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

Exerting force at the maximal speed drives the increase in power output in elite athletes after 4 weeks of resistance training

PURPOSE

In the present study, we examined how a 4-week intervention of maximal intended velocity (MIVRT) and controlled velocity resistance training (CRT)-induced task-specific responses in expert individuals.

METHODS

Twenty elite athletes were randomly assigned to either a MIVRT (n = 10) or CRT (n = 10) group, both following the same volume-load training based on the back-squat three times a week but with different intentions in moving load (force-exertion speed). We assessed one-repetition maximum (1RM), mean propulsive velocity (MPV), and mean propulsive power (MPP) using a progressive-loading test before and after the intervention. A linear position transducer was used to monitor propulsive velocity in training and testing sessions.

RESULTS

Both groups significantly increased their 1RM (CRT: + 12.3%, p < 0.001, d = 0.39; MIVRT: + 12.5%, p < 0.001, d = 0.45). Only the MIVRT group showed a significant improvement in MPV (p < 0.01) across different stepping loads, while both groups improved in MPP (MIVRT: + 22.4%, p < 0.001, d = 0.54; CRT: + 8.1%, p = 0.04, d = 0.17).

CONCLUSIONS

MIVRT induced significant adaptations in MPV and MPP at various loads (%1RM), underlining its specificity in targeting these parameters. Despite similar enhancements in 1RM, the distinct training protocols suggest that strength gains may stem from either maximal intent in moving loads or longer times under tension. This study highlights the role of execution speed in optimizing power outcomes, emphasizing task specificity as paramount to elicit physiological adaptations in chronically strength-trained individuals.

Applying a Holistic Injury Prevention Approach to Elite Triathletes

(1) Background: Studies on injury prevention programs are lacking for triathletes. The aim of the present study was to describe the results of a holistic (injury) training prevention program (HITP), based on training load control and strength training, in elite triathletes. (2) Methods: The study was conducted over 2021-2023 and involved 18 males and 10 females from the same training group. The HITP itself included various methods of fatigue monitoring, strength training focused on the prevention of overuse injuries (OIs), cycling skills training, and recovery strategies. The total number and type of injuries that were sustained, subsequent training/competition absence time, and injury incidence were determined. (3) Results: Twenty-four injuries were recorded over all three seasons, i.e., 0.65 injuries per 1000 h of training and competition exposure. Fourteen injuries were traumatic injuries (TIs) and ten were OIs. Of the OIs, four were of minimal severity, two were mild, three were moderate, and one was severe (accounting for 1-3, 4-7, 8-28, and >28 days of training absenteeism, respectively). A total of 46.4% of the participants did not present any type of injury and 71,4% did not incur any OIs. Average absenteeism was 17.3 days per injury. (4) Conclusions: The HITP design and implementation resulted in low OI and severe injury incidence. Due to their unpredictable nature, the number of TIs was not reduced. The TIs were suffered more frequently by men. Women are more likely to suffer from OIs, so it is particularly important to prevent OIs in women.

Effects of 4 Different Velocity-Based Resistance-Training Programming Models on Physical Performance

PURPOSE

To examine the effects of 4 programming models (linear [LP], undulating [UP], reverse [RP], and constant [CP]) on physical performance.

METHODS

Forty-eight moderately strength-trained men were randomly assigned to LP, UP, RP, and CP groups according to their 1-repetition maximum (1RM) in the full-squat exercise (SQ) and followed an 8-week training intervention using the SQ and monitoring movement velocity for every repetition. All groups trained with similar mean relative intensity (65% 1RM), number of repetitions (240), sets (3), and interset recovery (4 min) throughout the training program. Pretraining and posttraining measurements included, in the SQ, 1RM load, the average velocity attained for all absolute loads common to pretests and posttests (AV), and the average velocity for loads that were moved faster (AV > 1) and slower (AV < 1) than 1 m·s-1 at pretraining tests. Moreover, countermovement jump height and 20-m running sprint time were measured.

RESULTS

A significant time effect was found for all variables analyzed (P < .05), except for 20-m running sprint time. Significant group × time interactions were observed for 1RM, AV > 1, and AV (P < .05). After training, all groups attained significant strength gains on 1RM, AV, AV > 1, and AV < 1 (P < .001-.01). LP and RP groups improved their countermovement jump height (P < .01), but no significant changes were observed for UP and CP. No significant improvements were achieved in 20-m running sprint time for any groups.

CONCLUSIONS

These different programming models are all suitable for improving physical performance. LP and RP induce similar or greater gains in physical performance than UP and CP.

