Information theory and player archetype choice in Hearthstone

TL;DR

This study analyzes three years of Hearthstone data to understand how player archetype choices evolve, using information theory to reveal patterns and effects of game updates on player behavior.

Contribution

It introduces an information-theoretic approach to analyze player archetype dynamics and the impact of game changes on decision-making in Hearthstone.

Findings

Entropy increases before popular deck emergence

Player experimentation peaks during major updates

Player choices are partly predictable based on past decisions

Abstract

Using three years of game data of the online collectible card game Hearthstone, we analyse the evolution of the game's system over the period 2016--2019. By considering the frequencies that archetypes are played, and their corresponding win-rates, we are able to provide narratives of the system-wide changes that have occurred over time, and player reactions to them. Applying the archetype frequencies to analyse the system's Shannon entropy, we characterise the salient features of the time series of player choice. Paying particular attention to how entropy is affected during periods of both small and large-scale change, we are able to demonstrate the effects of increased player experimentation before popular decks and tactics emerge. Furthermore, constructing conditional probabilities that simulate understandable player behaviour, we analyse the system's information storage and test the explain-ability of current player choice based on previous decision-making.