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Harry G. Banyard, Ken Nosaka, Kimitake Sato, and G. Gregory Haff

Purpose:

To examine the validity of 2 kinematic systems for assessing mean velocity (MV), peak velocity (PV), mean force (MF), peak force (PF), mean power (MP), and peak power (PP) during the full-depth free-weight back squat performed with maximal concentric effort.

Methods:

Ten strength-trained men (26.1 ± 3.0 y, 1.81 ± 0.07 m, 82.0 ± 10.6 kg) performed three 1-repetition-maximum (1RM) trials on 3 separate days, encompassing lifts performed at 6 relative intensities including 20%, 40%, 60%, 80%, 90%, and 100% of 1RM. Each repetition was simultaneously recorded by a PUSH band and commercial linear position transducer (LPT) (GymAware [GYM]) and compared with measurements collected by a laboratory-based testing device consisting of 4 LPTs and a force plate.

Results:

Trials 2 and 3 were used for validity analyses. Combining all 120 repetitions indicated that the GYM was highly valid for assessing all criterion variables while the PUSH was only highly valid for estimations of PF (r = .94, CV = 5.4%, ES = 0.28, SEE = 135.5 N). At each relative intensity, the GYM was highly valid for assessing all criterion variables except for PP at 20% (ES = 0.81) and 40% (ES = 0.67) of 1RM. Moreover, the PUSH was only able to accurately estimate PF across all relative intensities (r = .92–.98, CV = 4.0–8.3%, ES = 0.04–0.26, SEE = 79.8–213.1 N).

Conclusions:

PUSH accuracy for determining MV, PV, MF, MP, and PP across all 6 relative intensities was questionable for the back squat, yet the GYM was highly valid at assessing all criterion variables, with some caution given to estimations of MP and PP performed at lighter loads.

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Laurent B. Seitz, Matt Barr, and G. Gregory Haff

Purpose:

To compare the effects of sprint training with or without ball carry on the sprint performance of elite rugby league players.

Methods:

Twenty-four elite rugby league players were divided into a ball-carry group (BC; n = 12) and a no-ball-carry group (NBC; n = 12). The players of the BC group were required to catch and carry the ball under 1 arm during each sprint, whereas the NBC group performed sprints without carrying a ball. The 8-wk training intervention took place during the precompetitive phase of the season and consisted of 2 sessions/wk. Sprint performance was measured before and after the training intervention with 40-m linear sprints performed under 2 conditions: with and without ball carry. Split times of 10, 20, and 40 m were recorded for further analysis. A 3-way (group × time × condition) factorial ANOVA was performed to compare changes in sprint performance with and without the ball, before and after the training intervention for both BC and NBC training groups.

Results:

The BC and NBC groups experienced similar improvements in 10-, 20-, and 40-m sprint times and accelerations, regardless of the condition under which the sprint tests were performed (P = .19).

Conclusions:

Sprint training while carrying a rugby ball is as effective as sprint training without carrying a rugby ball for improving the sprint performance of elite rugby league players.

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Joseph O.C. Coyne, Robert U. Newton, and G. Gregory Haff

Purpose: A simple and 2 different exponentially weighted moving average methods were used to investigate the relationships between internal training load and elite weightlifting performance. Methods: Training impulse data (sessional ratings of perceived exertion × training duration) were collected from 21 elite weightlifters (age = 26.0 [3.2] y, height = 162.2 [11.3] cm, body mass = 72.2 [23.8] kg, previous 12-mo personal best total 96.3% [2.7%] of world record total) during the 8 weeks prior to the 2016 Olympic Games qualifying competition. The amount of training modified or cancelled due to injury/illness was also collected. The training stress balance (TSB) and acute to chronic workload ratio (ACWR) were calculated with the 3 moving average methods. Along with the amount of modified training, TSB and ACWR across the moving average methods were then examined for their relationship to competitive performance. Results: There were no consistent associations between performance and training load on the day of competition. The volatility (SD) of the ACWR in the last 21 days preceding the competition was moderately correlated with performance across moving average methods (r = −.41 to .48, P = .03–.07). TSB and ACWR volatility in the last 21 days were also significantly lower for successful performers but only as a simple moving average (P = .03 and .03, g = 1.15 and 1.07, respectively). Conclusions: Practitioners should consider restricting change and volatility in an athlete’s TSB or ACWR in the last 21 days prior to a major competition. In addition, a simple moving average seemed to better explain elite weightlifting performance than the exponentially weighted moving averages in this investigation.

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Laurent B. Seitz, Gabriel S. Trajano, and G. Gregory Haff

Purpose:

To compare the acute effects of back squats and power cleans on sprint performance.

