MACHINE LEARNING MODELS FOR PERFORMANCE PREDICTION OF YOUNG PLAYERS IN FOOTBALL ACADEMIES – A REVIEW
Machine learning, a component of artificial intelligence, has applications in the most diverse domains. The field of machine learning can be classified into several categories, mainly based on the nature of the problems addressed. The main characteristics of these categories are reviewed. Machine...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
ALTIUS ACADEMY Foundation - Faculty of Physical Education and Sports
2025-05-01
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| Series: | Sport şi Societate |
| Subjects: | |
| Online Access: | https://www.sportsisocietate.ro/articol/713 |
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| Summary: | Machine learning, a component of artificial intelligence, has applications in the most
diverse domains. The field of machine learning can be classified into several categories, mainly
based on the nature of the problems addressed. The main characteristics of these categories are
reviewed. Machine learning has numerous applications in sports, which mainly aim at
anticipating medical problems and the recovery potential of athletes, predicting the results of
sporting events, estimating how different elements of a match can influence its outcome,
assessing the market value of a player, and predicting the performance of young players. Given
that football has become a business generating significant income, the talent discovery stage is of
particular importance, as it provides a competitive advantage over other teams and financial
compensation from future offers made to selected players. This involves monitoring and
evaluating football players with potential in order to sign a contract, as well as the subsequent
stages of developing these talents. The paper summarizes the different methods of using machine
learning algorithms to detect new football talents, based on criteria such as physical, mental and
technical qualities. |
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| ISSN: | 1582-2168 2344-3693 |