Effects of Velocity Loss Threshold during Resistance Training on Strength and Athletic Adaptations: A Systematic Review with Meta-Analysis

Conceptualizing a load and volume autoregulation integrated velocity model to minimize neuromuscular fatigue and maximize neuromuscular adaptations in resistance training

Resistance training (RT) load and volume are considered crucial variables to appropriately prescribe and manage for eliciting the targeted acute responses (i.e., minimizing neuromuscular fatigue) and chronic adaptations (i.e., maximizing neuromuscular adaptations). In traditional RT contexts, load and volume are generally pre-prescribed; thereby, potentially yielding sub-optimal outcomes. A RT concept that individualizes programming is autoregulation: a systematic two-step feedback process involving, (1) monitoring performance and its constituents (fitness, fatigue, and readiness) across multiple time frames (short-, moderate-, and long-term); and (2) adjusting programming (i.e., load and volume) to elicit the targeted goals (i.e., responses and adaptations). A growing body of load and volume autoregulation research has accelerated recently, with several meta-analyses suggesting that autoregulation may provide a small advantage over traditional RT. Nonetheless, the existing literature has typically conceptualized these current autoregulation methods as standalone practices, which has limited their extensive utility in research and applied settings. The primary purpose of this review was three-fold. Initially, we synthesized the current methods of load and volume autoregulation, while disseminating each method's main advantages and limitations. Second, we conceptualized a theoretical Integrated Velocity Model (IVM) that integrates the current methods for a more holistic perspective of autoregulation that may potentially augment its benefits. Lastly, we illustrated how the IVM may be compared to the current methods for future directions and how it may be implemented for practical applications. We hope that this review assists to contextualize a novel autoregulation framework to help inform future investigations for researchers and practices for RT professionals.

Delineating the Role of Inter-Repetition Interval in the Relationship between Maximum Repetitions to Failure or Repetitions in Reserve and Movement Velocity

BACKGROUND

Maximum repetitions to failure (RTF) and repetitions in reserve (RIR) can be estimated through fastest mean velocity (MVfastest) and mean velocity (MV), respectively. However, the impact of inter-repetition intervals (IRI) on these relationships in free-weight back squat and bench press exercises is unclear.

HYPOTHESIS

The IRI would affect RTF-MVfastest and RIR-MV relationships, with a higher goodness-of-fit using self-selected IRI (SSIRI) compared with 0 seconds (IRI0) and 3 seconds (IRI3).

STUDY DESIGN

Crossover study design.

LEVEL OF EVIDENCE

Level 3.

METHODS

Eighteen male participants completed 1 session per IRI configuration, consisting of 3 single sets of RTF (65%-75%-85% of the 1-repetition maximum) during the free-weight back squat and bench press exercises.

RESULTS

Individualized RTF-MVfastest and RIR-MV relationships were stronger than generalized (median R2 = 0.98 vs 0.65 and 0.84 vs 0.40, respectively). The goodness-of-fit of the relationships was stronger for SSIRI than for IRI0 during back squat (P < .01) and comparable between IRIs during bench press (P ≥ .28). During back squat, MVfastest values were higher for IRI0 than for IRI3 and SSIRI (eighth-fifteenth repetitions; P ≤ .07), whereas during the bench press, they were higher for IRI0 than for IRI3 (eleventh-fifteenth repetitions; P ≥ .28). Overall, MV values associated with each RIR were higher for IRI0 than for SSIRI (10 out of 18 comparisons) during back squat, and for IRI0 than for IRI3 and SSIRI (16 and 14 out of 18 comparisons) during bench press.

CONCLUSION

These results highlight the importance of standardizing the IRI during set-to-failure to establish RTF-MVfastest and RIR-MV relationships, with SSIRI recommended as a more accurate and effective procedure.

CLINICAL RELEVANCE

This information may provide practitioners with a valuable tool to objectively quantify the level of effort being exerted during resistance training sets by measuring movement velocity in free-weight exercises.

Exploring the Dose-Response Relationship Between Estimated Resistance Training Proximity to Failure, Strength Gain, and Muscle Hypertrophy: A Series of Meta-Regressions

BACKGROUND

The proximity to failure in which sets are terminated has gained attention in the scientific literature as a potentially key resistance training variable. Multiple meta-analyses have directly (i.e., failure versus not to failure) or indirectly (e.g., velocity loss, alternative set structures) evaluated the effect of proximity to failure on strength and muscle hypertrophy outcomes categorically; however, the dose-response effects of proximity to failure have not been analyzed collectively in a continuous manner.

OBJECTIVE

To meta-analyze the aforementioned areas of relevant research, proximity to failure was quantified as the number of repetitions in reserve (RIR). Importantly, the RIR associated with each effect in the analysis was estimated on the basis of the available descriptions of the training interventions in each study. Data were extracted and a series of exploratory multilevel meta-regressions were performed for outcomes related to both strength and muscle hypertrophy. A range of sensitivity analyses were also performed. All models were adjusted for the effects of load, method of volume equating, duration of intervention, and training status.

