Analysis of Optimization Approaches for the Game-Theoretic Matchmaking Queue Model in League of Legends

Abstract

This study takes the League of Legends matchmaking queuing system as an example. Using game theory frameworks, it constructs a basic queuing game model, analyzes non-cooperative game theory and Nash equilibrium, and incorporates mechanism design theory to model player decision-making behavior. It systematically analyzes the equilibrium characteristics of existing matchmaking rules and the conflict between queue waiting time and fairness. Based on this, it proposes a reputation- and priority-based dynamic matchmaking mechanism, a multi-agent game optimization model, and load balancing and cross-server matchmaking strategies. The aim is to alleviate player churn and toxicity issues through incentive-compatible design, thereby improving system efficiency and the competitive experience. This research provides theoretical support and practical pathways for online game matchmaking optimization and has significant reference value for the healthy development of the esports ecosystem.