Treffer: AI-SPOT: a Novel Artificial Intelligence enabled Sport Optimisation Tracker to Enhance Performance and Prevent Injury in Elite Footballers

Title:
AI-SPOT: a Novel Artificial Intelligence enabled Sport Optimisation Tracker to Enhance Performance and Prevent Injury in Elite Footballers
Authors:
Angus, Aaron Chen, Sirisena, Dinesh
Contributors:
Football Association of Singapore, Khoo Teck Puat Hospital, Republic Polytechnic
Source:
Global Medical and Health Communication; Vol 12, No 1 (2024); 1–11 ; Global Medical & Health Communication (GMHC); Vol 12, No 1 (2024); 1–11 ; 2460-5441 ; 2301-9123 ; 10.29313/gmhc.v12i1
Publisher Information:
Universitas Islam Bandung
Publication Year:
2024
Collection:
Jurnal Ilmiah Nasional dan Internasional Unisba (P2U - Pusat Penerbitan Universitas, LPPM Unisba)
Subject Terms:
Sport Medicine, Artificial intelligence, data-driven decision making, machine learning
Document Type:
Fachzeitschrift article in journal/newspaper
File Description:
application/pdf
Language:
English
Relation:
http://ejournal.unisba.ac.id/index.php/gmhc/article/view/12788/pdf; http://ejournal.unisba.ac.id/index.php/gmhc/article/downloadSuppFile/12788/3307; http://ejournal.unisba.ac.id/index.php/gmhc/article/downloadSuppFile/12788/3312; http://ejournal.unisba.ac.id/index.php/gmhc/article/view/12788
DOI:
10.29313/gmhc.v12i1.12788
Availability:
http://ejournal.unisba.ac.id/index.php/gmhc/article/view/12788
https://doi.org/10.29313/gmhc.v12i1.12788
Rights:
Copyright (c) 2024 Global Medical and Health Communication ; https://creativecommons.org/licenses/by-nc-sa/4.0
Accession Number:
edsbas.B3BCC053
Database:
BASE

Weitere Informationen

This study introduces AI-SPOT, a novel artificial intelligence tool for optimizing performance and preventing injuries in elite footballers. Data were collected from four Singapore Premiere League clubs and the National Team, encompassing 68 male footballers over two seasons (2021–2022). The comprehensive dataset included diverse metrics, injury records, and automated live match data from established databases. AI-SPOT employs Python's scikit-learn for predictive analytics, using techniques like logistic regression and XGBoost, and was further developed with TensorFlow. Its effectiveness in injury prediction and performance assessment was validated with extensive local and international data sources. The system's potential for broader sports applications was underscored by user experience assessments, indicating a significant shift towards AI-driven strategies in sports management. Despite its reliance on high-quality, sport-specific data, AI-SPOT's adaptability highlights its role as a transformative tool in sports analytics, paving the way for advanced, data-driven approaches in sports management and strategy formulation.