Elements of randomness are a common factor inmodern digital games, from simple rolls of a die tocomplex AI systems. These elements have an impacton how the player experiences a game. We believe thatexploring the field of luck analysis can benefit designersthrough an developed understanding of how such elementsaffect players. The developers of the digital card gameSlay the Spire has released 77 millions of instances ofplay and sample of these are explored in this study. Withthe use of data mining, data clustering and correlationanalysis the effect of elements of randomness present inSlay the Spire are analyzed. In conclusion, three playerskill groups were identified with the use of clustering:Winners, Low skill losers and High skill losers. Weobserved that people who succeeded in beating the game,had an increased amount of randomness in the formof cards by a factor of 1.82. Showing that more skilledplayers do not shy away from randomness but insteadembrace it more than lower skilled players.

Dream Quest(2014) introduced the Roguelike deckbuilder as a game genre. The genre later became popular with the help of Slay the Spire in 2017. As the genre is still fairly new, there are not a lot of tools for designing games of said genre. Taking inspiration from games of the same genre could be a solution to such a problem, one way to do so is via modding. Slay the Spire offers an extensive modding API to users which lets users create new cards, items, events, and even characters. By utilizing these features, it is possible to create a concept for a new game. To use the API, however, would require users to be familiar with programming, which could take a long time to learn for a beginner. Thus, a UI, The Creator was created to let users without experience create mods for Slay the Spire. The UI lets users create cards with different actions and properties without the need to interact with the source code.

Slay the Spire is a complex deck-building and roguelike game with many possibilities of improving players ability to win. An important part of Slay the Spire is choosing a path that makes the players character as successful as possible. In this study we show that machine learning can help players pick better paths by creating an Artificial Neural Network (ANN) that predicts the most successful path of all available paths, we also discuss what makes a path successful. This study performed two experiments, one user study and one simulation experiment, with the intention of evaluating the created ANN and analysing what makes paths successful. Through the user study this paper shows that the ANN was effective at predicting paths, outperforming all other human players who played normally in all three cases. This study concludes that machine learning can be used effectively to help make pathing decisions in Slay the Spire. Furthermore the study proves the importance of the room types ’Elite’ and ’Campfires’ through the simulation experiment, user study and analysis of data from previous playthroughs.