Abstract

BackgroundNumerous 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.MethodsIn 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).ResultsRepeated 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 (R2 = 0.96, SSE = 4.2 kg).ConclusionsThese 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.

Highlights

  • Numerous methods have been proposed that use submaximal loads to predict one repetition maximum (1RM)

  • analysis of variance (ANOVA) testing indicated that Mean vertical propulsive velocity (Vmean) and Peak vertical lifting velocity (Vpeak) both showed large, significant reductions (P < 0.001, Effect Size (ES) > 1.2) for each respective increase in relative bench press throw (BP-T) load, except for Vmean between 40 and 50% of One repetition maximum (1RM) (Fig. 2)

  • Results showed that the mean values for slope and Vmean0 at each of the load ranges differed significantly depending on whether Vmean or Vpeak were used in the prediction models (Table 1)

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Summary

Introduction

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. The quantification of the maximum load that can be lifted through a full range of motion, or one repetition maximum (1RM), is fundamental to the design of resistance training programs [1]. The direct determination of 1RM suffers from a number of pragmatic

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