The impact of test loads on the accuracy of 1RM prediction using the load-velocity relationship

Abstract Background Numerous methods have been proposed that use submaximal loads to predict one repetition maximum (1RM). One common method applies standard linear regression equations to load and average vertical lifting velocity (Vmean) data developed during squat jumps or three bench press throw...

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Main Authors: Mark G. L. Sayers, Michel Schlaeppi, Marina Hitz, Silvio Lorenzetti
Format: Article
Language:English
Published: BMC 2018-05-01
Series:BMC Sports Science, Medicine and Rehabilitation
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13102-018-0099-z
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spelling doaj-c275ab2ff4d844c1b91130157b6bf52a2020-11-24T20:50:00ZengBMCBMC Sports Science, Medicine and Rehabilitation2052-18472018-05-011011810.1186/s13102-018-0099-zThe impact of test loads on the accuracy of 1RM prediction using the load-velocity relationshipMark G. L. Sayers0Michel Schlaeppi1Marina Hitz2Silvio Lorenzetti3School of Health and Sport Sciences, University of the Sunshine CoastInstitute for Biomechanics, ETH ZürichInstitute for Biomechanics, ETH ZürichInstitute for Biomechanics, ETH ZürichAbstract Background Numerous methods have been proposed that use submaximal loads to predict one repetition maximum (1RM). One common method applies standard linear regression equations to load and average vertical lifting velocity (Vmean) data developed during squat jumps or three bench press throw (BP-T). The main aim of this project was to determine which combination of three submaximal loads during BP-T result in the most accurate prediction of 1RM Smith Machine bench press strength in healthy individuals. Methods In this study combinations of three BP-T loads were used to predict 1RM Smith Machine bench press strength. Additionally, we examined whether regression models developed using peak vertical bar velocity (Vpeak), rather than Vmean, provide the most accurate prediction of Smith Machine bench press 1RM. 1RM Smith Machine bench press strength was measured directly in 12 healthy regular weight trainers (body mass = 80.8 ± 5.7 kg). Two to three days later a linear position transducer attached to the collars on a Smith Machine was used to record Vmean and Vpeak during BP-T between 30 and 70% of 1RM (10% increments). Results Repeated measures analysis of variance testing showed that the mean values for slope and ordinate intercept for the regression models at each of the load ranges differed significantly depending on whether Vmean or Vpeak were used in the prediction models (P < 0.001). Conversely, the abscissa intercept did not differ significantly between either measure of vertical bar velocity at each load range. The key finding in this study was that 1RM Smith Machine bench press strength can be determined with high relative accuracy by examining Vmean and Vpeak during BP-T over three loads, with the most precise models using Vpeak during loads representing 30, 40 and 50% of 1RM (R 2  = 0.96, SSE = 4.2 kg). Conclusions These preliminary findings indicate that exercise programmers working with normal healthy populations can accurately predict Smith Machine 1RM bench press strength using relatively light load Smith Machine BP-T testing, avoiding the need to expose their clients to potentially injurious loads.http://link.springer.com/article/10.1186/s13102-018-0099-zStrength assessmentDynamic strengthPredictive modelsBench press throws
collection DOAJ
language English
format Article
sources DOAJ
author Mark G. L. Sayers
Michel Schlaeppi
Marina Hitz
Silvio Lorenzetti
spellingShingle Mark G. L. Sayers
Michel Schlaeppi
Marina Hitz
Silvio Lorenzetti
The impact of test loads on the accuracy of 1RM prediction using the load-velocity relationship
BMC Sports Science, Medicine and Rehabilitation
Strength assessment
Dynamic strength
Predictive models
Bench press throws
author_facet Mark G. L. Sayers
Michel Schlaeppi
Marina Hitz
Silvio Lorenzetti
author_sort Mark G. L. Sayers
title The impact of test loads on the accuracy of 1RM prediction using the load-velocity relationship
title_short The impact of test loads on the accuracy of 1RM prediction using the load-velocity relationship
title_full The impact of test loads on the accuracy of 1RM prediction using the load-velocity relationship
title_fullStr The impact of test loads on the accuracy of 1RM prediction using the load-velocity relationship
title_full_unstemmed The impact of test loads on the accuracy of 1RM prediction using the load-velocity relationship
title_sort impact of test loads on the accuracy of 1rm prediction using the load-velocity relationship
publisher BMC
series BMC Sports Science, Medicine and Rehabilitation
issn 2052-1847
publishDate 2018-05-01
description Abstract Background Numerous methods have been proposed that use submaximal loads to predict one repetition maximum (1RM). One common method applies standard linear regression equations to load and average vertical lifting velocity (Vmean) data developed during squat jumps or three bench press throw (BP-T). The main aim of this project was to determine which combination of three submaximal loads during BP-T result in the most accurate prediction of 1RM Smith Machine bench press strength in healthy individuals. Methods In this study combinations of three BP-T loads were used to predict 1RM Smith Machine bench press strength. Additionally, we examined whether regression models developed using peak vertical bar velocity (Vpeak), rather than Vmean, provide the most accurate prediction of Smith Machine bench press 1RM. 1RM Smith Machine bench press strength was measured directly in 12 healthy regular weight trainers (body mass = 80.8 ± 5.7 kg). Two to three days later a linear position transducer attached to the collars on a Smith Machine was used to record Vmean and Vpeak during BP-T between 30 and 70% of 1RM (10% increments). Results Repeated measures analysis of variance testing showed that the mean values for slope and ordinate intercept for the regression models at each of the load ranges differed significantly depending on whether Vmean or Vpeak were used in the prediction models (P < 0.001). Conversely, the abscissa intercept did not differ significantly between either measure of vertical bar velocity at each load range. The key finding in this study was that 1RM Smith Machine bench press strength can be determined with high relative accuracy by examining Vmean and Vpeak during BP-T over three loads, with the most precise models using Vpeak during loads representing 30, 40 and 50% of 1RM (R 2  = 0.96, SSE = 4.2 kg). Conclusions These preliminary findings indicate that exercise programmers working with normal healthy populations can accurately predict Smith Machine 1RM bench press strength using relatively light load Smith Machine BP-T testing, avoiding the need to expose their clients to potentially injurious loads.
topic Strength assessment
Dynamic strength
Predictive models
Bench press throws
url http://link.springer.com/article/10.1186/s13102-018-0099-z
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