<![CDATA[Background: Conventional badminton performance analysis primarily relies on manual observation and recording, making the process time-consuming, subjective, and unable to provide immediate feedback for evidence-based coaching. These limitations reduce the efficiency of training evaluation, particularly for beginner athletes. Aims: This study aimed to develop and validate an Android-based data-driven badminton performance analysis application featuring real-time tagging and performance visualization to improve the efficiency and objectivity of coaching practices. Method: A Research and Development (R&D) approach employing the ADDIE model was adopted. The application was validated by three experts in badminton, educational technology, and sports coaching, followed by field testing involving 30 beginner badminton athletes. User acceptance was evaluated using the Technology Acceptance Model (TAM), while effectiveness was determined by comparing application-based and conventional performance analysis methods. Results: The application achieved excellent validity with an expert agreement score of 1.00 and a reliability coefficient of 1.000. Field testing revealed a significant improvement in performance analysis compared with conventional methods (t = 51.95 > 2.00), indicating greater efficiency, objectivity, and accuracy in processing performance data. Conclusion: The developed application is highly valid, practical, and effective, providing an accessible digital solution that supports objective, data-driven badminton performance analysis for beginner athletes.]]>
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