Editorial on the Research Topic New technologies and statistical models applied to sports and exercise science research: methodological, technical and practical considerations With new technology and sophisticated statistical models, sports and exercise research has seen a tremendous revolution in recent years. These ground-breaking technologies have altered how researchers approach data collecting, processing, and interpretation by offering deeper insights into numerous elements of human performance, training, and injury prevention (1, 2). This special issue examined the methodological, technical, and practical aspects involved in using these advanced tools and statistical models in sports and exercise science studies.Technology developments have significantly influenced the study of sports and exercise. Researchers today have an unmatched capacity to acquire and evaluate data in real-time and in ecologically realistic settings because of wearable technology, sensor technologies, virtual reality, and machine learning algorithms (3-5). In addition to improving the precision and accuracy of data gathering, these technologies have created new opportunities for researching intricate physiological, biomechanical, and psychological phenomena in exercise and sport. By adding these technologies to their research processes, scientists may acquire thorough and objective measurements, leading to more reliable discoveries and useful applications (1, 2).However, using these new technologies has its own unique set of methodological difficulties. The proper choice and positioning of sensors, the verification and dependability of measurements, and the fusion of many data streams are all important considerations for researchers. Additionally, they must solve problems with data management, data processing, and result interpretation. Insights and best practices were provided for researchers looking to incorporate new technology into their studies in this special issue, which investigated these methodological issues. Another essential component TYPE