Comparison of individual and group-based load-velocity profiling as a means to dictate training load over a 6-week strength and power intervention

Application of a New Monitoring Variable: Effects of Power Loss During Squat Training on Strength Gains and Sports Performance

ABSTRACT

Zhang, M, Chen, L, Dai, J, Yang, Q, Huang, Z, He, J, Ji, H, Sun, J, and Li, D. Application of a new monitoring variable: Effects of power loss during squat training on strength gains and sports performance. J Strength Cond Res 38(4): 656-670, 2024-This study aimed to compare the effects of power loss (PL) autoregulated volume (PL10 and PL20) with standardized fixed-load (FL) prescription on strength, sports performance, and lean body mass (LBM). Thirty-five female basketball players from a sports college were randomly assigned to 3 experimental groups (PL10, n = 12; PL20, n = 12; and FL, n = 11, respectively) that performed a resistance training (RT) program with wave-like periodization for 10 weeks using the back squat exercise. Assessments performed before (Pre) and after (Post) intervention included assessed 1 repetition maximum (1RM), body composition, 20-m sprint (T20M), change of direction (COD), and jump performance, including countermovement jump with arm swing, maximum vertical jump, and reactive strength index. Three groups showed significant improvements in strength (effect size [ES]: PL10 = 2.98, PL20 = 3.14, and FL = 1.90; p < 0.001) and jump performance (ES: PL10 = 0.74, PL20 = 1.50, and FL = 0.50; p <0.05-0.001). However, PL10 and PL20 demonstrated different advantages in sports performance compared with FL (group × time interaction, p <0.05). Specifically, PL10 significantly improved COD performance (ES = -0.79 ∼ -0.53, p <0.01), whereas PL20 showed greater improvements in sprint (ES = -0.57, p <0.05) and jump performance (ES = 0.67-1.64, p <0.01-0.001). Moreover, PL10 resulted in similar gains to PL20 and beneficial improvements compared with FL in LBM, despite performing the least repetitions. Overall, the study indicates that power loss-based autoregulation induces greater gains in LBM and sports performance, as well as eliciting a higher efficiency dose response than standardized FL prescriptions, particularly for PL10. Therefore, incorporating PL monitoring in training programs is recommended, and further studies on power-based RT would be worthwhile.

The Effect of Various Training Variables on Developing Muscle Strength in Velocity-based Training: A Systematic Review and Meta-analysis

Velocity-based training is an advanced auto-regulation method that uses objective indices to dynamically regulate training loads. However, it is unclear currently how to maximize muscle strength with appropriate velocity-based training settings. To fill this gap, we conducted a series of dose-response and subgroup meta-analyses to check the effects of training variables/parameters, such as intensity, velocity loss, set, inter-set rest intervals, frequency, period, and program, on muscle strength in velocity-based training. A systematic literature search was performed to identify studies via PubMed, Web of Science, Embase, EBSCO, and Cochrane. One repetition maximum was selected as the outcome to indicate muscle strength. Eventually, twenty-seven studies with 693 trained individuals were included in the analysis. We found that the velocity loss of 15 to 30%, the intensity of 70 to 80%1RM, the set of 3 to 5 per session, the inter-set rest interval of 2 to 4 min, and the period of 7 to 12 weeks could be appropriate settings for developing muscle strength. Three periodical programming models in velocity-based training, including linear programming, undulating programming, and constant programming, were effective for developing muscle strength. Besides, changing periodical programming models around every 9 weeks may help to avoid a training plateau in strength adaption.

