AIMC Topic: Athletic Performance
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Predicting Basketball Shot Outcome From Visuomotor Control Data Using Explainable Machine Learning.
Journal of sport & exercise psychology
Sep 6, 2024
Quiet eye (QE), the visual fixation on a target before initiation of a critical action, is associated with improved performance. While QE is trainable, it is unclear whether QE can directly predict performance, which has implications for training int...
Using machine learning to determine the nationalities of the fastest 100-mile ultra-marathoners and identify top racing events.
PloS one
Aug 22, 2024
The present study intended to determine the nationality of the fastest 100-mile ultra-marathoners and the country/events where the fastest 100-mile races are held. A machine learning model based on the XG Boost algorithm was built to predict the runn...
Integration of machine learning XGBoost and SHAP models for NBA game outcome prediction and quantitative analysis methodology.
PloS one
Jul 23, 2024
This study investigated the application of artificial intelligence in real-time prediction of professional basketball games, identifying the variations within performance indicators that are critical in determining the outcomes of the games. Utilizin...
The role of morphometric characteristics in predicting 20-meter sprint performance through machine learning.
Scientific reports
Jul 18, 2024
The aim of this study was to test the morphometric features affecting 20-m sprint performance in children at the first level of primary education using machine learning (ML) algorithms. In this study, 130 male and 152 female volunteers aged between 6...
Identifying Key Training Load and Intensity Indicators in Ice Hockey Using Unsupervised Machine Learning.
Research quarterly for exercise and sport
Jul 3, 2024
To identify key training load (TL) and intensity indicators in ice hockey, practice, and game data were collected using a wearable 200-Hz accelerometer and heart rate (HR) recording throughout a four-week (29 days) competitive period (23 practice ses...
Measuring Vertical Jump Height With Artificial Intelligence Through a Cell Phone: A Validity and Reliability Report.
Journal of strength and conditioning research
Jul 2, 2024
Erik, HT, Onn, SW, and Montalvo, S. Vertical jump height with artificial intelligence through a cell phone: a validity and reliability report. J Strength Cond Res 38(9): e529-e533, 2024-This study estimated the reliability and validity of an artifici...
HoopTransformer: Advancing NBA Offensive Play Recognition with Self-Supervised Learning from Player Trajectories.
Sports medicine (Auckland, N.Z.)
May 30, 2024
BACKGROUND AND OBJECTIVE: Understanding and recognizing basketball offensive set plays, which involve intricate interactions between players, have always been regarded as challenging tasks for untrained humans, not to mention machines. In this study,...
Who are the best passing players in professional soccer? A machine learning approach for classifying passes with different levels of difficulty and discriminating the best passing players.
PloS one
May 30, 2024
The present study aimed to assess the use of technical-tactical variables and machine learning (ML) classifiers in the automatic classification of the passing difficulty (DP) level in soccer matches and to illustrate the use of the model with the bes...
Systematic training of table tennis players' physical performance based on artificial intelligence technology and data fusion of sensing devices.
SLAS technology
May 23, 2024
This research emphasises the value of physical training for table tennis players, particularly as ball speed and spin rate decline and emphasises how important intensity quality is to the game. Chinese table tennis players' dual identities place grea...
Artificial intelligence and Machine Learning approaches in sports: Concepts, applications, challenges, and future perspectives.
Brazilian journal of physical therapy
May 21, 2024
BACKGROUND: The development and application of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare have gained attention as a promising and powerful resource to change the landscape of healthcare. The potential of these technologies ...
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