Premier League SQL Analytics
SQL-based data analytics exploring team and player performance in the 2023–24 English Premier League.
Project Snapshot
Built a fully normalized SQL database from 2023–2024 Premier League player and team statistics. Conducted advanced analytical queries to identify key performance indicators and their correlation with final league standings, successfully predicting the next season's champion.
Problem
Understanding which statistical factors most strongly predict team success in professional football requires structured data modeling and rigorous analytical queries across multiple data dimensions.
Approach
- Designed and built a fully normalized relational database schema
- Loaded 2023–2024 EPL player-level and team-level statistics
- Wrote advanced SQL queries for correlation analysis, aggregation, and ranking
- Identified key performance indicators: offensive productivity, team ratings, possession, and xG metrics
Tech Stack
SQL, Oracle Database
Results
- Strong correlations (r ≈ 0.6) found between offensive productivity, possession/xG metrics, and final league rankings
- Top-ranked team by the model matched the actual next-season league champion
- Demonstrated the power of structured SQL analytics for sports data