Title: Computational efficiency in sports talent identification - a systematic review

Authors: Naveed Jeelani Khan; Gulfam Ahamad; Mohd. Naseem; Shahab Saquib Sohail

Addresses: Department of Computer Sciences, Baba Ghulam Shah Badshah University, Rajouri, India ' Department of Computer Sciences, Baba Ghulam Shah Badshah University, Rajouri, India ' Department of Computer Sciences, Baba Ghulam Shah Badshah University, Rajouri, India ' Department of Computer Science and Engineering, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi, India

Abstract: The selection of talent for sports has always been of great concern. The research interest in the domain of computational decision-making for sports talent identification is on an increasing curve. The conventional approaches are being modelled into the scientific models using various analytical and mathematical computational techniques. This paper reviews some of the talent identification models and aims to project the current perspective of the computational techniques being employed in sports talent identification (TiD). Articles from a timeframe of 1995-2020 were systematically selected in accordance with the PRISMA guidelines. We remain focused on the computational methodology being employed in the TiD models. The review delivers the findings and highlights some of the inherent issues that are not being addressed by the existing TiD models.

Keywords: sports talent identification; applied soft computing; multi-criteria decision making; MCDM; sports talent computation.

DOI: 10.1504/IJADS.2023.130600

International Journal of Applied Decision Sciences, 2023 Vol.16 No.3, pp.358 - 384

Received: 07 Aug 2021
Accepted: 10 Feb 2022
Published online: 01 May 2023 *

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