Bibliometric Mapping Research of Basketball Training Base on Age Classification and Talent Identification (2015 –2025)

Abstract

The aims of this study are to: (1) map research productivity on basketball training based on age classification and talent identification from 2015 to 2025; (2) identify the most highly cited researchers; (3) analyze keyword occurrence patterns; and (4) determine solutions to existing limitations and future research prospects in this field. Using a bibliometric analysis approach, the study employs scopus data with the keywords ‘basketball training age classification’ and ‘talent identification – limited to basketball’, covering the years 2015 – 2025. Data analysis was conducted using VOS viewer. The findings show a notable increase in research growth by 2025. Studies from 2015 – 2019 continue to serve as a strong theoretical foundation, particularly regarding the relative age effect (RAE), maturation, anthropometry, and performance. Recent research trends highlight multidimensional approaches involving anthropometric, biomotor, technical, tactical, and AI-based technologies such as machine learning and neural networks. Keyword patterns indicate a shift from basic characteristic analysis toward data-driven predictive approaches. Scientific collaboration reveals strong integration between Indonesian and international researchers, supporting the development of modern talent identification models based on athlete age classification.