  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.
