AIMC Topic: Athletic Performance

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Evaluation of tactical training in team handball by means of artificial neural networks.

Journal of sports sciences
While tactical performance in competition has been analysed extensively, the assessment of training processes of tactical behaviour has rather been neglected in the literature. Therefore, the purpose of this study is to provide a methodology to asses...

A minimum attention control law for ball catching.

Bioinspiration & biomimetics
Digital implementations of control laws typically involve discretization with respect to both time and space, and a control law that can achieve a task at coarser levels of discretization can be said to require less control attention, and also reduce...

Influence of recovery intensity on oxygen demand and repeated sprint performance.

The Journal of sports medicine and physical fitness
BACKGROUND: This study aimed to determine effects of recovery intensity (passive, 20%, 30% and 40% V̇O2peak) on oxygen uptake kinetics, performance and blood lactate accumulation during repeated sprints.

A Method for Using Player Tracking Data in Basketball to Learn Player Skills and Predict Team Performance.

PloS one
Player tracking data represents a revolutionary new data source for basketball analysis, in which essentially every aspect of a player's performance is tracked and can be analyzed numerically. We suggest a way by which this data set, when coupled wit...

Team activity recognition in Association Football using a Bag-of-Words-based method.

Human movement science
In this paper, a new methodology is used to perform team activity recognition and analysis in Association Football. It is based on pattern recognition and machine learning techniques. In particular, a strategy based on the Bag-of-Words (BoW) techniqu...

Effects of robotically modulating kinematic variability on motor skill learning and motivation.

Journal of neurophysiology
It is unclear how the variability of kinematic errors experienced during motor training affects skill retention and motivation. We used force fields produced by a haptic robot to modulate the kinematic errors of 30 healthy adults during a period of p...

A Survey of Deep Learning in Sports Applications: Perception, Comprehension, and Decision.

IEEE transactions on visualization and computer graphics
Deep learning has the potential to revolutionize sports performance, with applications ranging from perception and comprehension to decision. This article presents a comprehensive survey of deep learning in sports performance, focusing on three main ...

Machine Learning in Rugby Union: Predicting and Identifying Key Performance Indicators for Professional Rugby Union Players in Match Play Based Workload.

European journal of sport science
Rugby union is an intermittent high-intensity contact sport requiring the analysis of various training and match metrics. Time-motion analysis and video analysis have enhanced the understanding of the interplay between these two factors. However, lim...

A multidimensional prediction model for overtraining risk in youth soccer players: Integrating physiological and psychological markers.

Journal of sports sciences
Overtraining syndrome (OTS) poses a critical challenge in youth soccer, particularly during periods of rapid physiological maturation combined with high training demands. This study aimed to develop and validate a multidimensional prediction model fo...

DRL-driven padel players: Simulating padel matches through deep reinforcement learning in real and hypothetical scenarios.

Journal of sports sciences
Recent advances in Deep Reinforcement Learning (DRL) have opened new avenues for sport research. DRL allows virtual agents to learn and solve complex tasks with minimal input, which means that models can be trained with little or no data collection. ...