A highly accurate Mamdani fuzzy inference system for tennis match predictions

Boldizsár Tüű-Szabó () and László T. Kóczy ()
Additional contact information
Boldizsár Tüű-Szabó: Széchenyi István University
László T. Kóczy: Széchenyi István University

Fuzzy Optimization and Decision Making, 2025, vol. 24, issue 1, No 4, 99-127

Abstract: Abstract This paper presents a Mamdani fuzzy inference system (FIS) designed for predicting tennis match outcomes with greater accuracy compared to existing models such as the Weighted Elo (WElo) ranking system. By integrating factors like historical performance, surface-specific proficiency, and recent form trends, the Mamdani FIS provides a nuanced approach to forecasting match results. Central to this method is the optimization of membership functions using a Bacterial Evolutionary Algorithm (BEA), which fine-tunes parameters to better model uncertainties inherent in sports analytics. This is the further development of Nawa and Furuhashi’s original approach of fuzzy system parameter discovery, which operates on the stricter conditions concerning the membership function shapes. The study demonstrates that the Mamdani FIS outperforms the traditional methods in both predictive accuracy and profitability of betting strategies. Through extensive validation, the model achieves higher accuracy and lower log loss metrics, indicating improved reliability in prediction outcomes. Additionally, the Mamdani FIS consistently yields higher returns on investment across various betting scenarios, showcasing its practical utility in sports betting applications. Overall, the proposed Mamdani FIS represents a robust tool for tennis match prediction, with potential extensions to other sports and predictive contexts. Future research may explore incorporating additional variables and applying this fuzzy inference approach to broader areas of sports analytics.

Keywords: Fuzzy inference system; Forecasting; Tennis; Prediction (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10700-025-09440-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:fuzodm:v:24:y:2025:i:1:d:10.1007_s10700-025-09440-6

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10700

DOI: 10.1007/s10700-025-09440-6

Access Statistics for this article

Fuzzy Optimization and Decision Making is currently edited by Shu-Cherng Fang and Boading Liu

More articles in Fuzzy Optimization and Decision Making from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().