Comparison of velocity-based and traditional 1RM-percent-based prescription on acute kinetic and kinematic variables

Purpose: This study compared kinetic and kinematic data from three different velocity-based training (VBT) sessions and a 1-repetition maximum (1RM) percent-based training (PBT) session using full-depth, free-weight back squats with maximal concentric effort. Methods: Fifteen strength-trained men performed four randomized resistance-training sessions 96-hours apart: PBT session involved five sets of five repetitions using 80%1RM; load-velocity profile (LVP) session contained five sets of five repetitions with a load that could be adjusted to achieve a target velocity established from an individualized LVP equation at 80%1RM; fixed sets 20% velocity loss threshold (FSVL20) session that consisted of five sets at 80%1RM but sets were terminated once the mean velocity (MV) dropped below 20% of the threshold velocity or when five repetitions were completed per set; variable sets 20% velocity loss threshold (VSVL20) session comprised 25-repetitions in total, but participants performed as many repetitions in a set as possible until the 20% velocity loss threshold was exceeded. Results: When averaged across all repetitions, MV and peak velocity (PV) were significantly (p<0.05) faster during the LVP (MV: ES=1.05; PV: ES=1.12) and FSVL20 (MV: ES=0.81; PV: ES=0.98) sessions compared to PBT. Mean time under tension (TUT) and concentric TUT were significantly less during the LVP session compared to PBT. FSVL20 session had significantly less repetitions, total TUT and concentric TUT than PBT. No significant differences were found for all other measurements between any of the sessions. Conclusions: VBT permits faster velocities, avoids additional unnecessary mechanical stress but maintains similar measures of force and power output compared to strength-oriented PBT

Readiness to train: Return to baseline strength and velocity following strength or power training

This study investigated the return to baseline of movement velocity and maximal strength following a strength-orientated session and power-orientated session in the free-weight back-squat performed with maximal concentric velocity. Fourteen strength-trained males completed a strength-orientated session (five sets of five repetitions @80% of a one-repetition maximum) and a power-orientated session (three sets of six repetitions @50% one-repetition maximum ) in a randomised order over two weeks (e.g. strength week 1, power week 2). The back-squat was then performed with loads of 20%, 40%, 60%, 80%, 90% and 100% one-repetition maximum at 24, 48, 72 and 96 h following the strength and power exercise sessions to assess return to baseline of squat velocity and maximal strength. Dependent variables included one-repetition maximum, back-squat mean velocity and peak velocity and countermovement jump peak velocity. Meaningful changes ((effect size) ≥ −0.60) were reported for mean velocity and peak velocity at loads ≥ 60% one-repetition maximum at 24 and 48 h after the strength-orientated session. Trivial to small (effect size ≤ −0.59) differences were reported for squat velocities following the power-orientated session. Only trivial to small effect size differences were observed for countermovement jump peak velocity and one-repetition maximum at all time points following both sessions. Squat velocity (mean velocity and peak velocity) across the load–velocity profile had recovered at 72 h following the strength-orientated session. However, the return to baseline of squat velocity (mean velocity and peak velocity) did not coincide with the return to baseline of one-repetition maximum or countermovement jump peak velocity. Therefore, measuring and monitoring meaningful changes in velocity may be a more valid and practical alternative in determining full recovery and readiness to train

Sprint acceleration force-velocity-power characteristics in drafted vs non-drafted junior Australian football players: Preliminary results

This investigation aimed to compare the maximal sprint acceleration profiles of drafted and non-drafted elite junior Australian football (AF) players. Nineteen players (10 drafted and 9 non-drafted) from an elite junior AF state team participated in this study. Instantaneous velocity was measured via radar gun during maximal 30 m sprints. The velocity-time data were analysed to derive individual force-velocity-power characteristics and sprint times. No significant differences existed between groups, however drafted players reached moderately faster maximum velocity (Hedges’ g = 0.70 [-0.08; 1.48] and theoretical maximum velocity (g = 0.65 [-0.13; 1.42]) than non-drafted players indicating a superior ability to apply higher amounts of force at increasing sprinting velocity. Further, drafted players produced moderately higher absolute theoretical maximum force (g = 0.72 [-0.06; 1.50]) and absolute maximum power (g = 0.83 [0.04; 1.62]) which reflects their moderately higher body mass (g = 0.61[-0.16;1.38]). Although not significant, in this sample of elite junior AF players, those drafted into the AFL displayed greater absolute sprint acceleration characteristics and maximal velocity capabilities than their non-drafted counterparts (moderate effect size). Whether force-velocity-power characteristics can be more beneficial in differentiating sprint performance of elite junior Australian footballers compared to the traditional sprint time approach warrants further investigation with a larger sample size

Sprint acceleration characteristics across the Australian football participation pathway

