Gacha system in free-to-play games

This bachelor thesis deals with gacha mechanism, compares three different gacha systems in free-to-play games, and takes a deeper look into the Arknights gacha system whose simulation this work aims to create. Thus the main aim of this thesis is to create a complex simulation in the programming language Python and analyze its predictions and results. This thesis also describes the rules and common design practices used in games implementing this system and puts the simulation of one specific system into the context of other existing implementations, the history of gacha and similar random rewards mechanisms, and a probability theory. In the chapter dedicated to probability theory, this thesis explains related terms such as stochastic process, stochastic simulation, Markov process, Markov property, and Markov Chain Monte Carlo method, which is a method in a modified form used in the design and execution of the simulation. The results show how essential the implementation of pity is for the whole system. The results also state the prediction that the average resources needed to acquire the highest rarity reward are 48,000, meaning approximately four months' worth of standard game rewards or premium currency worth of 200\$. This thesis can be used both by the players who want to gain a better understanding of the gacha system, as well as the developers of games implementing the said system. It also puts current knowledge regarding legislation, regulations, and the psychological aspect of this phenomenon into a new perspective.