Force-velocity profile based training to improve vertical jump performance a systematic review and meta analysis

Abstract

This systematic review and meta-analysis evaluated the effects of training optimized to correct deficits in vertical force-velocity (FV) profiles compared to non-optimized training. Outcomes included changes in the FV profile, vertical jump height, and maximal power. Searches followed PRISMA guidelines and were conducted in PubMed, Web of Science, SPORTDiscus, and Scopus. Study quality was assessed using the PEDro scale. As of March 2025, ten studies were identified; four were eligible for meta-analysis. Individually optimized FV-based training partially corrected a force deficit, fully corrected a velocity deficit, and had little effect on an already optimum FV profile. Effects on maximal power were small to trivial and often unclear when compared with non-optimized training. There were small-moderate improvements in jump height with optimized training, but these gains were comparable to non-optimized training. Heterogeneity was small to moderate, and methodological shortcomings were noted in all studies, including those excluded from the meta-analysis. Overall, it remains unclear if FV-profile-based training outperforms standard approaches. Labeling training "optimized" or "non-optimized" may induce placebo or nocebo effects, underscoring the need for blinded, randomized controlled trials.

Keywords: Countermovement jump; Squat jump; Strength and power training; Testing of athletic performance.

Fig. 1

Preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram of the screening process.

Fig. 2

Meta-analyzed mean effects of the different types of training: green bars indicate optimized training based on the FV profile, orange bars indicate non-optimized and opposite-optimized training, and white bars are control (usual) training. The thick vertical lines are 90% confidence intervals for the overall mean effect across all possible settings (data also shown in Tables 3, 4, 5), while the thin lines indicate the 90% prediction interval (the range of values likely to contain the mean change in any new setting). The horizontal dotted lines are the smallest important positive and negative changes in the mean, demarcating trivial changes.