Validity of a Smartphone App Using Artificial Intelligence for the Real-Time Measurement of Barbell Velocity in the Bench Press Exercise

ABSTRACT

Balsalobre-Fernández, C, Xu, J, Jarvis, P, Thompson, S, Tannion, K, and Bishop, C. Validity of a smartphone app using artificial intelligence for the real-time measurement of barbell velocity in the bench press exercise. J Strength Cond Res 37(12): e640-e645, 2023-The purpose of this study was to explore the validity and within-session reliability of the newly developed My Jump Lab application (app), which uses artificial intelligence techniques to monitor barbell velocity in real time. Twenty-seven sport science students performed 5 repetitions at 50 and 75% of their self-reported bench press 1 repetition maximum (1RM) during a single testing session, whereas barbell velocity was concurrently measured using the app (installed on an iPhone 12 Pro) and the GymAware linear position transducer (LPT). A very high correlation was observed between devices at each loading condition (50% 1RM: r = 0.90 [0.82-0.97]; 75% 1RM: r = 0.92 [0.86-0.98]). Results showed trivial differences between the app and LPT at both 50% 1RM (g = -0.06) and 75% 1RM (g = -0.12). Bland-Altman analysis showed a bias estimate of -0.010 m·s-1 and -0.026 m·s-1 for the 50 and 75% 1RM, respectively. Finally, similar levels of reliability, as revealed by the coefficient of variation, were observed for both devices (50% 1RM: LPT = 6.52%, app = 8.17%; 75% 1RM: LPT = 12.10%, app = 13.55%). Collectively, the findings of this study support the use of My Jump Lab for the measurement of real-time barbell velocity in the bench press exercise.

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.

Agreement in Squat Jump Force-Time Characteristics Between Smith Machine and Free-Weight Squat Jump Force-Time Characteristics

ABSTRACT

Kotani, Y, Lake, J, Guppy, SN, Poon, W, Nosaka, K, and Haff, GG. Agreement in squat jump force-time characteristics between Smith machine and free-weight squat jump force-time characteristics. J Strength Cond Res 37(10): 1955-1962, 2023-The purpose of this study was to determine whether squat jump (SJ) force-velocity (FV) and load-velocity (LV) profiles created using free-weights agree with profiles created with a Smith machine. Fifteen resistance-trained male subjects (age = 26.4 ± 2.5 years; height = 1.75 ± 0.09 m; body mass = 82.6 ± 13.4 kg) participated in this study. All subjects completed 2 familiarization and 2 experimental sessions using both the Smith machine and free-weight SJs each separated by 48 hours. During the experimental trials, progressively loaded SJs were performed in a quasi-randomized block order with loads between 21 kg and 100% of the subject's body mass. Agreement between exercise mode was determined with a weighted least products regression analysis. No fixed or proportional bias was noted between exercise modes when using peak velocity (PV) and mean velocity (MV) to create an FV profile. There was no fixed and proportional bias present for the LV profile when the profile was created with PV. When the LV profile was calculated from MV, fixed and proportional bias were present, indicating that MVs were significantly different between exercise modes. In addition, the free-weight FV and LV profiles exhibited poor to good relative and good to poor absolute reliability. Furthermore, when created using the Smith machine, both profiles exhibited poor to moderate relative and absolute reliability. Based on these data, caution should be used when interpreting LV and FV profiles created with these 2 methods.

Adaptations in athletic performance and muscle architecture are not meaningfully conditioned by training free-weight versus machine-based exercises: Challenging a traditional assumption using the velocity-based method

BACKGROUND

Although the superior effectiveness of free-weight over machine-based training has been a traditionally widespread assumption, longitudinal studies comparing these training modalities were scarce and heterogeneous.

OBJECTIVE

This research used the velocity-based method to compare the effects of free-weight and machine-based resistance training on athletic performance and muscle architecture.

METHODS

Thirty-four resistance-trained men participated in an 8-week resistance training program allocated into free-weight (n = 17) or machine-based (n = 17) groups. Training variables (intensity, intraset fatigue, and recovery) were identical for both groups, so they only differed in the use of a barbell or specific machines to execute the full squat, bench press, prone bench pull, and shoulder press exercises. The velocity-based method was implemented to accurately adjust the planned intensity. Analysis of covariance and effect size (ES) statistics were used to compare both training modalities on a comprehensive set of athletic and muscle architecture parameters.

