AIMC Topic: Athletic Performance
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A Method for Using Player Tracking Data in Basketball to Learn Player Skills and Predict Team Performance.
PloS one
Sep 9, 2015
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
Mar 25, 2015
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
Feb 11, 2015
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...
Predicting Field-Sport Distances Without Global Positioning Systems in Indoor Play: A Comparative Study of Machine-Learning Techniques.
International journal of sports physiology and performance
Jun 1, 2025
PURPOSE: Accurately predicting the distance covered by athletes during indoor sport activities without the use of GPS (global positioning systems) presents a significant challenge. This study evaluates the effectiveness of various machine-learning te...
Predictive athlete performance modeling with machine learning and biometric data integration.
Scientific reports
May 11, 2025
The Purpose of this study is to propose a new integrative framework for athletic performance prediction based on state-of-the-art machine learning analysis and biometric data biometric scanning. By merging physiological signals i.e., Heart rate varia...
Predicting Sprint Potential: A Machine Learning Model Based on Blood Metabolite Profiles in Young Male Athletes.
European journal of sport science
Mar 1, 2025
This study aims to utilize male blood metabolite signatures for (i) distinguishing between healthy individuals and athletes, thereby optimizing the athlete screening process; and (ii) predicting athletic performance in 100, 200, and 400 m sprints, en...
Validity and Inter-Device Reliability of an Artificial Intelligence App for Real-Time Assessment of 505 Change of Direction Tests.
European journal of sport science
Feb 1, 2025
The present study aimed to explore the validity and inter-device reliability of a novel artificial intelligence app (Asstrapp) for real-time measurement of the traditional (tra505) and modified-505 (mod505) change of direction (COD) tests. Twenty-fiv...
Training forecast to football athletes using Hopfield neural networks based on Markov matrix.
PloS one
Jan 1, 2025
This paper proposes a neural network based on the Markov probability transition matrix to predict the training performance of football athletes. Firstly, seven training indicators affecting the training performance are designed by the Event-group tra...
Inner pace: A dynamic exploration and analysis of basketball game pace.
PloS one
Jan 1, 2025
This study aims to investigate the dynamics of basketball game pace and its influence on game outcomes through a novel intra-game segmentation approach. By employing K-means clustering on possession duration, we categorized possessions from 1,141 NBA...
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