### 5.1 Performance Posture The **ittf_player_info** table (37,620 rows) currently operates without dedicated indexing or search optimization, creating friction for the most common query pattern in sports data: name-based player lookup. With nearly 38,000 athlete records, linear scans of the Name column will degrade noticeably as concurrent users search for players during tournaments, rankings updates, or historical analysis. The single-table architecture is structurally sound but lacks the performance tuning necessary to support real-time search workloads at scale. ### 5.2 Key Optimizations | Target | Optimization Type | Recommendation | Strength | |--------|-------------------|----------------|----------| | ittf_player_info.Name | Text Search | keyword | High | Implementing keyword indexing on the **Name** column will deliver sub-second player lookups regardless of dataset growth, directly improving user experience for coaches, analysts, and tournament organizers who rely on rapid athlete identification. This optimization becomes critical during live events when hundreds of simultaneous queries hit the system—transforming a potential bottleneck into a competitive advantage for any platform serving table tennis stakeholders.