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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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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