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Soccer

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The tactics of successful attacks in professional association football: large-scale spatiotemporal analysis of dynamic subgroups using position tracking data.

Journal of sports sciences
Association football teams can be considered complex dynamical systems of individuals grouped in subgroups (defenders, midfielders and attackers), coordinating their behaviour to achieve a shared goal. As research often focusses on collective behavio...

Analysing the predictive capacity and dose-response of wellness in load monitoring.

Journal of sports sciences
This study aimed to identify the predictive capacity of wellness questionnaires on measures of training load using machine learning methods. The distributions of, and dose-response between, wellness and other load measures were also examined, offerin...

Deep Learning-Based Football Player Detection in Videos.

Computational intelligence and neuroscience
The main task of football video analysis is to detect and track players. In this work, we propose a deep convolutional neural network-based football video analysis algorithm. This algorithm aims to detect the football player in real time. First, five...

Influence of Different Passing Methods of Physical Fitness in Football Using Deep Learning.

Computational intelligence and neuroscience
Deep learning is a new direction in the field of machine learning, which learns the inherent laws and levels of data sample representation. The information gained during learning plays an important role in interpreting data such as text, images, and ...

Football Game Video Analysis Method with Deep Learning.

Computational intelligence and neuroscience
Football is a beloved sport, and its wide audience makes football video one of the most analytically valuable types of video. Researchers have achieved certain research results in football video content analysis. How to locate interesting event clips...

An End-to-End Deep Learning Pipeline for Football Activity Recognition Based on Wearable Acceleration Sensors.

Sensors (Basel, Switzerland)
Action statistics in sports, such as the number of sprints and jumps, along with the details of the corresponding locomotor actions, are of high interest to coaches and players, as well as medical staff. Current video-based systems have the disadvant...

Automated soccer head impact exposure tracking using video and deep learning.

Scientific reports
Head impacts are highly prevalent in sports and there is a pressing need to investigate the potential link between head impact exposure and brain injury risk. Wearable impact sensors and manual video analysis have been utilized to collect impact expo...

xLength: Predicting Expected Ski Jump Length Shortly after Take-Off Using Deep Learning.

Sensors (Basel, Switzerland)
With tracking systems becoming more widespread in sports research and regular training and competitions, more data are available for sports analytics and performance prediction. We analyzed 2523 ski jumps from 205 athletes on five venues. For every j...

Model of the Performance Based on Artificial Intelligence-Fuzzy Logic Description of Physical Activity.

Sensors (Basel, Switzerland)
The aim of the study was to build a fuzzy model of lower limb peak torque in an isokinetic mode. The study involved 93 male participants (28 male deaf soccer players, 19 hearing soccer players and 46 deaf untraining male). A fuzzy computational model...

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
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...