Search Results - Pasic, A.
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Football movement profile-based creatine-kinase prediction performs similarly to global positioning system-derived machine learning models in national-team soccer players
Schuth, G., Szigeti, G., Dobreff, G., Pašic, A., Gabbett, T., Szilas, A., Pavlik, G.Published in International Journal of Sports Physiology and Performance (2024)“…Pašic, A.…”
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Individual-specific relationship between external training and match load and creatine-kinase response in youth national team soccer players
Schuth, G., Szigeti, G., Dobreff, G., Pasic, A., Gabbett, T., Szilas, A., Pavlik, G.Published in Sports Health: A Multidisciplinary Approach (2023)“…Pasic, A.…”
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Physical performance optimization in football
Dobreff, G., Revisnyei, P., Schuth, G., Szigeti, G., Toka, L., Pašic, A.Published in Machine Learning and Data Mining for Sports Analytics (2020)“…Pašic, A.…”
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competition
load
soccer
training
muscle
injury
junior elite sport
prognosis
sports medicine
GPS
movement
youth
blood
creatine
damage
heart rate
individual
inertial measurement unit
load intensity
load volume
male
measuring and information system
muscle physiology
parameter
peaking for a competition
performance
performance capacity
performance factor
playing position (sport games)
prevention