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Courtside Catalyst

Built advanced analytics database to improve UMD basketball strategies supporting NCAA tournament success

DatabaseSports AnalyticsSQL

Role

Database Developer

Timeframe

March 2024

Team Size

4 developers and analysts

Tools & Technologies

SQLER DiagramsRelational Schemas

Key Impact

Identified top-performing players and optimized game strategies for NCAA tournament success

Context

UMD Men's Basketball needed deeper insights for performance and recruitment, with data being fragmented and underutilized.

Problem

Data was fragmented and underutilized, limiting strategic decisions for game planning and player recruitment.

Approach

  • Designed comprehensive ER Diagrams for basketball data modeling

  • Built relational schemas optimized for performance analytics

  • Executed advanced SQL queries to analyze player and team performance

  • Created reporting system for coaching staff and recruitment team

  • Implemented data validation and quality assurance processes

Outcome

  • Identified top-performing players through statistical analysis

  • Optimized game strategies based on data-driven insights

  • Supported NCAA tournament success with actionable analytics

  • Improved recruitment targeting through performance metrics

Next Steps

  • Extend system for real-time analytics during games

  • Integration with wearable IoT player tracking devices

  • Expand analytics to include opponent scouting and strategy

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