International journal of sports physiology and performance
Jun 1, 2025
PURPOSE: Accurately predicting the distance covered by athletes during indoor sport activities without the use of GPS (global positioning systems) presents a significant challenge. This study evaluates the effectiveness of various machine-learning te...
The Purpose of this study is to propose a new integrative framework for athletic performance prediction based on state-of-the-art machine learning analysis and biometric data biometric scanning. By merging physiological signals i.e., Heart rate varia...
This study aims to utilize male blood metabolite signatures for (i) distinguishing between healthy individuals and athletes, thereby optimizing the athlete screening process; and (ii) predicting athletic performance in 100, 200, and 400 m sprints, en...
The present study aimed to explore the validity and inter-device reliability of a novel artificial intelligence app (Asstrapp) for real-time measurement of the traditional (tra505) and modified-505 (mod505) change of direction (COD) tests. Twenty-fiv...
This paper proposes a neural network based on the Markov probability transition matrix to predict the training performance of football athletes. Firstly, seven training indicators affecting the training performance are designed by the Event-group tra...
This study aims to investigate the dynamics of basketball game pace and its influence on game outcomes through a novel intra-game segmentation approach. By employing K-means clustering on possession duration, we categorized possessions from 1,141 NBA...
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2024
BACKGROUND: The Ultimate Fighting Championship (UFC) stands as a prominent global platform for professional mixed martial arts, captivating audiences worldwide. With its continuous growth and globalization efforts, UFC events have garnered significan...
Medicine and science in sports and exercise
Aug 1, 2020
PURPOSE: To assess injury risk in elite-level youth football (soccer) players based on anthropometric, motor coordination and physical performance measures with a machine learning model.
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