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In an interactive digital-game, traces of a learner’s progress, problem-solving attempts, self-expressions and social communications can entail highly detailed and time-sensitive computer-based documentation of the context, actions, processes and products. This talk will present measurement and analysis considerations that are needed to address the challenges of finding patterns and making inferences based on these data. Methods based in data-mining, machine learning, model-building and complexity theory form a new theoretical foundation for dealing with the challenges of time sensitivity, spatial relationships, multiple layers of aggregations at different scales, and the dynamics of complex behavior spaces. Examples of these considerations in game-based learning analytics are presented and discussed, with implications for game-based e-learning design.