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Changes in the Load–Velocity Profile Following Power- and Strength-Oriented Resistance-Training Programs

Alejandro Pérez-Castilla and Amador García-Ramos

Objective: To compare the short-term effect of power- and strength-oriented resistance-training programs on the individualized load–velocity profiles obtained during the squat (SQ) and bench-press (BP) exercises. Methods: Thirty physically active men (age = 23.4 [3.5] y; SQ 1-repetition maximum [1RM] = 126.5 [26.7] kg; BP 1RM = 81.6 [16.7] kg) were randomly assigned to a power- (exercises: countermovement jump and BP throw; sets per exercise: 4–6; repetitions per set: 5–6; load: 40% 1RM) or strength-training group (exercises: SQ and BP; sets per exercise: 4–6; repetitions per set: 2–8; load: 70%–90% 1RM). The training program lasted 4 wk (2 sessions/wk). The individualized load–velocity profiles (ie, velocity associated with the 30%–60%–90% 1RM) were assessed before and after training through an incremental loading test during the SQ and BP exercises. Results: The power-training group moderately increased the velocity associated with the full spectrum of % 1RM for the SQ (effect size [ES] range: 0.70 to 0.93) and with the 30% 1RM for the BP (ES: 0.67), while the strength-training group reported trivial/small changes across the load–velocity spectrum for both the SQ (ES range: 0.00 to 0.35) and BP (ES range: −0.06 to −0.33). The power-training group showed a higher increase in the mean velocity associated with all % 1RM compared with the strength-training group for both the SQ (ES range: 0.54 to 0.63) and BP (ES range: 0.25 to 0.53). Conclusions: The individualized load–velocity profile (ie, velocity associated with different % 1RM) of lower-body and upper-body exercises can be modified after a 4-wk resistance-training program.

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Sensitivity of the iLOAD® Application for Monitoring Changes in Barbell Velocity Following Power- and Strength-Oriented Resistance Training Programs

Alejandro Pérez-Castilla, Daniel Boullosa, and Amador García-Ramos

Objective: To evaluate the sensitivity of the iLOAD® application to detect the changes in mean barbell velocity of complete sets following power- and strength-oriented resistance training (RT) programs. Methods: Twenty men were randomly assigned to a power training group (countermovement jump and bench press throw at 40% of the 1-repetition maximum [1RM]) or strength training group (back squat and bench press at 70% to 90% of 1RM). Single sets of 10 repetitions at 25% and 70% of 1RM during the back squat and bench press exercises were assessed before and after the 4-week RT programs simultaneously with the iLOAD® application and a linear velocity transducer. Results: The power training group showed a greater increment in velocity performance at the 25% of 1RM (effect size range = 0.66–1.53) and the 70% of 1RM (effect size range = 0.11–0.30). The percent change in mean velocity after the RT programs highly correlated between the iLOAD® application and the linear velocity transducer for the back squat (r range = .85–.88) and bench press (r range = .87–.93). However, the iLOAD® application revealed a 2% greater increase in mean velocity after training compared to the linear velocity transducer. Conclusions: The iLOAD® application is a cost-effective, portable, and easy-to-use tool which can be used to detect changes in mean barbell velocity after power- and strength-oriented RT programs.

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Lifting Velocity as a Predictor of the Maximum Number of Repetitions That Can Be Performed to Failure During the Prone Bench Pull Exercise

Sergio Miras-Moreno, Alejandro Pérez-Castilla, and Amador García-Ramos

Objective: To explore (1) the goodness of fit of generalized and individualized relationships between the maximum number of repetitions performed to failure (RTF) and the fastest mean velocity and peak velocity of the sets (RTF–velocity relationships), (2) the between-sessions reliability of mean velocity and peak velocity values associated with different RTFs, and (3) whether the errors in the prediction of the RTF under fatigued and nonfatigued conditions differ between generalized and individualized RTF–velocity relationships. Methods: Twenty-three sport-science students performed 4 testing sessions with the prone bench pull exercise in a Smith machine: a 1-repetition-maximum [1RM] session, 2 identical sessions consisting of singles sets of RTF against 4 randomized loads (60%–70%–80%–90%1RM), and 1 session consisting of 4 sets of RTF against the 75%1RM. Results: Individualized RTF–velocity relationships presented a higher goodness of fit (r 2 = .96–.97 vs .67–.70) and accuracy (absolute errors = 2.1–2.9 repetitions vs 2.8–4.3 repetitions) in the prediction of the RTF than generalized RTF–velocity relationships. The reliability of the velocity values associated with different RTFs was generally high (average within-subject coefficient of variation = 4.01% for mean velocity and 3.98% for peak velocity). The error in the prediction of the RTF increased by ~1 repetition under fatigue (ie, set 1 vs sets 2–4). Conclusions: Individualized RTF–velocity relationships can be used with acceptable precision and reliability to prescribe the loads associated with a given RTF during the match a specific XRM during the prone bench pull exercise, but a lower accuracy is expected in a fatigued state.

