Guidelines for Applying Psychometrics in Sports Science: Transitioning from Traditional Methods to the AI Era




Psychometrics, Artificial Intelligence, Machine learning, Sports science, Assessment, Validity, Reliability


This study introduces a comprehensive set of guidelines for the application of psychometrics in sports science, with a specific focus on the transition from conventional methods to the Artificial Intelligence (AI) era. As advancements in technology reshape the landscape of sports performance assessment, there is a growing need to adapt psychometric practices to harness the potential of AI tools. The proposed guidelines encompass both theoretical frameworks and practical considerations, aiming to optimize the integration of psychometrics and AI for enhanced athlete evaluation and development. This research delineates key principles for selecting and implementing psychometric tools within the context of sports science, emphasizing the importance of data quality, reliability, and validity. Furthermore, it explores the ethical implications of utilizing AI-driven psychometrics in sports, addressing concerns related to privacy, bias, and transparency. By bridging the gap between traditional psychometric methods and emerging AI technologies, these guidelines provide a roadmap for researchers, coaches, and practitioners to navigate the evolving landscape of sports science, facilitating a seamless transition towards more robust and sophisticated assessment methodologies.

Graphical Abstract