Video games are becoming an important part of digital library collections due to increasing popularity and the acknowledgement of their significance as cultural artifacts. In order to support robust search and browse functions, it is imperative to develop a metadata schema to effectively represent this medium. The potential of mood metadata in the domain of video game classification is little explored, despite the value given to it by gamers in user studies. Here, we present a Controlled Vocabulary (CV) for moods related to video games with 17 defined mood terms, equivalent terms, and game examples. This CV will enable catalogers to organize video games by mood, allowing mood to be used for search and collocation. In order to evaluate the applicability of this CV and discover which terms are most relevant for video games, we annotated the mood of a sample collection of 617 video game titles. In this poster, we discuss the issues and challenges we encountered in the creation and evaluation of the current CV and our future research goals.