The goal of this observational study was to evaluate the feasibility of percentage of velocity loss (%VL)-based approaches for prescribing training volume during constant-load and chain-based Smith machine back squats. The study aimed to answer whether %VL can be expressed as the maximum number of repetitions (%Rep) in constant-load and chain-based Smith machine squats. Twenty-six resistance-trained men performed repetitions-to-failure tests under variable (VRT) and constant resistance training (CRT). The %Rep attained before reaching different levels of effort were compared between VRT and CRT across various loads and sessions. Furthermore, this study evaluated the influence of different factors on the predictive accuracy of the %Rep-%VL relationships. These findings will provide evidence-based evidence in prescribing and monitoring intra-set volume.
The goal of this observational study was to evaluate the feasibility of percentage of velocity loss (%VL)-based approaches for prescribing training volume during constant-load and chain-based Smith machine back squats. The study aimed to answer whether %VL can be expressed as the maximum number of repetitions (%Rep) in constant-load and chain-based Smith machine squats. Twenty-six resistance-trained men performed repetitions-to-failure tests at 85%, 75%, and 65% of their constant-load one-repetition maximum (1RM) under variable (VRT; 40% of the total external load provided by chains) and constant resistance training (CRT; 0% chains). The %Rep attained before reaching low (10% VL), moderate (20% VL), and high (30% VL) levels of effort were compared between VRT and CRT across various loads and sessions. Furthermore, this study evaluated the influence of regression type (individual vs. general), load specificity (load-specific vs. multiple-load), and loading configuration (CRT vs. VRT) on the predictive accuracy of the %Rep-%VL relationships established in session 1 for estimating %Rep in session 2. These findings will provide evidence-based evidence in prescribing and monitoring intra-set volume.
Study Type
OBSERVATIONAL
Enrollment
26
Participants initially completed a standardized general warm-up and a specific warm-up. The specific warm-up protocol included 3 repetitions at approximately 40% 1RM, 2 repetitions at 65% 1RM, and 1 repetition at 90% 1RM using constant-load to ensure adequate neuromuscular activation for the subsequent testing sets. After a 3-minute rest, participants performed three sets to momentary muscular failure with 40% of total external loads provided by chains. To minimize fatigue from higher-repetition sets influencing the repetitions completed in subsequent loads, the loads were not tested in a randomized order. Instead, participants performed the tests in a descending order of 85%, 75%, and 65% 1RM.
Participants initially completed a standardized general warm-up and a specific warm-up. The specific warm-up protocol included 3 repetitions at approximately 40% 1RM, 2 repetitions at 65% 1RM, and 1 repetition at 90% 1RM using constant-load to ensure adequate neuromuscular activation for the subsequent testing sets. After a 3-minute rest, participants performed three sets to momentary muscular failure with 0% of total external loads provided by chains. To minimize fatigue from higher-repetition sets influencing the repetitions completed in subsequent loads, the loads were not tested in a randomized order. Instead, participants performed the tests in a descending order of 85%, 75%, and 65% 1RM.
School of Physical Education and Sports Science, South China normal university
Guangzhou, Guangdong, China
The %Rep attained before reaching the 10%, 20%, and 30% VL thresholds
The %Rep attained before reaching the 10%, 20%, and 30% VL thresholds was recorded across all loads, sessions, and loading configurations.
Time frame: April 1st, 2026
The %rep predictive accuracy
To assess predictive accuracy, second-order polynomial regression equations were generated from the first session of each loading configuration using all repetitions within a set, setting %Rep as the dependent variable and %VL as the independent variable. These equations were constructed using different regression types (individual vs. general), load specificities (load-specific vs. multiple-load), and loading configurations (CRT vs. VRT). During the second session, the actual %VL recorded after reaching the 10%, 20%, and 30% VL thresholds was substituted into the corresponding first-session equations to derive the predicted %Rep. Then, the absolute estimation error was calculated as (\|actual %Rep - predicted %Rep\|). In cases where muscular failure occurred before a specific %VL threshold was reached (e.g., 30% VL), the %VL of the final completed repetition was recorded, and the corresponding actual %Rep was defined as 100%.
Time frame: April 1st, 2026
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