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Soccer

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Seasonal Linear Predictivity in National Football Championships.

Big data
Predicting the results of sport matches and competitions is a growing research field, benefiting from the increasing amount of available data and novel data analytics techniques. Excellent forecasts can be achieved by advanced statistical and machine...

Keeping it 100: Social Media and Self-Presentation in College Football Recruiting.

Big data
Social media provides a platform for individuals to craft personal brands and influence their perception by others, including potential employers. Yet there remains a need for more research investigating the relationship between individuals' online i...

Task-Based Automatic Evaluation of People with Intellectual Disabilities Performed on a Robotic Table Soccer.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper is concerned with the automatic evaluation of selected tasks performed by people with intellectual Disabilities. According to the International Classification of Functioning, Disability and Health (ICF) system, subjects must be divided int...

Use of Machine Learning and Wearable Sensors to Predict Energetics and Kinematics of Cutting Maneuvers.

Sensors (Basel, Switzerland)
Changes of directions and cutting maneuvers, including 180-degree turns, are common locomotor actions in team sports, implying high mechanical load. While the mechanics and neurophysiology of turns have been extensively studied in laboratory conditio...

Predicting Future Perceived Wellness in Professional Soccer: The Role of Preceding Load and Wellness.

International journal of sports physiology and performance
PURPOSE: The influence of preceding load and future perceived wellness of professional soccer players is unexamined. This paper simultaneously evaluates the external load (EL) and internal load (IL) for different time frames in combination with prese...

Identifying playing talent in professional football using artificial neural networks.

Journal of sports sciences
The aim of the current study was to objectively identify position-specific key performance indicators in professional football that predict out-field players league status. The sample consisted of 966 out-field players who completed the full 90 minut...

Using machine learning to improve our understanding of injury risk and prediction in elite male youth football players.

Journal of science and medicine in sport
OBJECTIVES: The purpose of this study was to examine whether the use of machine learning improved the ability of a neuromuscular screen to identify injury risk factors in elite male youth football players.

Importance of anthropometric features to predict physical performance in elite youth soccer: a machine learning approach.

Research in sports medicine (Print)
The present study aimed to determine the contribution of soccer players' anthropometric features to predict their physical performance. Sixteen players, from a professional youth soccer academy, were recruited. Several anthropometric features such as...

A Machine Learning Approach to Assess Injury Risk in Elite Youth Football Players.

Medicine and science in sports and exercise
PURPOSE: To assess injury risk in elite-level youth football (soccer) players based on anthropometric, motor coordination and physical performance measures with a machine learning model.

GreenSea: Visual Soccer Analysis Using Broad Learning System.

IEEE transactions on cybernetics
Modern soccer increasingly places trust in visual analysis and statistics rather than only relying on the human experience. However, soccer is an extraordinarily complex game that no widely accepted quantitative analysis methods exist. The statistics...