

  

• Average Market Value by Position, Club, and Country
  A comparative analysis of the average market value segmented by player position, club, and country.

  

• Top 10 Clubs with Most Players in the Tournament
  Bar chart showing the top 10 clubs with the most players participating in the tournament.

  

• Correlation Matrix of Player Attributes
  A heatmap displaying the correlation between various player attributes like age, market value, caps, and goals.

  

How to Run

To run the analysis, you can open the Jupyter notebook file named Euro2024_Player_Analysis.ipynb included in this repository. Make sure you have the necessary Python libraries installed:

• pandas
• matplotlib
• seaborn

You can install these using pip:

pip install pandas matplotlib seaborn