AIMC Topic: Athletic Performance
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Predicting badminton outcomes through machine learning and technical action frequencies.
Scientific reports
Mar 27, 2025
The application of machine learning techniques to predict badminton match outcomes through the analysis of technical actions seems to represent an area that has not yet been extensively investigated within the existing body of research. This study ai...
Investigating the increase in the specialized performance of athletes using artificial neural network (ANN) exercises.
Scientific reports
Mar 12, 2025
Badminton, a dynamic and fast-paced racket sport, demands a unique combination of physical, technical, and cognitive abilities from its players. This study investigates the impact of a tailored core strength training program on the specialized perfor...
Leveraging graph neural networks and gate recurrent units for accurate and transparent prediction of baseball pitching speed.
Scientific reports
Mar 5, 2025
Long short-term memory (LSTM) networks are widely used in biomechanical data analysis but have the significant limitations in interpretability and decision transparency. Combining graph neural networks (GNN) with gate recurrent units (GRU) may offer ...
Table tennis coaching system based on a multimodal large language model with a table tennis knowledge base.
PloS one
Feb 13, 2025
UNLABELLED: Table tennis is one of the most popular sports in the world, and it plays a positive role in the overall development of people's physical and mental health. This study develops an AI table tennis coaching system using a Multimodal Large L...
Subjective recovery in professional soccer players: A machine learning and mediation approach.
Journal of sports sciences
Feb 5, 2025
Coaches often ask players to judge their recovery status (subjective recovery). We aimed to explore potential determinants of subjective recovery in 101 male professional soccer players of 4 Italian Serie C teams and to further investigate whether th...
A machine learning model the prediction of athlete engagement based on cohesion, passion and mental toughness.
Scientific reports
Jan 25, 2025
Athlete engagement is influenced by several factors, including cohesion, passion and mental toughness. Machine learning methods are frequently employed to construct predictive models as a result of their high efficiency. In order to comprehend the ef...
Explainable quality assessment of effective aligned skeletal representations for martial arts movements by multi-machine learning decisions.
Scientific reports
Jan 2, 2025
How to utilize modern technological means to provide both accurate scoring and objective feedback for martial arts movements has become an issue that needs to be addressed in the field of physical education. This study proposes an intelligent scoring...
Empowering the Sports Scientist with Artificial Intelligence in Training, Performance, and Health Management.
Sensors (Basel, Switzerland)
Dec 29, 2024
Artificial Intelligence (AI) is transforming the field of sports science by providing unprecedented insights and tools that enhance training, performance, and health management. This work examines how AI is advancing the role of sports scientists, pa...
Assessing the effectiveness of fuzzy logic-based models for predicting sports event outcomes: A CRITIC-VIKOR approach.
PloS one
Dec 23, 2024
Incorporating fuzzy logic-based models into sports prediction has generated significant interest due to the intricate nature of athletic events and the many factors influencing their outcomes. This study evaluates the effectiveness of fuzzy logic-bas...
Prediction of talent selection in elite male youth soccer across 7 seasons: A machine-learning approach.
Journal of sports sciences
Dec 17, 2024
This study aimed to investigate the relative importance of parameters from several domains associated to both selecting or de-selecting players with regards to the next age group within a professional German youth soccer academy across a 7-year perio...
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