Using Logistic Regression to Analyze the Balance of a Game: The Case of StarCraft II
Hyokun Yun

TL;DR
This paper applies logistic regression to analyze the game balance of StarCraft II, aiming to assess fairness and competitiveness in professional gaming environments.
Contribution
It introduces a novel application of logistic regression for game balance analysis, providing a statistical approach to evaluate fairness in e-sports.
Findings
Logistic regression can effectively assess game fairness.
The analysis reveals potential design flaws affecting balance.
Statistical methods can inform game design improvements.
Abstract
Recently, the market size of online game has been increasing astonishingly fast, and so does the importance of good game design. In online games, usually a human user competes with others, so the fairness of the game system to all users is of great importance not to lose interests of users on the game. Furthermore, the emergence and success of electronic sports (e-sports) and professional gaming which specially talented gamers compete with others draws more attention on whether they are competing in the fair environment. No matter how fierce the debates are in the game-design community, it is rarely the case that one employs statistical analysis to answer this question seriously. But considering the fact that we can easily gather large amount of user behavior data on games, it seems potentially beneficial to make use of this data to aid making decisions on design problems of games.…
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Taxonomy
TopicsSports Analytics and Performance · Artificial Intelligence in Games · Data Mining Algorithms and Applications
