Data Science

Soccer Player Performance Analysis

Exploratory data analysis to identify the highest-performing players across major soccer leagues using statistical metrics.

Problem

With hundreds of players across a league, identifying genuine top performers beyond just goals and assists requires a more holistic analytical lens that most fans and analysts don't have access to.

Solution

Performed comprehensive exploratory data analysis on league-wide player stats. Built visualizations to compare players across multiple performance dimensions, enabling clear identification of standout contributors at each position.

Impact

Produced a reusable analytical framework for evaluating player performance — applicable to any league or season — demonstrating practical data storytelling skills in a real-world sports context.

Technologies Used
PythonPandasMatplotlibSeabornJupyter
About This Project

A data analysis project focused on ranking and profiling top-performing soccer players within a specific league. It uses statistical aggregation and visualization techniques to surface standout performers across key metrics like goals, assists, passing accuracy, and defensive contributions.