The end-spurt and U-shape reflect common pacing patterns across numerous fields. To date, however, the literature lacks a parsimonious, applicable account for these effects. Here, I propose a novel causal explanation for these effects – perceived impact. As one perceives his/her actions to better affect progress within a task, the higher one’s motivation. The higher one’s motivation in a given time, the better his/her performance. To illustrate, during a race, if an athlete has five more laps to go, completing a given lap closes 20% of the remaining distance (1/5 laps = 20%). Alternatively, when the athlete has two laps to go, each lap represents 50% of the remaining distance. In the latter case, the impact of completing a single lap on goal progress is perceived to be higher. Accordingly, his/her motivation will increase near the end – giving rise to an end-spurt. I exemplify through simulations how this model can account for previous racing and research outcomes observing end-spurts and U-shaped pacing patterns. In addition to being theoretically insightful, this framework offers practical field implications for coaches and athletes by modifying counting style within sets (e.g., “3, 2, 1” instead of “13, 14, 15”), session outline (e.g., challenging sets in the end, instead of in the middle of the session), etc.