This research introduces a sophisticated Decision Support System (DSS) tailored for predicting football tournament outcomes, leveraging the robustness of the ELECTRE (Elimination and Choice Translating Reality) method. The study outlines a systematic methodology integrating multi-criteria decision-making principles, historical data, and diverse performance metrics to forecast match results. The research framework encompasses data collection, criteria identification, and the application of the ELECTRE method, assigning relative weights to criteria and establishing thresholds for evaluation. The DSS facilitates nuanced comparisons between teams across multiple criteria, navigating uncertainties and accommodating imprecise data inherent in sports analytics. Moreover, the research delineates the development of the predictive model, its calibration, and evaluation against historical data. Through a comparative analysis with other prediction methods, the study showcases the strengths of the ELECTRE-based DSS in providing comprehensive insights into football tournament outcomes. The implications of accurate predictions resonate across various stakeholders, influencing strategic decisions for teams, enhancing fan engagement, impacting betting landscapes, and shaping advertising and broadcasting strategies within the sports industry.
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