European Soccer Data Analysis using SQL & Python

A comprehensive data analytics project focused on the European Soccer Database, aiming to extract data-driven insights regarding team performances and player attributes across multiple seasons.

Key Technical Achievements:

Advanced SQL Queries: Developed complex queries using Joins, CTEs, and Window Functions to integrate data from over 25,000 matches and 10,000 players.

Match Classification: Leveraged CASE statements to automatically classify match results (Win, Loss, Draw) and calculate goal differences.

Scouting System: Designed a scouting report to identify high-potential players and those with the most significant rating improvements over time.

Data Processing: Performed data cleaning and statistical analysis using Python (Pandas) to ensure the accuracy of extracted insights.

Outcome: Successfully transformed raw database records into actionable statistical reports, showcasing trends in European football and player development.