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Selective Changes in the Mechanical Capacities of Lower-Body Muscles After Cycle-Ergometer Sprint Training Against Heavy and Light Resistances

Amador García-Ramos, Alejandro Torrejón, Alejandro Pérez-Castilla, Antonio J. Morales-Artacho, and Slobodan Jaric

Purpose: To explore the feasibility of the linear force–velocity (F–V) modeling approach to detect selective changes of F–V parameters (ie, maximum force [F 0], maximum velocity [V 0], F–V slope [a], and maximum power [P 0]) after a sprint-training program. Methods: Twenty-seven men were randomly assigned to a heavy-load group (HLG), light-load group (LLG), or control group (CG). The training sessions (6 wk × 2 sessions/wk) comprised performing 8 maximal-effort sprints against either heavy (HLG) or light (LLG) resistances in leg cycle-ergometer exercise. Pre- and posttest consisted of the same task performed against 4 different resistances that enabled the determination of the F–V parameters through the application of the multiple-point method (4 resistances used for the F–V modeling) and the recently proposed 2-point method (only the 2 most distinctive resistances used). Results: Both the multiple-point and the 2-point methods revealed high reliability (all coefficients of variation <5% and intraclass correlation coefficients >.80) while also being able to detect the group-specific training-related changes. Large increments of F 0, a, and P 0 were observed in HLG compared with LLG and CG (effect size [ES] = 1.29–2.02). Moderate increments of V 0 were observed in LLG compared with HLG and CG (ES = 0.87–1.15). Conclusions: Short-term sprint training on a leg cycle ergometer induces specific changes in F–V parameters that can be accurately monitored by applying just 2 distinctive resistances during routine testing.

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Differences in the Load–Velocity Profile Between 4 Bench-Press Variants

Amador García-Ramos, Francisco Luis Pestaña-Melero, Alejandro Pérez-Castilla, Francisco Javier Rojas, and Guy Gregory Haff

Purpose: To compare the load–velocity relationship between 4 variants of the bench-press (BP) exercise. Methods: The full load–velocity relationship of 30 men was evaluated by means of an incremental loading test starting at 17 kg and progressing to the individual 1-repetition maximum (1RM) in 4 BP variants: concentric-only BP, concentric-only BP throw (BPT), eccentric-concentric BP, and eccentric-concentric BPT. Results: A strong and fairly linear relationship between mean velocity (MV) and %1RM was observed for the 4 BP variants (r 2 > .96 for pooled data and r 2 > .98 for individual data). The MV associated with each %1RM was significantly higher in the eccentric-concentric technique than in the concentric-only technique. The only significant difference between the BP and BPT variants was the higher MV with the light to moderate loads (20–70%1RM) in the BPT using the concentric-only technique. MV was significantly and positively correlated between the 4 BP variants (r = .44–.76), which suggests that the subjects with higher velocities for each %1RM in 1 BP variant also tend to have higher velocities for each %1RM in the 3 other BP variants. Conclusions: These results highlight the need for obtaining specific equations for each BP variant and the existence of individual load–velocity profiles.

