AIMC Topic: Soccer
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Enhancing Sports Injury Risk Assessment in Soccer Through Machine Learning and Training Load Analysis.
Journal of sports science & medicine
Sep 1, 2024
Sports injuries pose significant challenges in athlete welfare and team dynamics, particularly in high-intensity sports like soccer. This study used machine learning algorithms to assess non-contact injury risk in professional male soccer players fro...
Artificial intelligence applications in the football codes: A systematic review.
Journal of sports sciences
Aug 14, 2024
Artificial Intelligence (AI) is increasingly being adopted across many domains such as transport, healthcare, defence and sport, with football codes no exception. Though there is a range of potential benefits of AI, concern has also been expressed re...
Football Movement Profile-Based Creatine-Kinase Prediction Performs Similarly to Global Positioning System-Derived Machine Learning Models in National-Team Soccer Players.
International journal of sports physiology and performance
Jun 25, 2024
PURPOSE: The relationship between external load and creatine-kinase (CK) response at the team/position or individual level using Global Positioning Systems (GPS) has been studied. This study aimed to compare GPS-derived and Football Movement Profile ...
Application of Machine Learning Methods to Investigate Joint Load in Agility on the Football Field: Creating the Model, Part I.
Sensors (Basel, Switzerland)
Jun 5, 2024
Laboratory studies have limitations in screening for anterior cruciate ligament (ACL) injury risk due to their lack of ecological validity. Machine learning (ML) methods coupled with wearable sensors are state-of-art approaches for joint load estimat...
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...
Learning agile soccer skills for a bipedal robot with deep reinforcement learning.
Science robotics
Apr 10, 2024
We investigated whether deep reinforcement learning (deep RL) is able to synthesize sophisticated and safe movement skills for a low-cost, miniature humanoid robot that can be composed into complex behavioral strategies. We used deep RL to train a hu...
Association between match-related physical activity profiles and playing positions in different tasks: A data driven approach.
Journal of sports sciences
Apr 4, 2024
Assessing the intensity characteristics of specific soccer drills (matches, small-side game, and match-based exercises) could help practitioners to plan training sessions by providing the optimal stimulus for every player. In this paper, we propose a...
Predicting Soccer Players' Fitness Status Through a Machine-Learning Approach.
International journal of sports physiology and performance
Feb 24, 2024
PURPOSE: The study had 3 purposes: (1) to develop an index using machine-learning techniques to predict the fitness status of soccer players, (2) to explore the index's validity and its relationship with a submaximal run test (SMFT), and (3) to analy...
Relationship between external and internal load indicators and injury using machine learning in professional soccer: a systematic review and meta-analysis.
Research in sports medicine (Print)
Dec 26, 2023
This study verified the relationship between internal load (IL) and external load (EL) and their association on injury risk (IR) prediction considering machine learning (ML) approaches. Studies were included if: (1) participants were male professiona...
Prediction of defensive success in elite soccer using machine learning - Tactical analysis of defensive play using tracking data and explainable AI.
Science & medicine in football
Aug 4, 2023
The interest in sports performance analysis is rising and tracking data holds high potential for game analysis in team sports due to its accuracy and informative content. Together with machine learning approaches one can obtain deeper and more object...
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