Game Performance Analysis Using SQL

This project focuses on analyzing player performance and game progression using SQL. The dataset consists of two tables: Player_Details, which stores player information and level statuses, and Level_Details, which records in-game activity such as stages crossed, difficulty level, scores, and kill counts.

Key analyses include:

Extracting player details at different levels and difficulty settings.

Computing average kill counts and cumulative statistics.

Ranking top scores for each device and difficulty level.

Tracking player login history and cumulative gameplay metrics.

This analysis provides insights into player behavior, game difficulty progression, and performance trends to enhance game design and user engagement.