Methods:

Thirteen elite junior rugby league players performed 20-m linear sprints before and 7 min after 2 different conditioning activities or 1 control condition. The conditioning activities included 1 set of 3 back squats or power cleans at 90% 1-repetition maximum. A 2 × 2 repeated-measures ANOVA was used to compare preconditioning and postconditioning changes in sprint performance.

Results:

Both the back-squat and power-clean conditioning activities demonstrated a potentiation effect as indicated by improved sprint time (back squat: P = .001, ES = –0.66; power cleans: P = .001, ES = –0.92), velocity (back squat: P = .001, ES = 0.63; power cleans: P = .001, ES = 0.84), and average acceleration over 20 m (back squat: P = .001, ES = 0.70; power cleans: P = .001, ES = 1.00). No potentiation effect was observed after the control condition. Overall, the power clean induced a greater improvement in sprint time (P = .042, ES = 0.83), velocity (P = .047, ES = 1.17), and average acceleration (P = .05, ES = 0.87) than the back squat.

Conclusions:

Back-squat and power-clean conditioning activities both induced improvements in sprint performance when included as part of a potentiation protocol. However, the magnitude of improvement was greater after the power cleans. From a practical perspective, strength and conditioning coaches should consider using power cleans rather than back squats to maximize the performance effects of potentiation complexes targeting the development of sprint performance.

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Harry G. Banyard, Kazunori Nosaka, Alex D. Vernon, and G. Gregory Haff

Purpose: To examine the reliability of peak velocity (PV), mean propulsive velocity (MPV), and mean velocity (MV) in the development of load–velocity profiles (LVP) in the full-depth free-weight back squat performed with maximal concentric effort. Methods: Eighteen resistance-trained men performed a baseline 1-repetition maximum (1-RM) back-squat trial and 3 subsequent 1-RM trials used for reliability analyses, with 48-h intervals between trials. 1-RM trials comprised lifts from 6 relative loads including 20%, 40%, 60%, 80%, 90%, and 100% 1-RM. Individualized LVPs for PV, MPV, or MV were derived from loads that were highly reliable based on the following criteria: intraclass correlation coefficient (ICC) >.70, coefficient of variation (CV) ≤10%, and Cohen d effect size (ES) <0.60. Results: PV was highly reliable at all 6 loads. MPV and MV were highly reliable at 20%, 40%, 60%, 80%, and 90% but not 100% 1-RM (MPV: ICC = .66, CV = 18.0%, ES = 0.10, SEM = 0.04 m·s−1; MV: ICC = .55, CV = 19.4%, ES = 0.08, SEM = 0.04 m·s−1). When considering the reliable ranges, almost perfect correlations were observed for LVPs derived from PV20–100% (r = .91–.93), MPV20–90% (r = .92–.94), and MV20–90% (r = .94–.95). Furthermore, the LVPs were not significantly different (P > .05) between trials or movement velocities or between linear regression versus 2nd-order polynomial fits. Conclusions: PV20–100%, MPV20–90%, and MV20–90% are reliable and can be utilized to develop LVPs using linear regression. Conceptually, LVPs can be used to monitor changes in movement velocity and employed as a method for adjusting sessional training loads according to daily readiness.

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Lachlan P. James, Emma M. Beckman, Vincent G. Kelly, and G. Gregory Haff

Purpose:

To determine whether the maximal strength, impulse, and power characteristics of competitive mixed-martial-arts (MMA) athletes differ according to competition level.

Methods:

Twenty-nine male semiprofessional and amateur MMA competitors were stratified into either higher-level (HL) or lower-level (LL) performers on the basis of competition grade and success. The 1-repetition-maximum (1RM) squat was used to assess lower-body dynamic strength, and a spectrum of impulse, power, force, and velocity variables were evaluated during an incremental-load jump squat. In addition, participants performed an isometric midthigh pull (IMTP) and 1RM bench press to determine whole-body isometric force and upper-body dynamic strength capabilities, respectively. All force and power variables were expressed relative to body mass (BM).

Results:

The HL competitors produced significantly superior values across a multitude of measures. These included 1RM squat strength (1.84 ± 0.23 vs 1.56 ± 0.24 kg BM; P = .003), in addition to performance in the incremental-load jump squat that revealed greater peak power (P = .005–.002), force (P = .002–.004), and velocity (P = .002–.03) at each load. Higher measures of impulse (P = .01–.04) were noted in a number of conditions. Average power (P = .002–.02) and velocity (P = .01–.04) at all loads in addition to a series of rate-dependent measures were also superior in the HL group (P = .005–.02). The HL competitors’ 1RM bench-press values approached significantly greater levels (P = .056) than the LL group’s, but IMTP performance did not differ between groups.

