Background: Due to the variety of etiological factors in chronic low back pain (CLBP), there is significant variability in functional measurements. Objects: This study aimed to determine if using metrics in addition to inferential statistics could change how the impact of poor prognosis risk for pain among volunteers with CLBP is interpreted. Methods: In this cross-sectional observational study, 74 adult volunteers were allocated to four groups: a pain-free control group (CG) and three CLBP groups stratified by the STarT Back Screening Tool into low (LR), medium (MR) and high risk (HR). Spatiotemporal gait parameters outcomes were self-selected walking speed (SWS), optimum walking speed (OWS) and the locomotor rehabilitation index (LRI). Data were analyzed using a generalized estimating equation model. Reproducibility, responsiveness (minimum detectable change [MDC]) and effect sizes were also computed. Results: No differences were found for OWS. SWS and LRI were significantly higher in CG than in all CLBP groups, but observed differences did not exceed MDC, indicating they are likely to reflect measurement error. Nevertheless, large effect sizes suggest these reductions in SWS and LRI are clinically meaningful. Comparisons among the LR, MR, and HR groups revealed no significant differences or meaningful effect sizes. Conclusion: Combining complementary metrics with inferential statistics confirms that individuals with CLBP walk more slowly and exhibit lower LRI than pain-free controls, while prognostic risk strata do not influence these spatiotemporal gait parameters.