Virtual Coach: Personalized Training Recommendations for Football Players Using Machine Learning and enhance the players performance

Jaymon, Joshua (2025) Virtual Coach: Personalized Training Recommendations for Football Players Using Machine Learning and enhance the players performance. Masters thesis, Dublin, National College of Ireland.

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Abstract

Do current computer vision and machine learning tools give football coaches a reliable way to shape teams plus individuals through automated performance analysis?

The study shows that YOLO object detection - YOLOv3, YOLOv5, YOLOv8 - combined with MediaPipe tracking sharpens how coaches spot player actions, judge performance along with tailor training advice. The Virtual Coach ingests IAUFD match footage and returns real time detections of players, the ball in addition to key events, but also gesture data for technical scrutiny. Experiments reveal that YOLOv8l balances accuracy, recall next to localization best among the tested models - YOLOv5m delivers the tightest bounding boxes. The outcome confirms that modern analysis tools slot into coaching routines and sharpen decisions.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Nolan, Eamon UNSPECIFIED
Uncontrolled Keywords:	Deep learning; Football Analysis; Gesture Detection; Recommendation; Realtime Streaming
Subjects:	G Geography. Anthropology. Recreation > GV Recreation Leisure > Sports > Soccer Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence > Computer vision Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence > Computer vision Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning G Geography. Anthropology. Recreation > GV Recreation Leisure > Sports
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	25 Aug 2026 14:56
Last Modified:	25 Aug 2026 14:56
URI:	https://norma.ncirl.ie/id/eprint/9633

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