RESULTS

The best fit models for both strength and muscle hypertrophy outcomes demonstrated modest quality of overall fit. In all of the best-fit models for strength, the confidence intervals of the marginal slopes for estimated RIR contained a null point estimate, indicating a negligible relationship with strength gains. However, in all of the best-fit models for muscle hypertrophy, the marginal slopes for estimated RIR were negative and their confidence intervals did not contain a null point estimate, indicating that changes in muscle size increased as sets were terminated closer to failure.

CONCLUSIONS

The dose-response relationship between proximity to failure and strength gain appears to differ from the relationship with muscle hypertrophy, with only the latter being meaningfully influenced by RIR. Strength gains were similar across a wide range of RIR, while muscle hypertrophy improves as sets are terminated closer to failure. Considering the RIR estimation procedures used, however, the exact relationship between RIR and muscle hypertrophy and strength remains unclear. Researchers and practitioners should be aware that optimal proximity to failure may differ between strength and muscle hypertrophy outcomes, but caution is warranted when interpreting the present analysis due to its exploratory nature. Future studies deliberately designed to explore the continuous nature of the dose-response effects of proximity to failure in large samples should be considered.

A Comparison of Subjective Estimations and Objective Velocities at Quantifying Proximity to Failure for the Bench Press in Resistance-Trained Men and Women

ABSTRACT

Hickmott, LM, Butcher, SJ, and Chilibeck, PD. A comparison of subjective estimations and objective velocities at quantifying proximity to failure for the bench press in resistance-trained men and women. J Strength Cond Res 38(7): 1206-1212, 2024-The purpose of this study was to compare the accuracy of quantifying repetitions in reserve (RIR) in the bench press among 18 men and 18 women between 2 conditions: (a) subjective estimations and (b) objective velocities. Subjects performed 4 sessions over 10 days: (a) 1 repetition maximum (1RM) test; (b) repetition-to-failure test at 80% of 1RM; (c) 3 sets to failure at 80% of 1RM; and (d) 3 sets to failure at 75, 80, and 85% of 1RM. During sessions 2, 3, and 4, subjects verbally stated their perceived 4 and 2 RIR intraset, whereas average concentric velocity was recorded on all repetitions. The dependent variable for the subjective estimations condition was the difference between the actual number of RIR and the subject's subjective estimated number of RIR at the verbally stated 4 and 2 RIR. The dependent variable for the objective velocities condition was the difference between the actual number of RIR and the number of RIR calculated from the subject's baseline individualized last repetition average concentric velocity-RIR profile. Significance was set at p ≤ 0.05. Sessions 3 and 4 had significant ( p < 0.001) condition × set and condition × load interactions, respectively, at both 4 and 2 RIR. Objective velocities were significantly more accurate than subjective estimations on set 1 and set 2 at both RIRs during session 3 and for 75 and 80% of 1RM at both RIRs during session 4. Objective velocities exhibit significantly greater accuracy than subjective estimations at quantifying RIR during initial sets and lower loads.

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.

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.

Velocity-Based Method in Free-Weight and Machine-Based Training Modalities: The Degree of Freedom Matters

ABSTRACT

Hernández-Belmonte, A, Buendía-Romero, Á, Pallares, JG, and Martínez-Cava, A. Velocity-based method in free-weight and machine-based training modalities: the degree of freedom matters. J Strength Cond Res 37(9): e500-e509, 2023-This study aimed to analyze and compare the load-velocity relationships of free-weight and machine-based modalities of 4 resistance exercises. Moreover, we examined the influence of the subject's strength level on these load-velocity relationships. Fifty men completed a loading test in the free-weight and machine-based modalities of the bench press, full squat, shoulder press, and prone bench pull exercises. General and individual relationships between relative intensity (%1RM) and velocity variables were studied through the coefficient of determination ( R2 ) and standard error of the estimate ( SEE ). Moreover, the velocity attained to each %1RM was compared between both modalities. Subjects were divided into stronger and weaker to study whether the subject's strength level influences the mean test (mean propulsive velocity [MPV Test ]) and 1RM (MPV 1RM ) velocities. For both modalities, very close relationships ( R2 ≥ 0.95) and reduced estimation errors were found when velocity was analyzed as a dependent ( SEE ≤ 0.086 m·s -1 ) and independent ( SEE ≤ 5.7% 1RM) variable concerning the %1RM. Fits were found to be higher ( R2 ≥ 0.995) for individual load-velocity relationships. Concerning the between-modality comparison, the velocity attained at each intensity (from 30 to 100% 1RM) was significantly faster for the free-weight variant. Finally, nonsignificant differences were found when comparing MPV Test (differences ≤ 0.02 m·s -1 ) and MPV 1RM (differences ≤ 0.01 m·s -1 ) between stronger and weaker subjects. These findings prove the accuracy and stability of the velocity-based method in the free-weight and machine-based variants but highlight the need to use the load-velocity relationship (preferably the individual one) specific to each training modality.

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.