<![CDATA[Predicting the outcome of a Dota 2 match is a complex problem because it is influenced by many dynamic variables that change at each stage of the game. This study aims to analyze and predict the probability of winning a Dota 2 match using the Fuzzy Tsukamoto method based on three main variables: Hero Win Rate, Number of Kills, and Tower Destroyed. The fuzzy model was constructed using triangular and trapezoidal membership functions, with variable weights adjusted for the early game, mid game, and late game. Test results show that in the early game, the Hero Win Rate variable has the most dominant influence on the probability of winning, with a weight of 0.7. In the mid game, the number of kills and tower destruction begin to have a significant impact, while in the late game, towers and kills become the primary determinants of the probability of winning. The proposed system is able to generate different percentages of the probability of winning at each stage of the game and logically reflect the dynamics of the Dota 2 game. Based on these results, the Fuzzy Tsukamoto method is considered capable of handling uncertainty in Dota 2 match prediction and provides more flexible results than deterministic approaches, although it still depends on the quality of the dataset and the fuzzy rules used.]]>
Copyrights © 2025
