Game data science, defined as the practice of deriving insights from game data, has created a revolution in the globalgame industry—informing and enhancing production, design, and development processes. Almost all game companies collect data from games and have adopted some type of game data science, —yet, there has been no definitive resource for professionals, academics and students in this crucial and rapidly developing aspect of games until now.

Games Data Science delivers a thorough introduction to this new domain and serves as a definitive guide to the methods and practices of computer science, analytics, and data science as applied to video games. It is the ideal resource for professional learners and students seeking to understand how data science is used within the game development and production cycle, as well as within the interdisciplinary field of games research.

Organized into chapters that integrate laboratory and real-life game data examples, this book provides a unique resource to train and educate both industry professionals and academic experts about the use of game data science, with practical exercises and examples on how such processes are implemented and used, interweaving theoretical learning with practical application throughout.

For additional details, please see the book’s companion website:

Edited by Magy Seif El-Nasr, Truong-Huy D. Nguyen, Alessandro Canossa and Anders Drachen.