Secondary Logo

Institutional members access full text with Ovid®

Development of 1RM Prediction Equations for Bench Press in Moderately Trained Men

Macht, Jordan W.; Abel, Mark G.; Mullineaux, David R.; Yates, James W.

Journal of Strength and Conditioning Research: October 2016 - Volume 30 - Issue 10 - p 2901–2906
doi: 10.1519/JSC.0000000000001385
Original Research

Macht, JW, Abel, MG, Mullineaux, DR, and Yates, JW. Development of 1RM prediction equations for bench press in moderately trained men. J Strength Cond Res 30(10): 2901–2906, 2016—There are a variety of established 1 repetition maximum (1RM) prediction equations, however, very few prediction equations use anthropometric characteristics exclusively or in part, to estimate 1RM strength. Therefore, the purpose of this study was to develop an original 1RM prediction equation for bench press using anthropometric and performance characteristics in moderately trained male subjects. Sixty male subjects (21.2 ± 2.4 years) completed a 1RM bench press and were randomly assigned a load to complete as many repetitions as possible. In addition, body composition, upper-body anthropometric characteristics, and handgrip strength were assessed. Regression analysis was used to develop a performance-based 1RM prediction equation: 1RM = 1.20 repetition weight + 2.19 repetitions to fatigue − 0.56 biacromial width (cm) + 9.6 (R2 = 0.99, standard error of estimate [SEE] = 3.5 kg). Regression analysis to develop a nonperformance-based 1RM prediction equation yielded: 1RM (kg) = 0.997 cross-sectional area (CSA) (cm2) + 0.401 chest circumference (cm) − 0.385%fat − 0.185 arm length (cm) + 36.7 (R2 = 0.81, SEE = 13.0 kg). The performance prediction equations developed in this study had high validity coefficients, minimal mean bias, and small limits of agreement. The anthropometric equations had moderately high validity coefficient but larger limits of agreement. The practical applications of this study indicate that the inclusion of anthropometric characteristics and performance variables produce a valid prediction equation for 1RM strength. In addition, the CSA of the arm uses a simple nonperformance method of estimating the lifter's 1RM. This information may be used to predict the starting load for a lifter performing a 1RM prediction protocol or a 1RM testing protocol.

1Department of Kinesiology and Health Promotion, University of Kentucky, Lexington, Kentucky; and

2School of Sport, Coaching, and Exercise Science, University of Lincoln, United Kingdom

Address correspondence to Jordon Macht,

Copyright © 2016 by the National Strength & Conditioning Association.