One of the challenges that a computer game developer meets when creating a new game is setting the difficulty ``right''. Not only it is a complicated task to balance all the game parameters, but the developer also needs to cater for players with very different skill levels. Providing a game with an ability to automatically scale the difficulty depending on the current player would make the games more engaging over longer time. In this paper we propose a simple approach based on ranking of available strategies and show that it leads to a surprisingly good online adaptive agent. We evaluate the performance of the developed agent in the games against algorithmic as well as human opponents.