The applications of data science techniques to game learning analytics data obtained from serious games can provide a more scientific approach to improve the serious games lifecycle. Honing on the game analytics data is possible to use an evidence-based approach to the design, evaluation and deployment of serious games. For instance, the use of game analytics techniques on the users gameplay interaction data can be applied to systematize the evaluation of games, and allow both teachers and institutions to make better evidence-based decisions. The talk will address some of the new possibilities offered by game learning analytics and what are the requirements (e.g. standards) for its generalization in real settings (including some of the ethical implications).