A Machine Learning Framework to Scout Football Players

Sayeed, Hashir (2023) A Machine Learning Framework to Scout Football Players. Masters thesis, Dublin, National College of Ireland.

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Abstract

Scouting football players involves selecting players that have potential to play at a national level for which they are being assessed and also the optimal position they can play based on their performance such as goals scored, accuracy of passes and so on. The current challenge is that the scouts may not identify all the performance factors during their assessment for example Command, Communication and so on. This research proposes a Machine Learning Framework to scout football players that have the potential to play at a national level. The proposed framework combines a classification model and a predictive model. The classification models identifies the optimal position of the player. The predictive models identifies best possible match in a national team for every position. The dataset is given by the FIFA organization, who are responsible for keeping updated statistics of the players.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Stynes, Paul UNSPECIFIED McLaughlin, Eugene UNSPECIFIED Clifford, William UNSPECIFIED
Subjects:	H Social Sciences > HA Statistics Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science G Geography. Anthropology. Recreation > GV Recreation Leisure > Sports > Soccer Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Tamara Malone
Date Deposited:	02 Jan 2025 13:55
Last Modified:	02 Jan 2025 13:55
URI:	https://norma.ncirl.ie/id/eprint/7265

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