Designing a Data-Driven Athlete Management System for Optimizing Basketball Performance

Abstract

The growing dependency on data-based decision-making in sports has driven the use of Athlete ManagementAthlete management Systems (AMS) to improve basketballBasketball strategy. This chapter highlights the significance of structured data management for tracking player performance, training loadTraining load, recoveryRecovery metrics, and game statistics by leveraging relational databases. AMS enables efficient data storage, retrieval, and analysis, providing coaches with actionable insights. The case study illustrates the use of wearable technologyWearable technology, including WHOOP straps and the Polar Team Pro system, to monitor sleep, heart rate variabilityHeart Rate Variability (HRV), training loadTraining load, and game performanceGame performance. Data from Short RecoveryRecovery Short Stress (SRSS) questionnaires and vertical jump assessments were incorporated into AMS to assess athlete readiness and injury risk. An efficient AMS design in collegiate basketballBasketball showcases applications in injury preventionInjury prevention, training optimization, and real-time game strategy. Future trends, such as AI-powered scouting, blockchain-based data security, and real-time wearable integration, emphasize AMS’s growing role in modern basketballBasketball and sports analyticsSports analytics. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.