Recent advancements in professional baseball have led to the introduction of the Automated Ball-Strike (ABS) system, or "robot umpires," which utilize machine learning, computer vision, and precise tracking technologies to automate ball-strike calls....
This study investigated the acute effects of static (SS), dynamic (DS), and ballistic (BS) hamstring stretching on performance in male soccer players and applied machine learning (ML) to predict protocol efficacy. A total of 249 players with and with...
This study aims to analyze the key factors contributing to victories in world women's volleyball matches and predict match win rates using machine learning algorithms. Initially, Grey Relational Analysis (GRA) was employed to analyze the fundamental ...
Sports motion recognition is essential for performance analysis, injury prevention, and athlete monitoring. Traditional deep learning models, such as Long Short-Term Memory (LSTM) and Transformer-based architectures, struggle to capture motion dynami...
Analytical methods : advancing methods and applications
Oct 9, 2025
Non-invasive monitoring of lactate levels offers a promising avenue for optimizing athletic performance assessment, yet remains constrained by the limitations of traditional blood-based sampling methods. This review critically examines electrochemica...
The rapid development of internet of things, big data, and artificial intelligence is propelling sports science into a data-driven era, demanding real-time, multidimensional athletic performance monitoring. Triboelectric nanogenerators (TENGs) have d...
Because chess is played in formal tournaments and competitive environments, it requires physical and mental endurance. This endurance declines as the years progress and can decrease the player's performance. As the player's age increases, elements su...
This study aimed to verify and interpret a model for predicting the number of home runs per year using sensor data from professional baseball players during batting practice. A machine learning model was constructed using Random Forest from the bat k...
This study presents an Internet of Things (IoT)-enabled Deep Learning Monitoring (IoT-E-DLM) model for real-time Athletic Performance (AP) tracking and feedback in collegiate sports. The proposed work integrates advanced wearable sensor technologies ...
International journal of sports physiology and performance
Jul 22, 2025
PURPOSE: Preseason in football is crucial for optimizing physical fitness, team cohesion, and tactical readiness. This study investigated the effects of 2 distinct preseason training environments-mild altitude with cooler conditions and sea level wit...
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