Literature DB >> 21399537

Jump peak power assessment through power prediction equations in different samples.

Amador J Lara-Sánchez1, María L Zagalaz, Daniel Berdejo-Del-Fresno, Emilio J Martínez-López.   

Abstract

The aim of this study was to describe the characteristics of jump capacity in a group of secondary school students and to develop 2 specific equations-applied to boys and girls, respectively, to estimate the jump power of secondary school students. Four hundred and fifty-six boys (age, 14.1 ± 0.8 years; mass, 61.9 ± 15.7 kg; height, 1.64 ± 0.10 m) and 465 girls (age, 14.1 ± 0.9 years; mass, 55.1 ± 10.0 kg; height, 1.58 ± 0.07 m), all of them secondary school students, volunteered to participate in this study. They performed a vertical jump test (Abalakov) on a force platform, and jump height and peak power were measured. Most importantly, peak power was also estimated through a series of previously established power equations. For the purpose of establishing statistically significant differences, a p value ≤ 0.05 was fixed. The equations proposed by Canavan and Vesconvi, and Harman were the most precise with respect to actual power, reaching a percentage of 1.9-2.1 and 3.6-4.1%, respectively. The equations by Sayers and Lara showed a greater difference in percentage (9.9-12.4 and 22.4-24.2%, respectively) with that of actual power. Similar results were not obtained in other studies, which means that a specific equation will be required according to the characteristics of the assessed sample. Two equations specifically addressed to secondary school students will be established in this article: boys: ([61.8 jump height (cm)] + [37.1 body mass (kg)] - 1,941.6); girls: ([31 jump height (cm)] + [45 body mass (kg)] - 1,045.4). Crossvalidation tests that were done to prove the validity of said equations showed positive results. Practical applications: Those teachers who wish to estimate the jump power of their pupils can use these equations and thereby calculate jump power by the indirect method from jump height and body mass index, without any need to use any expensive tools.

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Year:  2011        PMID: 21399537     DOI: 10.1519/JSC.0b013e3181e06ef8

Source DB:  PubMed          Journal:  J Strength Cond Res        ISSN: 1064-8011            Impact factor:   3.775


  5 in total

1.  When Jump Height is not a Good Indicator of Lower Limb Maximal Power Output: Theoretical Demonstration, Experimental Evidence and Practical Solutions.

Authors:  Jean-Benoit Morin; Pedro Jiménez-Reyes; Matt Brughelli; Pierre Samozino
Journal:  Sports Med       Date:  2019-07       Impact factor: 11.136

2.  Potential Energy as an Alternative for Assessing Lower Limb Peak Power in Children: A Bayesian Hierarchical Analysis.

Authors:  Jorge R Fernandez-Santos; Jose V Gutierrez-Manzanedo; Pelayo Arroyo-Garcia; Jose Izquierdo-Jurado; Jose L Gonzalez-Montesinos
Journal:  Int J Environ Res Public Health       Date:  2022-05-22       Impact factor: 4.614

3.  Determining jumping performance from a single body-worn accelerometer using machine learning.

Authors:  Mark G E White; Neil E Bezodis; Jonathon Neville; Huw Summers; Paul Rees
Journal:  PLoS One       Date:  2022-02-10       Impact factor: 3.240

4.  Lower-Limb Power cannot be Estimated Accurately from Vertical Jump Tests.

Authors:  Jean-François Tessier; Fabien-A Basset; Martin Simoneau; Normand Teasdale
Journal:  J Hum Kinet       Date:  2013-10-08       Impact factor: 2.193

5.  Developing a new muscle power prediction equation through vertical jump power output in adolescent women.

Authors:  Aziz Güçlüöver; Mehmet Gülü
Journal:  Medicine (Baltimore)       Date:  2020-06-19       Impact factor: 1.817

  5 in total

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