Sport Mont | 2026
Authors: Geantă V.A.; de Hillerin P.J.
DOI: 10.26773/smj.260206
Journal: Sport Mont
Year: 2026
Publisher: Montenegrin Sports Academy
Document Type: Article
Open Access: All Open Access; Gold Open Access
Cited by: 0
Lower-limb average power is an important indicator of neuromuscular performance and can be assessed either indirectly through computational models derived from repetitive vertical jumps or directly using ergometers that quantify mechanical output. However, these approaches often yield different values, complicating interpretation and comparison across studies. This preliminary, exploratory within-subject study (n=5) aimed to examine discrepancies between lower-limb average power estimated from computational models applied to 15-second vertical jump tests and that measured during short-duration maximal efforts on cycle- and row-ergometers. Five male sport science university students performed a 15-second repeated vertical jump test assessed using the OptoJump Next system (Microgate, Bolzano, Italy). Average power was calculated using the Bosco, Miron Georgescu (MG), and Miron Georgescu Modified 15-second (MGM-15) formulas. Each participant subsequently completed two 20-second all-out trials on the Concept2 BikeErg and RowErg (Concept2 Inc., Morrisville, Vermont, USA). The analysis revealed a significant main effect of method (F(1.03, 4.12)=77.04, p=0.001, ηp2=0.95). The Bosco and MG equations generated substantially higher power outputs compared with both ergometer assessments (p<0.05). The MGM-15 model produced estimates not statistically different from RowErg (p>0.05), while slightly lower than those recorded on BikeErg (p<0.01). Substantial discrepancies were observed in lower-limb average power values obtained from different computational models applied to repeated vertical jump data. While classical equations produced markedly higher estimates, the MGM-15 formulation yielded power values that were closer to those obtained from direct ergometer measurements, highlighting the influence of computational assumptions on jump-derived power estimates. © 2026, Montenegrin Sports Academy. All rights reserved.
athlete performance assessment; computational modelling; ergometer; lower-limb power; vertical jump