AIMC Topic: Team Sports
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Estimating oxygen uptake in simulated team sports using machine learning models and wearable sensor data: A pilot study.
PloS one
Apr 21, 2025
Accurate assessment of training status in team sports is crucial for optimising performance and reducing injury risk. This pilot study investigates the feasibility of using machine learning (ML) models to estimate oxygen uptake (VO2) with wearable se...
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
Jun 25, 2024
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 ...
Predicting successful draft outcome in Australian Rules football: Model sensitivity is superior in neural networks when compared to logistic regression.
PloS one
Feb 29, 2024
Using logistic regression and neural networks, the aim of this study was to compare model performance when predicting player draft outcome during the 2021 AFL National Draft. Physical testing, in-game movement and technical involvements were collecte...
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