Abstract

The single most important aspect that allowed for the rise of playing video games as a form of competition is the creation of games that provide an even playing field for casuals and pro players alike. First person shooter games such as Counter-Strike: Global Offensive and Valorant have established themselves as two of the most popular eSports games of recent history on account of their high levels of attention in the field of balancing and fairness. The creation of balanced gamespaces for competitive shooter games has proven to be a difficult task for game developers, who usually have to support and improve their maps using iterative updates even long after their release. The goal set for this thesis is the creation of an analysis toolkit for competitive shooter maps that is intended to support developers in the map creation process. By examining gamespaces found in modern First person shooters, the aspects most influential to balancing were identified as the timing of meeting points, rotation time between multiple objectives and the design of chokepoint areas. For the purpose of data analysis, a datastructure was implemented that can be used to represent and store various types of information of any gamespace. On the foundation of this framework, tools that aid in the identification of possible imbalances were implemented, including Distance Evaluation for determining meeting points and rotation times as well as a computation for the progression of visibility for high intensity areas. The analysis toolkit allows for visualization of this accumulated data, including information gained through player testing. Additionally, a framework for creating automated tests was implemented that allows developers to quickly verify desired properties of their digital environments.

Results/Implementation/Project Description

Conclusion

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