Computer Science in Sport

I HISTORY.- History.- II DATA.- Artificial data.- Text data.- Video data.- Event data.- Position data.- Online data.- III MODELING.- Modeling.- Predictive models.- Physiological modeling.- IV SIMULATION.- Simulation.- Metabolic simulation.- Simulation of physiological adaptation processes.- V PROGRAMMING LANGUAGES.- An introduction to the programming language R for beginners.- Phyton.- VI DATA ANALYSIS.- Logistic Regression.- Time Series Data Mining.- Process Mining.- Networks Centrality.-  Artificial Neural Networks.- Deep Neural Networks.- Convolutional Neural Networks.- Transfer Learning.- Random Forest.- Statistical learning for the modeling of soccer matches.- Open-Set Recognition.- VII VISUALIZATION.- Visualization – Basics and Concepts.- VIII OUTLOOK.- Outlook.