Countermovement Jump and Squat Jump Force-Time Curve Analysis in Control and Fatigue Conditions

Hughes, S, Warmenhoven, J, Haff, GG, Chapman, DW, and Nimphius, S. Countermovement jump and squat jump force-time curve analysis in control and fatigue conditions. J Strength Cond Res 36(10): 2752-2761, 2022-This study aimed to reanalyze previously published discrete force data from countermovement jumps (CMJs) and squat jumps (SJs) using statistical parametric mapping (SPM), a statistical method that enables analysis of data in its native, complete state. Statistical parametric mapping analysis of 1-dimensional (1D) force-time curves was compared with previous zero-dimensional (0D) analysis of peak force to assess sensitivity of 1D analysis. Thirty-two subjects completed CMJs and SJs at baseline, 15 minutes, 1, 24, and 48 hours following fatigue and control conditions in a pseudo random cross-over design. Absolute (CMJ(ABS)/SJ(ABS)) and time-normalized (CMJ(NORM)/SJ(NORM)) force-time data were analyzed using SPM 2-way repeated measures analysis of variance with significance accepted at alpha = 0.05. The SPM indicated a magnitude of difference between force-time data with main effects for time (p < 0.001) and interaction (p < 0.001) observed in CMJ(ABS), SJ(ABS,) and SJ(NORM,) whereas previously published 0D analysis reported no 2-way interaction in CMJ and SJ peak force. This exploratory research demonstrates the strength of SPM to identify changes between entire movement force-time curves. Continued development and use of SPM analysis techniques could present the opportunity for refined assessment of athlete fatigue and readiness with the analysis of complete force-time curves.

Automated summary

This study reanalyzed force data from countermovement jumps and squat jumps using statistical parametric mapping (SPM). The results showed that SPM can accurately assess changes in the entire force-time curve, providing an opportunity for a more refined assessment of athlete fatigue and readiness.