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Cluster Set Loading in the Back Squat: Kinetic and Kinematic Implications. | LitMetric

Cluster Set Loading in the Back Squat: Kinetic and Kinematic Implications.

J Strength Cond Res

Department of Sport, Exercise, Recreation, and Kinesiology, Center of Excellence for Sport Science and Coach Education, East Tennessee State University, Johnson City, Tennessee.

Published: July 2019

AI Article Synopsis

Article Abstract

Wetmore, A, Wagle, JP, Sams, ML, Taber, CB, DeWeese, BH, Sato, K, and Stone, MH. Cluster set loading in the back squat: Kinetic and kinematic implications. J Strength Cond Res 33(7S): S19-S25, 2019-As athletes become well trained, they require greater stimuli and variation to force adaptation. One means of adding additional variation is the use of cluster loading. Cluster loading involves introducing interrepetition rest during a set, which in theory may allow athletes to train at higher absolute intensities for the same volume. The purpose of this study was to investigate the kinetic and kinematic implications of cluster loading as a resistance training programming tactic compared with traditional loading (TL). Eleven resistance-trained men (age = 26.75 ± 3.98 years, height = 181.36 ± 5.96 cm, body mass = 89.83 ± 10.66 kg, and relative squat strength = 1.84 ± 0.34) were recruited for this study. Each subject completed 2 testing sessions consisting of 3 sets of 5 back squats at 80% of their 1 repetition maximum with 3 minutes of interset rest. Cluster loading included 30 seconds of interrepetition rest with 3 minutes of interset rest. All testing was performed on dual-force plates sampling at 1,000 Hz, and the barbell was connected to 4 linear position transducers sampling at 1,000 Hz. Both conditions had similar values for peak force, concentric average force, and eccentric average force (p = 0.25, effect size (ES) = 0.09, p = 0.25, ES = 0.09, and p = 0.60, ES = 0.04, respectively). Cluster loading had significantly higher peak power (PP) (p < 0.001, ES = 0.77), peak and average velocities (p < 0.001, ES = 0.77, and p < 0.001, ES = 0.81, respectively), lower times to PP and velocity (p < 0.001, ES = -0.68, and p < 0.001, ES = -0.68, respectively) as well as greater maintenance of time to PP (p < 0.001, ES = 1.57). These results suggest that cluster loading may be superior to TL when maintaining power output and time point variables is the desired outcome of training.

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http://dx.doi.org/10.1519/JSC.0000000000002972DOI Listing

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