Conclusions:

Maximal lower-body neuromuscular capabilities are key attributes distinguishing HL from LL MMA competitors. This information can be used to inform evidenced-based training and performance-monitoring practices.

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Stephen J. Rossi, Thomas W. Buford, Douglas B. Smith, Robin Kennel, Erin E. Haff, and G. Gregory Haff

Purpose:

The primary purpose of this study was to simultaneously analyze both ends of the barbell with 19 weightlifters (age 18.0 ± 3.2 years, body mass 84.0 ± 14.2 kg, height 167.3 ± 8.7 cm) participating in a weightlifting competition to determine whether there were asymmetries in barbell kinematics and kinetics between the right and left sides of the barbell. The second purpose was to compare barbell-trajectory classification of the snatch and clean lifts between the right and left sides of the barbell.

Methods:

Barbell kinematic and kinetic data were collected and analyzed with 2 VS-120 weightlifting-analysis systems (Lipman Electronic Engineering Ltd, Ramat Hahayal, Israel). Barbell trajectories (A, B, and C) for the right and left sides were analyzed for each lift.

Results:

No significant difference was found in trajectory classification between sides of the barbell for either lift. The frequencies analysis revealed that type C barbell trajectories were the most prevalent in each lift. When the right and left sides of the barbell were compared during the snatch and clean, no significant differences were determined for any kinematic or kinetic variables.

Conclusions:

The V-scope system appears to facilitate analysis of barbell kinematics, kinetics, and trajectories during weightlifting competition regardless of which side of the barbell is analyzed.

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Michael H. Stone, William A. Sands, Kyle C. Pierce, Michael W. Ramsey, and G. Gregory Haff

Purpose:

To assess the effects of manipulating the loading of successive sets of midthigh clean pulls on the potentiation capabilities of 7 international-level US weightlifters (4 men, 3 women).

Methods:

Isometric and dynamic peak-force characteristics were measured with a force plate at 500 Hz. Velocity during dynamic pulls was measured using 2 potentiometers that were suspended from the top of the right and left sides of the testing system and attached to both ends of the bar. Five dynamic-performance trials were used (in the following order) as the potentiation protocol: women at 60, 80, 100, 120, and 80 kg and men at 60, 140, 180, 220, and 140 kg. Trials 2 vs 5 were specifically analyzed to assess potentiation capabilities. Isometric midthigh pulls were assessed for peak force and rate of force development. Dynamic lifts were assessed for peak force (PF), peak velocity (PV), peak power (PP), and rate of force development (RFD).

Results:

Although all values (PF, PV, PP, and RFD) were higher postpotentiation, the only statistically higher value was found for PV (ICCα = .95, P = .011, η2 = .69).

Conclusions:

Results suggest that manipulating set-loading configuration can result in a potentiation effect when heavily loaded sets are followed by a lighter set. This potentiation effect was primarily characterized by an increase in the PV in elite weightlifters.

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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.

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Joseph O.C. Coyne, Sophia Nimphius, Robert U. Newton, and G. Gregory Haff

Purpose: Criticisms of the acute to chronic workload ratio (ACWR) have been that the mathematical coupling inherent in the traditional calculation of the ACWR results in a spurious correlation. The purposes of this commentary are (1) to examine how mathematical coupling causes spurious correlations and (2) to use a case study from actual monitoring data to determine how mathematical coupling affects the ACWR. Methods: Training and competition workload (TL) data were obtained from international-level open-skill (basketball) and closed-skill (weightlifting) athletes before their respective qualifying tournaments for the 2016 Olympic Games. Correlations between acute TL, chronic TL, and the ACWR as coupled/uncoupled variations were examined. These variables were also compared using both rolling averages and exponentially weighted moving averages to account for any potential benefits of one calculation method over another. Results: Although there were some significant differences between coupled and uncoupled chronic TL and ACWR data, the effect sizes of these differences were almost all trivial (g = 0.04–0.21). Correlations ranged from r = .55 to .76, .17 to .53, and .88 to .99 for acute to chronic TL, acute to uncoupled chronic TL, and ACWR to uncoupled ACWR, respectively. Conclusions: There may be low risk of mathematical coupling causing spurious correlations in the TL–injury-risk relationship. Varying levels of correlation seem to exist naturally between acute and chronic TL variables regardless of coupling. The trivial to small effect sizes and large to nearly perfect correlations between coupled and uncoupled AWCRs also imply that mathematical coupling may have little effect on either calculation method, if practitioners choose to apply the ACWR for TL monitoring purposes.