Expertise is easy to identify in retrospect. It is the most ex- pert player who wins the meet and the most proficient team that wins the playoffs. However, sometimes during play we see a masterful move that clearly separates one player from the competition. Our goal, in this work, is to identify the masterful moves or elements of expertise that predict the con- tinuum of performance in the game of Tetris. As a first step we have collected data from a wide variety of Tetris Tourna- ment players and used it to derive metrics of global, local, and immediate interactions. Here we present statistical models of these data and report the initial success of these models at predicting level of expertise.