Magy Seif El-Nasr, Truong-Huy D. Nguyen, Alessandro Canossa, Anders Drachen. Game Data Science

Oxford University Press, 2021. — 414 p. — ISBN: 9780192897879 (hbk.), ISBN: 9780192897886 (pbk.)This book was developed to give readers an introduction to the practical side of game data science. Before we discuss what that means, let’s delve a bit deeper into what “game data science” means. Game data science is a term that we use to denote a process composed of methods and techniques by which an analyst or a data scientist can make sense of data to allow decision-makers in a game company to make informed decisions. The type of data used, and stakeholders involved can vary from company to company. For example, analysts at Riot use gameplay data collected from players to make decisions about the design of the game. In such cases, game data scientists will analyze data to come up with patterns that they can communicate to the design team, allowing them to adjust their designs. However, this is not the only reason to analyze data from games.