RESULTS

No between-group differences were found for any athletic (p ≥ 0.146) and muscle architecture (p ≥ 0.184) variable. Both training modalities significantly and similarly improved vertical jump (Free-weight: ES ≥ 0.45, p ≤ 0.001; Machine-based: ES ≥ 0.41, p ≤ 0.001) and lower limb anaerobic capacity (Free-weight: ES ≥ 0.39, p ≤ 0.007; Machine-based: ES ≥ 0.31, p ≤ 0.003). Additionally, the machine-based group meaningfully enhanced upper limb anaerobic power (ES = 0.41, p = 0.021), whereas the free-weight group significantly improved the change of direction (ES = -0.54, p = 0.003) and 2/6 balance conditions analyzed (p ≤ 0.012). Changes in sprint capacity (ES ≥ -0.13, p ≥ 0.274), fascicle length, and pennation angle (ES ≤ 0.19, p ≥ 0.129) were not significant for either training modality.

CONCLUSION

Adaptations in athletic performance and muscle architecture would not be meaningfully influenced by the resistance modality trained.

The Acute and Chronic Effects of Implementing Velocity Loss Thresholds During Resistance Training: A Systematic Review, Meta-Analysis, and Critical Evaluation of the Literature

BACKGROUND

Velocity loss (VL) experienced in a set during resistance training is often monitored to control training volume and quantify acute fatigue responses. Accordingly, various VL thresholds are used to prescribe resistance training and target different training adaptations. However, there are inconsistencies in the current body of evidence regarding the magnitude of the acute and chronic responses to the amount of VL experienced during resistance training.

OBJECTIVE

The aim of this systematic review was to (1) evaluate the acute training volume, neuromuscular, metabolic, and perceptual responses to the amount of VL experienced during resistance training; (2) synthesize the available evidence on the chronic effects of different VL thresholds on training adaptations; and (3) provide an overview of the factors that might differentially influence the magnitude of specific acute and chronic responses to VL during resistance training.

METHODS

This review was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Five databases were searched, and studies were included if they were written in English, prescribed resistance training using VL, and evaluated at least one (1) acute training volume, neuromuscular, metabolic, or perceptual response or (2) training adaptation. Risk of bias was assessed using a modified Cochrane Collaboration's tool for assessing the risk of bias in randomized trials. Multilevel and multivariate meta-regressions were performed where possible.

RESULTS

Eighteen acute and 19 longitudinal studies met the inclusion criteria, of which only one had more than one risk of bias item assessed as high risk. Based on the included acute studies, it seems that the number of repetitions per set, blood lactate concentration, and rating of perceived exertion generally increase, while countermovement jump height, running sprint times, and velocity against fixed loads generally decrease as VL increases. However, the magnitude of these effects seems to be influenced, among other factors, by the exercise and load used. Regarding training adaptations, VL experienced during resistance training did not influence muscle strength and endurance gains. Increases in VL were associated with increases in hypertrophy (b = 0.006; 95% confidence interval [CI] 0.001, 0.012), but negatively affected countermovement jump (b = - 0.040; 95% CI - 0.079, - 0.001), sprint (b = 0.001; 95% CI 0.001, 0.002), and velocity against submaximal load performance (b = - 0.018; 95% CI - 0.029, - 0.006).

CONCLUSIONS

A graded relationship exists between VL experienced during a set and acute training volume, neuromuscular, metabolic, and perceptual responses to resistance training. However, choice of exercise, load, and individual trainee characteristics (e.g., training history) seem to modulate these relationships. The choice of VL threshold does not seem to affect strength and muscle endurance gains whereas higher VL thresholds are superior for enhancing hypertrophy, and lower VL thresholds are superior for jumping, sprinting, and velocity against submaximal loads performance.

CLINICAL TRIAL REGISTRATION

The original protocol was prospectively registered ( https://osf.io/q4acs/ ) with the Open Science Framework.

Toward a New Paradigm in Resistance Training by Means of Velocity Monitoring: A Critical and Challenging Narrative

For more than a century, many concepts and several theories and principles pertaining to the goals, organization, methodology and evaluation of the effects of resistance training (RT) have been developed and discussed between coaches and scientists. This cumulative body of knowledge and practices has contributed substantially to the evolution of RT methodology. However, a detailed and rigorous examination of the existing literature reveals many inconsistencies that, unless resolved, could seriously hinder further progress in our field. The purpose of this review is to constructively expose, analyze and discuss a set of anomalies present in the current RT methodology, including: (a) the often inappropriate and misleading terminology used, (b) the need to clarify the aims of RT, (c) the very concept of maximal strength, (d) the control and monitoring of the resistance exercise dose, (e) the existing programming models and (f) the evaluation of training effects. A thorough and unbiased examination of these deficiencies could well lead to the adoption of a revised paradigm for RT. This new paradigm must guarantee a precise knowledge of the loads being applied, the effort they involve and their effects. To the best of our knowledge, currently this can only be achieved by monitoring repetition velocity during training. The main contribution of a velocity-based RT approach is that it provides the necessary information to know the actual training loads that induce a specific effect in each athlete. The correct adoption of this revised paradigm will provide coaches and strength and conditioning professionals with accurate and objective information concerning the applied load (relative load, level of effort and training effect). This knowledge is essential to make rational and informed decisions and to improve the training methodology itself.

