The gallop is the preferred gait by mammals for agile traversal through terrain. This motion is intrinsically complex as the feet are used individually and asymmetrically. Simple models provide a conceptual framework for understanding this gait. In this light, this paper considers the footfall projections as suggested by an impulse model for galloping as a measurement simplifying strategy. Instead of concentrating on forces and inverse dynamics, this view focuses observations on leg motion (footfalls and stance periods) for subsequent gallop analysis and parameter estimation. In practice, this eases experiments (particularly for IR-based motion capture) by extending the experimental workspace, removing the need for single-leg contact force-plate measurements, and reducing the marker set. This provides shorter setup times, and it reduces postprocessing as data are less likely to suffer from occlusion, errant correspondence, and tissue flexion. This approach is tested using with three canine subjects (ranging from 8 to 24 kg) performing primarily rotary gallops down a 15 m runway. Normalized results are in keeping with insights from previous animal and legged robot studies and are consistent with motions suggested by said impulse model.