AIMC Topic: Soccer

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Artificial neural networks' estimations of lower-limb kinetics in sidestepping: Comparison of full-body vs. lower-body landmark sets.

Journal of biomechanics
Artificial neural networks (ANNs) offers potential for obtaining kinetics in non-laboratory. This study compared the estimation performance for ground reaction forces (GRF) and lower-limb joint moments during sidestepping between ANNs fed with full-b...

Use of AI methods to assessment of lower limb peak torque in deaf and hearing football players group.

Acta of bioengineering and biomechanics
Monitoring and assessing the level of lower limb motor skills using the Biodex System plays an important role in the training of football players and in post-traumatic rehabilitation. The aim of this study was to build and test an artificial intelli...

Predicting noncontact injuries of professional football players using machine learning.

PloS one
Noncontact injuries are prevalent among professional football players. Yet, most research on this topic is retrospective, focusing solely on statistical correlations between Global Positioning System (GPS) metrics and injury occurrence, overlooking t...

High specificity of an AI-powered framework in cross-checking male professional football anterior cruciate ligament tear reports in public databases.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: While public databases like Transfermarkt provide valuable data for assessing the impact of anterior cruciate ligament (ACL) injuries in professional footballers, they require robust verification methods due to accuracy concerns. We hypothes...

Prediction of talent selection in elite male youth soccer across 7 seasons: A machine-learning approach.

Journal of sports sciences
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...

An Educational Review on Machine Learning: A SWOT Analysis for Implementing Machine Learning Techniques in Football.

International journal of sports physiology and performance
PURPOSE: The abundance of data in football presents both opportunities and challenges for decision making. Consequently, this review has 2 primary objectives: first, to provide practitioners with a concise overview of the characteristics of machine-l...

Prediction of Perceived Exertion Ratings in National Level Soccer Players Using Wearable Sensor Data and Machine Learning Techniques.

Journal of sports science & medicine
This study aimed to identify relationships between external and internal load parameters with subjective ratings of perceived exertion (RPE). Consecutively, these relationships shall be used to evaluate different machine learning models and design a ...

Enhancing Sports Injury Risk Assessment in Soccer Through Machine Learning and Training Load Analysis.

Journal of sports science & medicine
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
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
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 ...