Harry G. Banyard

Reliability and validity of the load-velocity relationship to predict the 1RM back squat

Abstract Banyard, HG, Nosaka, K, and Haff, GG. Reliability and validity of the load–velocity relationship to predict the 1RM back squat. J Strength Cond Res 31(7): 1897–1904, 2017—This study investigated the reliability and validity of the load–velocity relationship to predict the free-weight back squat one repetition maximum (1RM). Seventeen strength-trained males performed three 1RM assessments on 3 separate days. All repetitions were performed to full depth with maximal concentric effort. Predicted 1RMs were calculated by entering the mean concentric velocity of the 1RM (V1RM) into an individualized linear regression equation, which was derived from the load–velocity relationship of 3 (20, 40, 60% of 1RM), 4 (20, 40, 60, 80% of 1RM), or 5 (20, 40, 60, 80, 90% of 1RM) incremental warm-up sets. The actual 1RM (140.3 ± 27.2 kg) was very stable between 3 trials (ICC = 0.99; SEM = 2.9 kg; CV = 2.1%; ES = 0.11). Predicted 1RM from 5 warm-up sets up to and including 90% of 1RM was the most reliable (ICC = 0.92; SEM = 8.6 kg; CV = 5.7%; ES = −0.02) and valid (r = 0.93; SEE = 10.6 kg; CV = 7.4%; ES = 0.71) of the predicted 1RM methods. However, all predicted 1RMs were significantly different (p ⩽ 0.05; ES = 0.71–1.04) from the actual 1RM. Individual variation for the actual 1RM was small between trials ranging from −5.6 to 4.8% compared with the most accurate predictive method up to 90% of 1RM, which was more variable (−5.5 to 27.8%). Importantly, the V1RM (0.24 ± 0.06 m·s−1) was unreliable between trials (ICC = 0.42; SEM = 0.05 m·s−1; CV = 22.5%; ES = 0.14). The load–velocity relationship for the full depth free-weight back squat showed moderate reliability and validity but could not accurately predict 1RM, which was stable between trials. Thus, the load–velocity relationship 1RM prediction method used in this study cannot accurately modify sessional training loads because of large V1RM variability.

Periodization Strategies in Older Adults: Impact on Physical Function and Health

PURPOSE This study compared the effect of periodized versus nonperiodized (NP) resistance training (RT) on physical function and health outcomes in older adults. METHODS Forty-one apparently healthy untrained older adults (women = 21, men = 20; 70.9 ± 5.1 yr; 166.3 ± 8.2 cm; 72.9 ± 13.4 kg) were recruited and randomly stratified to a NP, block periodized, or daily undulating periodized training group. Outcome measures were assessed at baseline and after a 22-wk × 3 d·wk RT intervention, including; anthropometrics, body composition, blood pressure and biomarkers, maximal strength, functional capacity, balance confidence, and quality of life. RESULTS Thirty-three subjects satisfied all study requirements and were included in analyses (women = 17, men = 16; 71.3 ± 5.4 yr; 166.3 ± 8.5 cm; 72.5 ± 13.7 kg). The main finding was that all three RT models produced significant improvements in several physical function and physiological health outcomes, including; systolic blood pressure, blood biomarkers, body composition, maximal strength, functional capacity and balance confidence, with no between-group differences. CONCLUSIONS Periodized RT, specifically block periodization and daily undulating periodized, and NP RT are equally effective for promoting significant improvements in physical function and health outcomes among apparently healthy untrained older adults. Therefore, periodization strategies do not appear to be necessary during the initial stages of RT in this population. Practitioners should work toward increasing RT participation in the age via feasible and efficacious interventions targeting long-term adherence in minimally supervised settings.

Identifying the Physical Fitness, Anthropometric and Athletic Movement Qualities Discriminant of Developmental Level in Elite Junior Australian Football: Implications for the Development of Talent

Abstract Gaudion, SL, Doma, K, Sinclair, W, Banyard, HG, and Woods, CT. Identifying the physical fitness, anthropometric and athletic movement qualities discriminant of developmental level in elite junior Australian football: implications for the development of talent. J Strength Cond Res 31(7): 1830–1839, 2017—This study aimed to identify the physical fitness, anthropometric and athletic movement qualities discriminant of developmental level in elite junior Australian football (AF). From a total of 77 players, 2 groups were defined according to their developmental level; under 16 (U16) (n = 40, 15.6 to 15.9 years), and U18 (n = 37, 17.1 to 17.9 years). Players performed a test battery consisting of 7 physical fitness assessments, 2 anthropometric measurements, and a fundamental athletic movement assessment. A multivariate analysis of variance tested the main effect of developmental level (2 levels: U16 and U18) on the assessment criterions, whilst binary logistic regression models and receiver operating characteristic (ROC) curves were built to identify the qualities most discriminant of developmental level. A significant effect of developmental level was evident on 9 of the assessments (d = 0.27–0.88; p ⩽ 0.05). However, it was a combination of body mass, dynamic vertical jump height (nondominant leg), repeat sprint time, and the score on the 20-m multistage fitness test that provided the greatest association with developmental level (Akaikes information criterion = 80.84). The ROC curve was maximized with a combined score of 180.7, successfully discriminating 89 and 60% of the U18 and U16 players, respectively (area under the curve = 79.3%). These results indicate that there are distinctive physical fitness and anthropometric qualities discriminant of developmental level within the junior AF talent pathway. Coaches should consider these differences when designing training interventions at the U16 level to assist with the development of prospective U18 AF players.

