DS 4320 Project 2: Projecting Soccer Player Performance Using a Document Model

This project builds a document-based secondary dataset using soccer player statistics from the 2025–2026 top five European leagues. The dataset was cleaned, transformed, and stored in MongoDB using a document model where each document represents a player and their performance statistics. Using Python, MongoDB, and machine learning, the project analyzes player performance patterns across forwards, midfielders, and defenders using per-90 metrics that allow fairer comparisons between players with different playing times. The project includes:- MongoDB document database- Data processing pipeline- Feature engineering- Visualizations- Random Forest classification model- Publication-quality figures- Metadata and documentation