Mouse Sensitivity in First-Person Targeting Tasks

Abstract

Mouse sensitivity in first-person targeting tasks is a highly debated issue. Recommendations within a single game can vary by a factor of 10× or more and are an active topic of experimentation in both competitive and recreational esports communities. Inspired by work in pointer-based gain optimization and extending our previous results from the first user study focused on mouse sensitivity in first-person targeting tasks (Boudaoud et al., 2023), we describe a range of optimal mouse sensitivity wherein players perform statistically significantly better in task completion time and throughput. For tasks involving first-person view control, mouse sensitivity is best described using the ratio between an in-game rotation of the view and corresponding physical displacement of the mouse. We discuss how this displacement-to-rotation sensitivity is incompatible with the control-display gain reported in traditional pointer-based gain studies as well as other rotational gains reported in head-controlled interface studies. We provide additional details regarding impacts of mouse dots per inch, on reported sensitivity, the distribution of spatial difficulty in our experiment, our submovement parsing algorithm, and relationships between measured parameters, further demonstrating optimal sensitivity arising from a speed-precision tradeoff. We conclude our work by updating and improving our suggestions for mouse sensitivity selection and refining directions for future work.