The Hidden Rules of Win Rate Manipulation: A Study on Algorithmic Discrimination in the Matching Mechanism of MOBA Games—Taking Honor of Kings as an Example

Abstract

With the prevalence of MOBA games such as Honor of Kings, the fairness of the algorithm in their matching mechanisms has sparked widespread controversy. This study uses this game as a case to explore whether algorithmic discrimination exists in its matching mechanism. Through stratified random sampling to obtain data from over 3,000 players, combined with questionnaires, controlled experiments, and quantitative analysis, it is found that game duration, recharge amount, and the number of consecutive wins/losses have a significant impact on players' win rates: there is a stepwise positive correlation between payment amount and win rate, with heavy-paying players having a win rate of 58.1%, 6.4% higher than free players (51.7%); consecutive wins trigger negative matching adjustments by the system (win rate decreases by 4.5%), while consecutive losses activate protection mechanisms (win rate increases by 1.6%). Jurisprudential analysis shows that operators actively design differentiated matching strategies based on commercial goals, systematically damaging players' right to fair competition by linking payments to high-quality resources and dynamically adjusting match difficulty, constituting algorithmic discrimination in a legal sense. The study proposes a collaborative governance approach from three aspects: legislatively defining the constitutive elements of algorithmic discrimination, establishing a transparent review system for regulation, and building algorithm self-correction mechanisms for enterprises, providing theoretical and practical references for the fairness of the digital competitive ecosystem.