The Effect of Velocity Loss on Strength Development and Related Training Efficiency: A Dose-Response Meta-Analysis

The velocity loss method is often used in velocity-based training (VBT) to dynamically regulate training loads. However, the effects of velocity loss on maximum strength development and training efficiency are still unclear. Therefore, we conducted a dose-response meta-analysis aiming to fill this research gap. A systematic literature search was performed to identify studies on VBT with the velocity loss method via PubMed, Web of Science, Embase, EBSCO, and Cochrane. Controlled trials that compared the effects of different velocity losses on maximum strength were considered. One-repetition maximum (1RM) gain and 1RM gain per repetition were the selected outcomes to indicate the maximum strength development and its training efficiency. Eventually, nine studies with a total of 336 trained males (training experience/history ≥ 1 year) were included for analysis. We found a non-linear dose-response relationship (reverse U-shaped) between velocity loss and 1RM gain (pdose-response relationship < 0.05, pnon-linear relationship < 0.05). Additionally, a negative linear dose-response relationship was observed between velocity loss and 1RM gain per repetition (pdose-response relationship < 0.05, pnon-linear relationship = 0.23). Based on our findings, a velocity loss between 20 and 30% may be beneficial for maximum strength development, and a lower velocity loss may be more efficient for developing and maintaining maximum strength. Future research is warranted to focus on female athletes and the interaction of other parameters.

The effects of velocity-based versus percentage-based resistance training on athletic performances in sport-collegiate female basketball players

Introduction: The study compared the effects of 6-week (2 sessions/week) velocity-based resistance training (VBRT) and percentage-based resistance training (PBRT) on athletic performance in Sport-College female basketball players. Methods: Fifteen participants were assigned to the VBRT (n = 8) or PBRT (n = 7) groups. The load in VBRT group were determined through the sessional target velocity and velocity loss monitoring, whereas PBRT group used a fixed-load based on percentage of 1-repetition maximum (1RM). Both groups completed intervention that involved the free weight back squat and bench press using the same relative load (linear periodization from 65% to 95% 1RM). Training loads data was continuously recorded. Measurements at baseline (T0) and post-training (T2) included 1RM, countermovement-jump (CMJ), squat-jump (SJ), eccentric-utilization-ratio (EUR), drop-jump height and reactive-strength-index (DJ, DJ-RSI), plyometric-push-up (PPU), 505 change-of-direction (COD), 10-m、20-m sprint (T-10、T-20), 17 × 15 m drill-lines (17-drill), Hexagon agility, and functional movement screen (FMS). A mid-term (T1) assessment was included to investigate the short-term effects of both methods and the fluctuation of personalized 1RM. Results: No between-group differences were observed at T0 for descriptive variables (p > 0.05). Both groups showed significant improvement in strength gains for back squat and bench press, but VBRT showed likely to very likely favorable improvements in CMJ, SJ, EUR, DJ-RSI, Hexagon and COD among athletic performance. The VBRT showed likely to very likely improvements in 17-drill and DJ, while PBRT showed unclear effects. The lifted weights adjusted by VBRT method were higher than prescribed by PBRT (p < 0.05) for the same subjects. Conclusion: Compared with fixed-load PBRT, VBRT enhanced power and athletic performance despite similar strength gains. VBRT can be regarded as a more functional resistance-training method under linear periodization.

Using the Load-Velocity Profile for Predicting the 1RM of the Hexagonal Barbell Deadlift Exercise

ABSTRACT

Lopes dos Santos, M, Mann, JB, Berton, R, Alvar, B, Lockie, RG, and Dawes, JJ. Using the load-velocity profile for predicting the 1RM of the hexagonal barbell deadlift exercise. J Strength Cond Res 37(1): 220-223, 2023-The aim of this study was to determine whether bar velocity can be used to estimate the 1 repetition maximum (1RM) on the hexagonal bar deadlift (HBD). Twenty-two National Collegiate Athletic Association Division I male ice hockey players (age = 21.0 ± 1.5 years, height = 182.9 ± 7.3 cm, and body mass = 86.2 ± 7.3 kg) completed a progressive loading test using the HBD at maximum intended velocity to determine their 1RM. The mean concentric velocity was measured for each load through a linear position transducer. The a priori alpha level of significance was set at p = 0.05. The mean concentric velocity showed a very strong relationship to %1RM (R2 = 0.85). A nonsignificant difference and a trivial effect size (ES) were observed between the actual and predicted 1RM (p = 0.90, ES = -0.08). Near-perfect correlations were also discovered between the actual and predicted 1RM (R = 0.93) with low typical error and coefficient of variation (5.11 kg and 2.53%, respectively). This study presented results that add the HBD to the list of exercises with established load-velocity relationships. The predictive ability for 1RM HBD indicates that this is a viable means of prediction of 1RM.

