In the hedonic coalition formation game model Roles Based Hedonic Games (RBHG), agents view teams as compositions of available roles. An agent's utility for a partition is based upon which roles she and her teammates fulfill within the coalition. I show positive results for finding optimal or stable role matchings given a partitioning into teams. In settings such as massively multiplayer online games, a central authority assigns agents to teams but not necessarily to roles within them. For such settings, I consider the problems of optimizing expected utility and expected stability in RBHG. I show that the related optimization problems for partitioning are NP-hard. I introduce a local search heuristic method for approximating such solutions. I validate the heuristic by comparison to existing partitioning approaches using real-world data scraped from League of Legends games.