In this article, we trained what we believe to be the first MT system adapted to video game translation and show that very limited in-domain data is enough to largely surpass publicly available systems, while also revealing interesting findings in the final translation. After introducing some of the challenges of video game translation, existing literature, as well as the systems and data sets used in this experiment, we provide and discuss the resulting translation as well as the potential benefits of such a system. We find that the model is able to learn typical rules and patterns of video game translations from English into French, indicating that the case of video game machine translation could prove useful given the encouraging results and the specific working conditions of translators this field. As with other use cases of MT in cultural sectors, however, we believe this is heavily dependent on the proper implementation of the tool, which we think could to stimulate creativity.