The Effect of Load and Volume Autoregulation on Muscular Strength and Hypertrophy: A Systematic Review and Meta-Analysis

Background

Autoregulation has emerged as a potentially beneficial resistance training paradigm to individualize and optimize programming; however, compared to standardized prescription, the effects of autoregulated load and volume prescription on muscular strength and hypertrophy adaptations are unclear. Our objective was to compare the effect of autoregulated load prescription (repetitions in reserve-based rating of perceived exertion and velocity-based training) to standardized load prescription (percentage-based training) on chronic one-repetition maximum (1RM) strength and cross-sectional area (CSA) hypertrophy adaptations in resistance-trained individuals. We also aimed to investigate the effect of volume autoregulation with velocity loss thresholds ≤ 25% compared to > 25% on 1RM strength and CSA hypertrophy.

Methods

This review was performed in accordance with the PRISMA guidelines. A systematic search of MEDLINE, Embase, Scopus, and SPORTDiscus was conducted. Mean differences (MD), 95% confidence intervals (CI), and standardized mean differences (SMD) were calculated. Sub-analyses were performed as applicable.

Results

Fifteen studies were included in the meta-analysis: six studies on load autoregulation and nine studies on volume autoregulation. No significant differences between autoregulated and standardized load prescription were demonstrated for 1RM strength (MD = 2.07, 95% CI – 0.32 to 4.46 kg, p = 0.09, SMD = 0.21). Velocity loss thresholds ≤ 25% demonstrated significantly greater 1RM strength (MD = 2.32, 95% CI 0.33 to 4.31 kg, p = 0.02, SMD = 0.23) and significantly lower CSA hypertrophy (MD = 0.61, 95% CI 0.05 to 1.16 cm², p = 0.03, SMD = 0.28) than velocity loss thresholds > 25%. No significant differences between velocity loss thresholds > 25% and 20–25% were demonstrated for hypertrophy (MD = 0.36, 95% CI – 0.29 to 1.00 cm², p = 0.28, SMD = 0.13); however, velocity loss thresholds > 25% demonstrated significantly greater hypertrophy compared to thresholds ≤ 20% (MD = 0.64, 95% CI 0.07 to 1.20 cm², p = 0.03, SMD = 0.34).

Conclusions

Collectively, autoregulated and standardized load prescription produced similar improvements in strength. When sets and relative intensity were equated, velocity loss thresholds ≤ 25% were superior for promoting strength possibly by minimizing acute neuromuscular fatigue while maximizing chronic neuromuscular adaptations, whereas velocity loss thresholds > 20–25% were superior for promoting hypertrophy by accumulating greater relative volume.

Protocol Registration The original protocol was prospectively registered (CRD42021240506) with the PROSPERO (International Prospective Register of Systematic Reviews).

Supplementary Information

The online version contains supplementary material available at 10.1186/s40798-021-00404-9.

The Maximum Flywheel Load: A Novel Index to Monitor Loading Intensity of Flywheel Devices

BACKGROUND

The main aim of this study was (1) to find an index to monitor the loading intensity of flywheel resistance training, and (2) to study the differences in the relative intensity workload spectrum between the FW-load and ISO-load.

METHODS

twenty-one males participated in the study. Subjects executed an incremental loading test in the squat exercise using a Smith machine (ISO-load) or a flywheel device (FW-load). We studied different association models between speed, power, acceleration, and force, and each moment of inertia was used to find an index for FW-load. In addition, we tested the differences between relative workloads among load conditions using a two-way repeated-measures test.

RESULTS

the highest r2 was observed using a logarithmic fitting model between the mean angular acceleration and moment of inertia. The intersection with the x-axis resulted in an index (maximum flywheel load, MFL) that represents a theoretical individual maximal load that can be used. The ISO-load showed greater speed, acceleration, and power outcomes at any relative workload (%MFL vs. % maximum repetition). However, from 45% of the relative workload, FW-load showed higher vertical forces.

