—Fitts’ law is a fundamental tool in measuring the capacity of the human motor system. It measures information throughput in terms of the tradeoff between the speed and accuracy of aimed movements. However, it is, by definition, confined to prescribed stimulus-response conditions and it leaves out complex skilled performance produced irrespective of the environment. We revisit the information-theoretic basis of Fitts’ law with the goal of generalizing it into unconstrained movement. The proposed new metric is based on a subjects ability to accurately reproduce a movement pattern. It can accommodate recorded movement of any duration and composition, and involving contributions of any part(s) of the body. We demonstrate the metric by analyzing publicly available motion capture data. Possible applications include human-computer interaction, sports science, and clinical diagnosis.