Fitts' law has been widely employed as a research method for analyzing tasks within the domain of Human-Computer Interaction (HCI). However, its application to non-computer tasks has remained limited. This study aims to extend the application of Fitts' law to the realm of sports, specifically focusing on squash. Squash is a high-intensity sport that requires quick movements and precise shots. Our research investigates the effectiveness of utilizing Fitts' law to evaluate the task difficulty and effort level associated with executing and responding to various squash shots. By understanding the effort/information rate required for each shot, we can determine which shots are more effective in making the opponent work harder. Additionally, this knowledge can be valuable for coaches in designing training programs. However, since Fitts' law was primarily developed for human-computer interaction, we adapted it to fit the squash scenario. This paper provides an overview of Fitts' law and its relevance to sports, elucidates the motivation driving this investigation, outlines the methodology employed to explore this novel avenue, and presents the obtained results, concluding with key insights. We conducted experiments with different shots and players, collecting data on shot speed, player movement time, and distance traveled. Using this data, we formulated a modified version of Fitts' law specifically for squash. The results provide insights into the difficulty and effectiveness of various shots, offering valuable information for both players and coaches in the sport of squash.
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