Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/22436
Title: Integrating Hybrid FAHP–FRADAR Approach and the FMEA Framework for Evidence-Informed Risk Assessment in Football Player Transfers
Authors: Komatina, Nikola
Journal: Journal of Data Science and Intelligent Systems
Issue Date: 2025
Abstract: This study established a methodology for assessing risk in football player transfers to help football club management make decisions. The proposed model is based on the Failure Mode and Effects Analysis (FMEA) framework, which is expanded by incorporating two Multi-Attribute Decision-Making (MADM) techniques: the Fuzzy Analytic Hierarchy Process (FAHP) was utilized to assign weights to risk factors, and the Fuzzy Ranking based on Distances And Range (FRADAR) method was used to rank potential football transfers. The proposed model is analogous to FMEA, but instead of the traditional risk factors severity, occurrence, and detection, risk factors tailored to the given problem are used: player market value (as severity), frequency of club changes or a player’s injury history (as occurrence), and adaptability to various tactics and playing styles (as detection). The primary objective of this study is to develop a sufficiently reliable model that is flexible enough to be applied in other sports and in various areas of management. The quality of available data and the assessments made by decision-makers, which rely on their experience, knowledge, and subjective judgment, play a crucial role in implementing the proposed model. The model was tested on a random sample of five football players, all central defenders, who are members of one of the five highest-ranked football leagues in Europe.
URI: https://scidar.kg.ac.rs/handle/123456789/22436
Type: article
DOI: 10.47852/bonviewJDSIS52025293
ISSN: 2972-3841
Appears in Collections:Faculty of Engineering, Kragujevac

Downloads(s)

1

Files in This Item:
File Description SizeFormat 
JDSIS52025293-R3.pdf1.15 MBAdobe PDFThumbnail
View/Open


This item is licensed under a Creative Commons License Creative Commons