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Tableau Projects

Welcome to my Tableau Projects repository. This collection highlights a variety of data visualization projects created using Tableau, focusing on different data sets and providing insights through interactive dashboards. Each project folder contains its own detailed README.md file with further information and instructions.


Projects

1. Scouting the Best Young Footballers Under 22

This project analyzes data from SoFIFA (2022) to scout young footballers under the age of 22, with a focus on strikers. The dashboard visualizes key performance metrics such as attacking finishing, dribbling, acceleration, and shot power. Interactive filters allow users to explore players based on contract details, market value, wages, and more. This visualization aims to help football scouts and analysts assess potential top talents.

View the live dashboard


2. UEFA Champions League Dashboard

This project visualizes key statistics from the UEFA Champions League, focusing on top players, coaches, and clubs over the years. The dashboard provides insights into player appearances, goal records, top clubs by games played and goals scored, and other significant records. It also includes a map showing UEFA titles won by clubs from different countries. This dashboard is designed to provide a comprehensive overview of the top performers in the Champions League era.

View the live dashboard


How to Use This Repository

  1. Explore Projects: Each project has its own folder with a dedicated README.md file explaining the data source, methodology, and key insights from the Tableau dashboards.
  2. View Dashboards: Use the provided Tableau Public links to explore the live dashboards, interact with the data, and apply filters.
  3. Download Tableau Files: If you'd like to dive deeper into the analysis, you can download the .twb or .twbx files and open them in Tableau Desktop.

Credits


Note: These projects were created as part of my journey to learn Tableau, with a focus on applying data visualization techniques to football-related data sets.