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Precision of 7 Commercially Available Devices for Predicting Bench-Press 1-Repetition Maximum From the Individual Load–Velocity Relationship

Alejandro Pérez-Castilla, Antonio Piepoli, Gabriel Garrido-Blanca, Gabriel Delgado-García, Carlos Balsalobre-Fernández, and Amador García-Ramos

Objective: To compare the accuracy of different devices to predict the bench-press 1-repetition maximum (1RM) from the individual load–velocity relationship modeled through the multiple- and 2-point methods. Methods: Eleven men performed an incremental test on a Smith machine against 5 loads (45–55–65–75–85%1RM), followed by 1RM attempts. The mean velocity was simultaneously measured by 1 linear velocity transducer (T-Force), 2 linear position transducers (Chronojump and Speed4Lift), 1 camera-based optoelectronic system (Velowin), 2 inertial measurement units (PUSH Band and Beast Sensor), and 1 smartphone application (My Lift). The velocity recorded at the 5 loads (45–55–65–75–85%1RM), or only at the 2 most distant loads (45–85%1RM), was considered for the multiple- and 2-point methods, respectively. Results: An acceptable and comparable accuracy in the estimation of the 1RM was observed for the T-Force, Chronojump, Speed4Lift, Velowin, and My Lift when using both the multiple- and 2-point methods (effect size ≤ 0.40; Pearson correlation coefficient [r] ≥ .94; standard error of the estimate [SEE] ≤ 4.46 kg), whereas the accuracy of the PUSH (effect size = 0.70–0.83; r = .93–.94; SEE = 4.45–4.80 kg), and especially the Beast Sensor (effect size = 0.36–0.84; r = .50–.68; SEE = 9.44–11.2 kg), was lower. Conclusions: These results highlight that the accuracy of 1RM prediction methods based on movement velocity is device dependent, with the inertial measurement units providing the least accurate estimate of the 1RM.

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Prediction of the Maximum Number of Repetitions and Repetitions in Reserve From Barbell Velocity

Amador García-Ramos, Alejandro Torrejón, Belén Feriche, Antonio J. Morales-Artacho, Alejandro Pérez-Castilla, Paulino Padial, and Guy Gregory Haff

Purpose: To provide 2 general equations to estimate the maximum possible number of repetitions (XRM) from the mean velocity (MV) of the barbell and the MV associated with a given number of repetitions in reserve, as well as to determine the between-sessions reliability of the MV associated with each XRM. Methods: After determination of the bench-press 1-repetition maximum (1RM; 1.15 ± 0.21 kg/kg body mass), 21 men (age 23.0 ± 2.7 y, body mass 72.7 ± 8.3 kg, body height 1.77 ± 0.07 m) completed 4 sets of as many repetitions as possible against relative loads of 60%1RM, 70%1RM, 80%1RM, and 90%1RM over 2 separate sessions. The different loads were tested in a randomized order with 10 min of rest between them. All repetitions were performed at the maximum intended velocity. Results: Both the general equation to predict the XRM from the fastest MV of the set (CV = 15.8–18.5%) and the general equation to predict MV associated with a given number of repetitions in reserve (CV = 14.6–28.8%) failed to provide data with acceptable between-subjects variability. However, a strong relationship (median r 2 = .984) and acceptable reliability (CV < 10% and ICC > .85) were observed between the fastest MV of the set and the XRM when considering individual data. Conclusions: These results indicate that generalized group equations are not acceptable methods for estimating the XRM–MV relationship or the number of repetitions in reserve. When attempting to estimate the XRM–MV relationship, one must use individualized relationships to objectively estimate the exact number of repetitions that can be performed in a training set.

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Feasibility of the 2-Point Method for Determining the 1-Repetition Maximum in the Bench Press Exercise

Amador García-Ramos, Guy Gregory Haff, Francisco Luis Pestaña-Melero, Alejandro Pérez-Castilla, Francisco Javier Rojas, Carlos Balsalobre-Fernández, and Slobodan Jaric

