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.
Alejandro Pérez-Castilla and Amador García-Ramos
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.
Amador García-Ramos, Alejandro Torrejón, Antonio J. Morales-Artacho, Alejandro Pérez-Castilla and Slobodan Jaric
This study determined the optimal resistive forces for testing muscle capacities through the standard cycle ergometer test (1 resistive force applied) and a recently developed 2-point method (2 resistive forces used for force-velocity modelling). Twenty-six men were tested twice on maximal sprints performed on a leg cycle ergometer against 5 flywheel resistive forces (R1–R5). The reliability of the cadence and maximum power measured against the 5 individual resistive forces, as well as the reliability of the force-velocity relationship parameters obtained from the selected 2-point methods (R1–R2, R1–R3, R1–R4, and R1–R5), were compared. The reliability of outcomes obtained from individual resistive forces was high except for R5. As a consequence, the combination of R1 (≈175 rpm) and R4 (≈110 rpm) provided the most reliable 2-point method (CV: 1.46%–4.04%; ICC: 0.89–0.96). Although the reliability of power capacity was similar for the R1–R4 2-point method (CV: 3.18%; ICC: 0.96) and the standard test (CV: 3.31%; ICC: 0.95), the 2-point method should be recommended because it also reveals maximum force and velocity capacities. Finally, we conclude that the 2-point method in cycling should be based on 2 distant resistive forces, but avoiding cadences below 110 rpm.
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.
Alejandro Pérez-Castilla, Belén Feriche, Slobodan Jaric, Paulino Padial and Amador García-Ramos
This study aimed to examine the validity of mechanical variables obtained by a linear velocity transducer from the unconstrained and constrained squat jump (SJ). Twenty-three men were tested on the unconstrained SJ and the SJ constrained by a Smith machine. Maximum values of force, velocity, and power were simultaneously recorded both by a linear velocity transducer attached to a bar of mass of 17, 30, 45, 60, and 75 kg and by a force plate. Linear velocity transducer generally overestimated the outcomes measured as compared to the force plate, particularly in unconstrained SJ. Bland-Altman plots revealed that heteroscedasticity of errors was mainly observed for velocity variables (r 2 = .26–.58) where the differences were negatively associated with the load magnitude. However, exceptionally high correlations were observed between the same outcomes recorded with the 2 methods in both unconstrained (median r = .89 [.71–.95]) and constrained SJ (r = .90 [.65–.95]). Although the systematic and proportional bias needs to be acknowledged, the high correlations between the variables obtained by 2 methods suggest that the linear velocity transducer could provide valid values of the force, velocity, and power outputs from both unconstrained and constrained SJ.
Francisco Luis Pestaña-Melero, G. Gregory Haff, Francisco Javier Rojas, Alejandro Pérez-Castilla and Amador García-Ramos
This study aimed to compare the between-session reliability of the load–velocity relationship between (1) linear versus polynomial regression models, (2) concentric-only versus eccentric–concentric bench press variants, as well as (3) the within-participants versus the between-participants variability of the velocity attained at each percentage of the 1-repetition maximum. The load–velocity relationship of 30 men (age: 21.2 [3.8] y; height: 1.78 [0.07] m, body mass: 72.3 [7.3] kg; bench press 1-repetition maximum: 78.8 [13.2] kg) were evaluated by means of linear and polynomial regression models in the concentric-only and eccentric–concentric bench press variants in a Smith machine. Two sessions were performed with each bench press variant. The main findings were: (1) first-order polynomials (coefficient of variation: 4.39%–4.70%) provided the load–velocity relationship with higher reliability than the second-order polynomials (coefficient of variation: 4.68%–5.04%); (2) the reliability of the load–velocity relationship did not differ between the concentric-only and eccentric–concentric bench press variants; and (3) the within-participants variability of the velocity attained at each percentage of the 1-repetition maximum was markedly lower than the between-participants variability. Taken together, these results highlight that, regardless of the bench press variant considered, the individual determination of the load–velocity relationship by a linear regression model could be recommended to monitor and prescribe the relative load in the Smith machine bench press exercise.
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.
Alejandro Pérez-Castilla, Ainara Jiménez-Alonso, Mar Cepero, Sergio Miras-Moreno, F. Javier Rojas and Amador García-Ramos
This study explored the impact of different frequencies of knowledge of results (KR) on velocity performance during ballistic training. Fifteen males completed four identical sessions (three sets of six repetitions at 30% one-repetition maximum during the countermovement jump and bench press throw) with the only difference of the KR condition provided: no feedback, velocity feedback after the first half of repetitions of each set (HalfKR), velocity feedback immediately after each repetition (ImKR), and feedback of the average velocity of each set (AvgKR). When compared with the control condition, the ImKR reported the highest velocity performance (1.9–5.3%), followed by the HalfKR (1.3–3.6%) and AvgKR (0.7–4.3%). These results support the verbal provision of velocity performance feedback after every repetition to induce acute improvements in velocity performance.
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.
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.