Football players are often evaluated based only on goals scored, which does not fully reflect their overall contribution to the team. This project analyzes a FIFA 2026 dataset containing 72 player performance metrics using SQL to uncover deeper insights into player effectiveness.

The analysis identifies the most efficient attackers, strongest defensive players, top-performing goalkeepers, and teams that rely heavily on specific players. A custom Player Impact Score was also developed to provide a more comprehensive measure of player performance by combining multiple statistical indicators.

This project demonstrates how SQL-based data analytics can transform raw sports data into meaningful insights for player evaluation, scouting, and team strategy.

• SQL Server
• GitHub
• Kaggle FIFA Dataset

1. Efficient Attackers Analysis
2. Defensive Player Rankings
3. Goalkeeper Performance Analysis
4. Team Dependency Analysis
5. Player Impact Score

• 01_efficient_attackers.sql
• 02_defensive_players.sql
• 03_goalkeepers.sql
• 04_team_dependency.sql
• 05_player_impact_score.sql