CONCLUSIONS

MFL can be easily computed using a logarithmic model between the mean angular acceleration and moment of inertia to characterize the maximum theoretical loading intensity in the flywheel squat.

Use of Machine-Learning and Load-Velocity Profiling to Estimate 1-Repetition Maximums for Two Variations of the Bench-Press Exercise

The purpose of the current study was to compare the ability of five different methods to estimate eccentric–concentric and concentric-only bench-press 1RM from load–velocity profile data. Smith machine bench-press tests were performed in an eccentric–concentric (n = 192) and a concentric-only manner (n = 176) while mean concentric velocity was registered using a linear position transducer. Load–velocity profiles were derived from incremental submaximal load (40–80% 1RM) tests. Five different methods were used to calculate 1RM using the slope, intercept, and velocity at 1RM (minimum velocity threshold—MVT) from the load–velocity profiles: calculation with individual MVT, calculation with group average MVT, multilinear regression without MVT, regularized regression without MVT, and an artificial neural network without MVT. Mean average errors for all methods ranged from 2.7 to 3.3 kg. Calculations with individual or group MVT resulted in significant overprediction of eccentric–concentric 1RM (individual MVT: difference = 0.76 kg, p = 0.020, d = 0.17; group MVT: difference = 0.72 kg, p = 0.023, d = 0.17). The multilinear and regularized regression both resulted in the lowest errors and highest correlations. The results demonstrated that bench-press 1RM can be accurately estimated from load–velocity data derived from submaximal loads and without MVT. In addition, results showed that multilinear regression can be used to estimate bench-press 1RM. Collectively, the findings and resulting equations should be helpful for strength and conditioning coaches as they would help estimating 1RM without MVT data.

Effects of Four Different Velocity-Based Training Programming Models on Strength Gains and Physical Performance

ABSTRACT

Riscart-López, J, Rendeiro-Pinho, G, Mil-Homens, P, Costa, RS-d, Loturco, I, Pareja-Blanco, F, and León-Prados, JA. Effects of Four different velocity-based training programming models on strength gains and physical performance. J Strength Cond Res 35(3): 596-603, 2021-The aim of this study was to compare the effects of 4 velocity-based training (VBT) programming models (linear programming [LP], undulating programming [UP], reverse programming [RP], and constant programming [CP]) on the physical performance of moderately strength-trained men. Forty-three young (age: 22.9 ± 4.8 years; body mass [BM]: 71.7 ± 7.6; full squat [SQ] relative strength 1.32 ± 0.29) subjects were randomly assigned to LP (gradually increase training intensity and decrease volume), UP (volume and intensity increase or decrease repeatedly), RP (gradually increases volume and decrease intensity), and CP (maintains constant volume and intensity) groups and followed an 8-week VBT intervention using the SQ exercise and monitoring movement velocity for every repetition. All groups trained with similar relative average intensity (67.5% 1 repetition maximum [1RM]), magnitude of velocity loss within the set (20%), number of sets (3), and interset recoveries (4 minutes) throughout the training program. Pre-training and post-training measurements included predicted SQ (1RM), average velocity attained for all loads common to pre-tests and post-tests (AV), average velocity for those loads that were moved faster (AV > 1) and slower (AV < 1) than 1 m·s-1 at pre-tests, countermovement jump height (CMJ), and 20-m sprint time (T20). No significant group × time interactions were observed for any of the variables analyzed. All groups obtained similar increases (shown in effect size values) in 1RM strength (LP: 0.88; UP: 0.54; RP: 0.62; CP: 0.51), velocity-load-related variables (LP: 0.74-4.15; UP: 0.46-5.04; RP: 0.36-3.71; CP: 0.74-3.23), CMJ height (LP: 0.35; UP: 0.53; RP: 0.49; CP: 0.34), and sprint performance (LP: 0.34; UP: 0.35; RP: 0.32; CP: 0.30). These results suggest that different VBT programming models induced similar physical performance gains in moderately strength-trained subjects.