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

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 ($ V_{mean} $) data developed during squat jumps or three bench press throw (...
Ausführliche Beschreibung

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 ($ V_{mean} $) data developed during squat jumps or three bench press throw (BP-T). The main aim of this project was to determine which combination of three submaximal loads during BP-T result in the most accurate prediction of 1RM Smith Machine bench press strength in healthy individuals. Methods In this study combinations of three BP-T loads were used to predict 1RM Smith Machine bench press strength. Additionally, we examined whether regression models developed using peak vertical bar velocity ($ V_{peak} $), rather than $ V_{mean} $, 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 $ V_{mean} $ and $ V_{peak} $ 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 $ V_{mean} $ or $ V_{peak} $ 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 $ V_{mean} $ and $ V_{peak} $ during BP-T over three loads, with the most precise models using $ V_{peak} $ during loads representing 30, 40 and 50% of 1RM (R2 = 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. Ausführliche Beschreibung

Autor*in:	Sayers, Mark G. L. [verfasserIn] Schlaeppi, Michel Hitz, Marina Lorenzetti, Silvio

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	Strength assessment Dynamic strength Predictive models Bench press throws

Anmerkung:	© The Author(s). 2018

Übergeordnetes Werk:	Enthalten in: BMC sports science, medicine & rehabilitation - London : BioMed Central, 2013, 10(2018), 1 vom: 29. Mai
Übergeordnetes Werk:	volume:10 ; year:2018 ; number:1 ; day:29 ; month:05

Links:	Volltext

DOI / URN:	10.1186/s13102-018-0099-z

Katalog-ID:	SPR030264316