The Role of Velocity-Based Training (VBT) in Enhancing Athletic Performance in Trained Individuals: A Meta-Analysis of Controlled Trials

Velocity-based training (VBT) is a rising auto-regulation method that dynamically regulates training loads to promote resistance training. However, the role of VBT in improving various athletic performances is still unclear. Hence, the presented study aimed to examine the role of VBT in improving lower limbs’ maximum strength, strength endurance, jump, and sprint performance among trained individuals. A systematic literature search was performed to identify studies on VBT for lower limb strength training via databases, including PubMed, Web of Science, Embase, EBSCO, Cochrane, CNKI (in Chinese), and Wanfang Database (in Chinese). Controlled trials that deployed VBT only without extra training content were considered. Eventually, nine studies with a total of 253 trained males (at least one year of training experience) were included in the meta-analysis. The pooled results suggest that VBT may effectively enhance lower limbs’ maximum strength (SMD = 0.76; p < 0.001; I2 = 0%), strength endurance (SMD = 1.19; p < 0.001; I2 = 2%), countermovement jump (SMD = 0.53; p < 0.001; I2 = 0%), and sprint ability (SMD of sprint time = −0.40; p < 0.001; I2 = 0%). These findings indicate the positive role of VBT in serving athletic training. Future research is warranted to focus on the effect of velocity loss of VBT on athletic performance.

Strength and Athletic Adaptations Produced by 4 Programming Models: A Velocity-Based Intervention Using a Real-Context Routine

PURPOSE

To compare the strength and athletic adaptations induced by 4 programming models.

METHODS

Fifty-two men were allocated into 1 of the following models: linear programming (intensity increased while intraset volume decreased), undulating programming (intensity and intraset volume were varied in each session or set of sessions), reverse programming (intensity decreased while intraset volume increased), or constant programming (intensity and intraset volume kept constant throughout the training plan). All groups completed a 10-week resistance-training program made up of the free-weight bench press, squat, deadlift, prone bench pull, and shoulder press exercises. The 4 models used the same frequency (2 sessions per week), number of sets (3 per exercise), interset recoveries (4 min), and average intensity throughout the intervention (77.5%). The velocity-based method was used to accurately adjust the planned intensity for each model.

RESULTS

The 4 programming models exhibited significant pre-post changes in most strength variables analyzed. When considering the effect sizes for the 5 exercises trained, we observed that the undulating programming (mean effect size = 0.88-2.92) and constant programming (mean effect size = 0.61-1.65) models induced the highest and lowest strength enhancements, respectively. Moreover, the 4 programming models were found to be effective to improve performance during shorter (jump and sprint tests) and longer (upper- and lower-limb Wingate test) anaerobic tasks, with no significant differences between them.

CONCLUSION

The linear, undulating, reverse, and constant programming models are similarly effective to improve strength and athletic performance when they are implemented in a real-context routine.

Velocity-Based Resistance Training on 1-RM, Jump and Sprint Performance: A Systematic Review of Clinical Trials

Weight resistance training (RT) has been shown to positively influence physical performance. Within the last two decades, a methodology based on monitoring RT through movement velocity (also called velocity-based resistance training, VBRT) has emerged. The aim of this PRISMA-based systematic review was to evaluate the effect of VBRT programs on variables related to muscle strength (one-repetition maximum, 1-RM), and high-speed actions (vertical jump, and sprint performance) in trained subjects. The search for published articles was performed in PubMed/MEDLINE, SPORT Discus/EBSCO, OVID, Web of Science, Scopus, and EMBASE databases using Boolean algorithms independently. A total of 22 studies met the inclusion criteria of this systematic review (a low-to-moderate overall risk of bias of the analyzed studies was detected). VBRT is an effective method to improve 1-RM, vertical jump and sprint. According to the results of the analyzed studies, it is not necessary to reach high muscle failure in order to achieve the best training results. These findings reinforce the fact that it is possible to optimize exercise adaptations with less fatigue. Future studies should corroborate these findings in female population.