Purpose: This study compared the concurrent validity and reliability of previously proposed generalized group equations for estimating the bench press (BP) 1-repetition maximum (1RM) with the individualized load–velocity relationship modeled with a 2-point method. Methods: Thirty men (BP 1RM relative to body mass: 1.08 [0.18] kg·kg−1) performed 2 incremental loading tests in the concentric-only BP exercise and another 2 in the eccentric–concentric BP exercise to assess their actual 1RM and load–velocity relationships. A high velocity (≈1 m·s−1) and a low velocity (≈0.5 m·s−1) were selected from their load–velocity relationships to estimate the 1RM from generalized group equations and through an individual linear model obtained from the 2 velocities. Results: The directly measured 1RM was highly correlated with all predicted 1RMs (r = .847–.977). The generalized group equations systematically underestimated the actual 1RM when predicted from the concentric-only BP (P < .001; effect size = 0.15–0.94) but overestimated it when predicted from the eccentric–concentric BP (P < .001; effect size = 0.36–0.98). Conversely, a low systematic bias (range: −2.3 to 0.5 kg) and random errors (range: 3.0–3.8 kg), no heteroscedasticity of errors (r 2 = .053–.082), and trivial effect size (range: −0.17 to 0.04) were observed when the prediction was based on the 2-point method. Although all examined methods reported the 1RM with high reliability (coefficient of variation ≤ 5.1%; intraclass correlation coefficient  ≥ .89), the direct method was the most reliable (coefficient of variation < 2.0%; intraclass correlation coefficient ≥ .98). Conclusions: The quick, fatigue-free, and practical 2-point method was able to predict the BP 1RM with high reliability and practically perfect validity, and therefore, the authors recommend its use over generalized group equations.

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The Novel Single-Stroke Kayak Test: Can It Discriminate Between 200-m and Longer-Distance (500- and 1000-m) Specialists in Canoe Sprint?

Milos R. Petrovic, Amador García-Ramos, Danica N. Janicijevic, Alejandro Pérez-Castilla, Olivera M. Knezevic, and Dragan M. Mirkov

Purpose: To test whether the force–velocity (F–V) relationship obtained during a specific single-stroke kayak test (SSKT) and during nonspecific traditional resistance-training exercises (bench press and prone bench pull) could discriminate between 200-m specialists and longer-distance (500- and 1000-m) specialists in canoe sprint. Methods: A total of 21 experienced male kayakers (seven 200-m specialists and 14 longer-distance specialists) participated in this study. After a familiarization session, kayakers came to the laboratory on 2 occasions separated by 48 to 96 hours. In a randomized order, kayakers performed the SSKT in one session and the bench press and bench pull tests in another session. Force and velocity outputs were recorded against 5 loads in each exercise to determine the F–V relationship and related parameters (maximum force, maximum velocity, F–V slope, and maximum power). Results: The individual F–V relationships were highly linear for the SSKT (r = .990 [.908, .998]), bench press (r = .993 [.974, .999]), and prone bench pull (r = .998 [.992, 1.000]). The F–V relationship parameters (maximum force, maximum velocity, and maximum power) were significantly higher for 200-m specialists compared with longer-distance specialists (all Ps ≤ .047) with large effect sizes (≥0.94) revealing important practical differences. However, no significant differences were observed between 200-m specialists and longer-distance specialists in the F–V slope (P ≥ .477). Conclusions: The F–V relationship assessed during both specific (SSKT) and nonspecific upper-body tasks (bench press and bench pull) may distinguish between kayakers specialized in different distances.

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Influence of Grip Width and Anthropometric Characteristics on the Bench-Press Load–Velocity Relationship

Alejandro Pérez-Castilla, Daniel Jerez-Mayorga, Dario Martínez-García, Ángela Rodríguez-Perea, Luis J. Chirosa-Ríos, and Amador García-Ramos

Purpose: To compare the load–velocity (L-V) relationship between bench-press exercises performed using 4 different grip widths, to determine the association between the anthropometric characteristics and L-V profile, and to explore whether a multiple linear-regression model with movement velocity and subjects’ anthropometric characteristics as predictor variables could increase the goodness of fit of the individualized L-V relationship. Methods: The individual L-V relationship of 20 men was evaluated by means of an incremental loading test during the bench-press exercise performed on a Smith machine using narrow, medium, wide, and self-selected grip widths. Simple and multiple linear-regression models were performed. Results: The mean velocity associated with each relative load did not differ among the 4 grip widths (P ≥ .130). Only body height and total arm length were correlated with the mean velocity associated with light and medium loads (r ≥ .464). A slightly higher variance of the velocity attained at each relative load was explained when some anthropometric characteristics were used as predictor variables along with the movement velocity (r 2 = .969 [.965–.973]) in comparison with the movement velocity alone (r 2 = .966 [.955–.968]). However, the amount of variance explained by the individual L-V relationships was always higher than with the multiple linear-regression models (r 2 = .995 [.985–1.000]). Conclusions: These results indicate that the individual determination of the L-V relationship using a self-selected grip width could be recommended to monitor relative loads in the Smith machine bench-press exercise.