<p>Reaction-time measurements play a crucial role in assessing cognitive and sensory processing, with applications in functional clinical diagnostics such as eye-movement perimetry (EMP) for the detection of glaucoma. However, reaction-time distributions are typically right-skewed, complicating statistical analysis and requiring large numbers of repetitions for reliable parameter estimation. One well-known transformation to normalise reaction-time distributions is taking their reciprocal, called ‘speed’ or ‘promptness’ (unit 1/s). Using the promptness transformation for individual visual-field locations typically normalises the corresponding reaction-time distributions and enables more efficient statistical analysis. This study investigated whether pooling promptness across visual-field locations maintains sufficient normality for robust parameter estimation, even with sparse data typical of clinical applications, such as EMP. The results demonstrate that pooled promptness distributions generally retain normal-like properties in normal vision and glaucoma, allowing for efficient estimation of key distribution parameters (mean and standard deviation) with a minimal number of repetitions. These findings suggest that promptness-based metrics could serve as clinically relevant summary indices for visual-function assessment, similar to mean deviation (MD) in standard perimetry. While the reciprocal transformation of reaction time is well established, its targeted application in visual-field analysis via EMP and the robustness to pooling across stimulus conditions, that is, visual-field locations, has not been explored systematically. This study shows that promptness enables compact, interpretable metrics for EMP, even with sparse data. By reducing data collection demands while preserving statistical rigour, this approach offers a promising framework for enhancing the efficiency and applicability of EMP in clinical and research settings.</p>