In complex task domains, such as games, students may exceed their teachers. Such tasks afford diverse means to tradeoff one type of performance for another, combining task elements in novel ways to yield method variations and strategy discoveries that, if mastered, might produce large or small leaps in performance. For the researcher interested in the development of extreme expertise in the wild, the problem posed by such tasks is “where to look” to capture the explorations, trials, errors, and successes that eventually lead to the invention of superior performance. In this paper, we present several successful discoveries of methods for superior performance. For these discoveries we used Symbolic Aggregate Approximation as our method of identifying changepoints within score progressions in the venerable game of Space Fortress. By decomposing performance at these changepoints, we find previously unknown strategies that even the designers of the task had not anticipated.