Validity of Various Methods for Determining Velocity, Force, and Power in the Back Squat

PURPOSE To examine the validity of 2 kinematic systems for assessing mean velocity (MV), peak velocity (PV), mean force (MF), peak force (PF), mean power (MP), and peak power (PP) during the full-depth free-weight back squat performed with maximal concentric effort. METHODS Ten strength-trained men (26.1 ± 3.0 y, 1.81 ± 0.07 m, 82.0 ± 10.6 kg) performed three 1-repetition-maximum (1RM) trials on 3 separate days, encompassing lifts performed at 6 relative intensities including 20%, 40%, 60%, 80%, 90%, and 100% of 1RM. Each repetition was simultaneously recorded by a PUSH band and commercial linear position transducer (LPT) (GymAware [GYM]) and compared with measurements collected by a laboratory-based testing device consisting of 4 LPTs and a force plate. RESULTS Trials 2 and 3 were used for validity analyses. Combining all 120 repetitions indicated that the GYM was highly valid for assessing all criterion variables while the PUSH was only highly valid for estimations of PF (r = .94, CV = 5.4%, ES = 0.28, SEE = 135.5 N). At each relative intensity, the GYM was highly valid for assessing all criterion variables except for PP at 20% (ES = 0.81) and 40% (ES = 0.67) of 1RM. Moreover, the PUSH was only able to accurately estimate PF across all relative intensities (r = .92-.98, CV = 4.0-8.3%, ES = 0.04-0.26, SEE = 79.8-213.1 N). CONCLUSIONS PUSH accuracy for determining MV, PV, MF, MP, and PP across all 6 relative intensities was questionable for the back squat, yet the GYM was highly valid at assessing all criterion variables, with some caution given to estimations of MP and PP performed at lighter loads.

Cluster Sets Permit Greater Mechanical Stress Without Decreasing Relative Velocity.

PURPOSE To determine the effects of intraset rest frequency and training load on muscle time under tension, external work, and external mechanical power output during back-squat protocols with similar changes in velocity. METHODS Twelve strength-trained men (26.0 ± 4.2 y, 83.1 ± 8.8 kg, 1.75 ± 0.06 m, 1.88:0.19 one-repetition-maximum [1RM] body mass) performed 3 sets of 12 back squats using 3 different set structures: traditional sets with 60% 1RM (TS), cluster sets of 4 with 75% 1RM (CS4), and cluster sets of 2 with 80% 1RM (CS2). Repeated-measures ANOVAs were used to determine differences in peak force (PF), mean force (MF), peak velocity (PV), mean velocity (MV), peak power (PP), mean power (MP), total work (TW), total time under tension (TUT), percentage mean velocity loss (%MVL), and percentage peak velocity loss (%PVL) between protocols. RESULTS Compared with TS and CS4, CS2 resulted in greater MF, TW, and TUT in addition to less MV, PV, and MP. Similarly, CS4 resulted in greater MF, TW, and TUT in addition to less MV, PV, and MP than TS did. There were no differences between protocols for %MVL, %PVL, PF, or PP. CONCLUSIONS These data show that the intraset rest provided in CS4 and CS2 allowed for greater external loads than with TS, increasing TW and TUT while resulting in similar PP and %VL. Therefore, cluster-set structures may function as an alternative method to traditional strength- or hypertrophy-oriented training by increasing training load without increasing %VL or decreasing PP.

Comparison of velocity-based and traditional 1RM-percent-based prescription on acute kinetic and kinematic variables

PURPOSE To compare kinetic and kinematic data from 3 different velocity-based training sessions and a 1-repetition-maximum (1RM)-percent-based training (PBT) session using full-depth, free-weight back squats with maximal concentric effort. METHODS Fifteen strength-trained men performed 4 randomized resistance-training sessions 96 h apart: PBT session involved 5 sets of 5 repetitions using 80% 1RM; load-velocity profile (LVP) session contained 5 sets of 5 repetitions with a load that could be adjusted to achieve a target velocity established from an individualized LVP equation at 80% 1RM; fixed sets 20% velocity loss threshold (FSVL20) session consisted of 5 sets at 80% 1RM, but sets were terminated once the mean velocity (MV) dropped below 20% of the threshold velocity or when 5 repetitions were completed per set; and variable sets 20% velocity loss threshold session comprised 25 repetitions in total, but participants performed as many repetitions in a set as possible until the 20% velocity loss threshold was exceeded. RESULTS When averaged across all repetitions, MV and peak velocity (PV) were significantly (P < .05) faster during the LVP (MV effect size [ES] = 1.05; PV ES = 1.12) and FSVL20 (MV ES = 0.81; PV ES = 0.98) sessions compared with PBT. Mean time under tension (TUT) and concentric TUT were significantly less during the LVP sessions compared with PBT. The FSVL20 sessions had significantly less repetitions, total TUT, and concentric TUT than PBT. No significant differences were found for all other measurements between any of the sessions. CONCLUSIONS Velocity-based training permits faster velocities and avoids additional unnecessary mechanical stress but maintains similar measures of force and power output compared with strength-oriented PBT in a single training session.