This chapter examines ways in which movement patterns can be analyzed as performance contexts change or as a function of learning and development. The methods described can be used to study the effects of important factors such as fatigue, injury, learning, development or training in motor performance. Overall, cluster analysis and SOMs enjoy increasing popularity among movement scientists, owing to their capacity to explore and validate different qualities in movement science and match analysis. Both methods of analysis offer a fruitful basis for characterizing and interpreting high-dimensional datasets. The need to balance exploratory and confirmatory approaches in combination with time-continuous and time-discrete approaches is one of the biggest challenges for the coming years. The willingness to apply most recent methodological developments from related disciplines is growing and offers a promising wide new field of research.
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