SQL for Sports Analytics

SQL for Sports Data Analysis

SQL is the foundation of working with large sports databases. Whether querying Statcast data or building your own analytics database, SQL skills are essential.

Key SQL Concepts for Sports

Window Functions for Running Stats

Window functions are powerful for sports calculations:

• ROW_NUMBER(): Rankings within groups
• LAG()/LEAD(): Compare to previous/next games
• AVG() OVER: Rolling averages
• SUM() OVER: Cumulative stats

Performance Tips

• Index columns used in WHERE and JOIN clauses
• Use EXPLAIN to understand query plans
• Avoid SELECT * in production queries
• Pre-aggregate large tables into summary tables
• Partition tables by season/year for large datasets

Key Takeaways

• Window functions are essential for time-series sports data
• CTEs improve readability of complex queries
• Proper indexing is crucial for performance
• Design schemas around common query patterns
• Consider materialized views for expensive calculations