The primary objective was to examine the utility of a novel method of detecting "actual" kinematic changes using the within-subject variation. Twenty firefighters were assigned to one of two groups (lifting or firefighting). Participants performed 25 repetitions of two lifting or firefighting tasks, in three sessions. The magnitude and within-subject variation of several discrete kinematic measures were computed. Sequential averages of each variable were used to derive a cubic, quadratic and linear regression equation. The efficacy of each equation was examined by contrasting participants' sequential means to their 25-trial mean±1SD and 2SD. The magnitude and within-subject variation of each dependent measure was repeatable for all tasks; however, each participant did not exhibit the same movement patterns as the group. The number of instances across all variables, tasks and testing sessions whereby the 25-trial mean±1SD was contained within the boundaries established by the regression equations increased as the aggregate scores included more trials. Each equation achieved success in at least 88% of all instances when three trials were included in the sequential mean (95% with five trials). The within-subject variation may offer a means to examine participant-specific changes without having to collect a large number of trials.