Back to Search Start Over

Artificial intelligence applications in the football codes: A systematic review.

Authors :
Elstak, Isaiah
Salmon, Paul
McLean, Scott
Source :
Journal of Sports Sciences; Jul2024, Vol. 42 Issue 13, p1184-1199, 16p
Publication Year :
2024

Abstract

Artificial Intelligence (AI) is increasingly being adopted across many domains such as transport, healthcare, defence and sport, with football codes no exception. Though there is a range of potential benefits of AI, concern has also been expressed regarding potential risks. An important first step in ensuring that AI applications in football are usable, beneficial, safe and ethical is to understand the current range of applications, the AI models adopted and their proposed functions. This systematic review aimed to identify different applications of AI across football codes to synthesise current knowledge and determine whether potential risks are being considered. The systematic review included 190 peer-reviewed articles. Nine areas of application were found ranging from athlete evaluation and event detection to match outcome prediction and injury detection and prediction. In total, 27 different AI models were identified, with artificial neural networks the most frequently applied. Five AI assessment metrics were identified including specificity, recall, precision, accuracy and F1-score. Four potential risks were identified, concerning data security, usability, data biases and inappropriate athlete load management. It is concluded that, though a wide range of AI applications currently exist, further work is required to develop AI for football and identify and manage potential risks. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02640414
Volume :
42
Issue :
13
Database :
Complementary Index
Journal :
Journal of Sports Sciences
Publication Type :
Academic Journal
Accession number :
179359968
Full Text :
https://doi.org/10.1080/02640414.2024.2383065