Football Player Scouting and Recruitment: Performance Prediction Using Player Skills and Injuries with Machine Learning

-, Abhilash Janardhanan (2024) Football Player Scouting and Recruitment: Performance Prediction Using Player Skills and Injuries with Machine Learning. Masters thesis, Dublin, National College of Ireland.

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Abstract

Recruiting and scouting football players requires a more complex understanding of both the skills and injury history of a player for optimal team performance. Most of the existing methods might look at these factors separately which might in turn overlook how a player’s health and their skills affect each other. Current techniques might not fully capture the holistic view necessary for making crucial decisions while scouting and recruiting players. To address these shortcomings and gaps this study introduces a new approach which integrates both player features and injury data to predict future performance more comprehensively and effectively. A new performance metric is developed that combines key skill attributes with injury data. The study tries to provide a more complete and balanced evaluation of football recruits and scouts. The initial results from the implementation of this combined model are encouraging. They suggest that it could improve how players are assessed by considering both player’s ability and injury risks. Further research aims to improve these predictions by including additional factors such as psychological attributes and how well can a player fit into team strategies.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Subhnil, Shubham UNSPECIFIED
Subjects:	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:	Ciara O'Brien
Date Deposited:	01 Sep 2025 11:43
Last Modified:	01 Sep 2025 11:43
URI:	https://norma.ncirl.ie/id/eprint/8663

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