Adversarial team games are tricky because players have different information, making it hard to find the best strategy. Existing methods use complex techniques like Linear Programming, but they limit the use of helpful tools. Our new approach turns team games into simpler two-player games, where one player coordinates the team's actions based on shared information. This new game can capture all the details of the original game, but not the other way around. By using our method, we can make the game tree much smaller without losing important information. We tested our approach on poker games and found it to be effective.