The aim of this study was to compare the force, velocity and power profiles of a maximal sprint acceleration through different competition levels of the Australian Football (AF) participation pathway. One hundred and sixty-two junior AF athletes across five competition levels including State under 18’s (ST 18), State under 16’s (ST 16), local under 18’s (LOC 18), local under 15’s (LOC 15), and local under 14’s (LOC 14) participated in this cross-sectional study. Velocity-time data from maximal sprint accelerations were analysed to derive athlete’s sprint acceleration characteristics and split times. ST 18 showed a more force-orientated profile than the LOC 18 with moderate differences in relative theoretical maximal force (F0) (7.54%), absolute F0 (10.51%), and slope of the force–velocity relationship (Sf-v) (9.27%). Similarly, small differences were found between ST 18 and ST 16 in relative F0 (4.79%) and Sf-v (6.28%). Moderate to extremely large differences were observed between players competing in older (ST 18, LOC 18, ST 16) compared to younger (LOC 15, LOC 14) competition levels highlighting the potential influence of biological maturation. It is recommended that practitioners working with junior AF players to consider developing a force-orientated sprint acceleration profile to improve sprinting performance

Pooled Versus Individualized Load–Velocity Profiling in the Free-Weight Back Squat and Power Clean

Purpose: This study compared pooled against individualized load–velocity profiles (LVPs) in the free-weight back squat and power clean. Methods: A total of 10 competitive weightlifters completed baseline 1-repetition maximum assessments in the back squat and power clean. Three incremental LVPs were completed, separated by 48 to 72 hours. Mean and peak velocity were measured via a linear-position transducer (GymAware). Linear and nonlinear (second-order polynomial) regression models were applied to all pooled and individualized LVP data. A combination of coefficient of variation (CV), intraclass correlation coefficient, typical error of measurement, and limits of agreement assessed between-subject variability and within-subject reliability. Acceptable reliability was defined a priori as intraclass correlation coefficient > .7 and CV < 10%. Results: Very high to practically perfect inverse relationships were evident in the back squat (r = .83–.96) and power clean (r = .83–.89) for both regression models; however, stronger correlations were observed in the individualized LVPs for both exercises (r = .85–.99). Between-subject variability was moderate to large across all relative loads in the back squat (CV = 8.2%–27.8%) but smaller in the power clean (CV = 4.6%–8.5%). The power clean met our criteria for acceptable reliability across all relative loads; however, the back squat revealed large CVs in loads ≥90% of 1-repetition maximum (13.1%–20.5%). Conclusions: Evidently, load– velocity characteristics are highly individualized, with acceptable levels of reliability observed in the power clean but not in the back squat (≥90% of 1-repetition maximum). If practitioners want to adopt load–velocity profiling as part of their testing and monitoring procedures, an individualized LVP should be utilized over pooled LVPs

Comparison between back squat, Romanian deadlift, and barbell hip thrust for leg and hip muscle activities during hip extension

This study compared muscle activities of vastus lateralis (VL), biceps femoris (BF), and gluteus maximus (GM) during the back squat (SQ), Romanian deadlift (RDL), and barbell hip thrust (BHT) exercises performed with the same load (60 kg) and at one repetition maximum (1RM). Eight men with a minimum of 1 year\u27s lower-body strength training experience performed the exercises in randomized order. Before each exercise, surface electromyography (EMG) was recorded during a maximal voluntary isometric contraction (MVIC) and then used to normalize to each muscle\u27s EMG during each trial. Barbell hip thrust showed higher GM activity than the SQ (effect size [ES] = 1.39, p = 0.038) but was not significantly different from RDL (ES = 0.49, p = 0.285) at 1RM. Vastus lateralis activity at 1RM during the SQ was significantly greater than RDL (ES = 1.36, p = 0.002) and BHT (ES = 2.27, p = 0.009). Gluteus maximus activity was higher during MVIC when compared with the 60 kg load for the SQ (ES = 1.29, p = 0.002) and RDL (ES = 1.16, p = 0.006) but was similar for the BHT (ES = 0.22, p = 0.523). There were no significant differences in GM (ES = 0.35, p = 0.215) and BF activities (ES = 0.16, p = 0.791) between 1RM and MVIC for the SQ. These findings show that the RDL was equally as effective as the BHT for isolating the hip extensors, while the SQ simultaneously activated the hip and knee extensors

Discriminating Talent Identified Junior Australian Footballers Using a Fundamental Gross Athletic Movement Assessment

Talent identification (TID) is a pertinent component of the sports sciences, affording practitioners the opportunity to target developmental interventions to a select few; optimising financial investments. However, TID is multi-componential, requiring the recognition of immediate and prospective performance. The measurement of athletic movement skill may afford practitioners insight into the latter component given its augmented relationship with functional sport specific qualities. It is currently unknown whether athletic movement skill is a discriminant quality in junior Australian football (AF). This study aimed to discriminate talent identified junior AF players from their non-talent identified counterparts using a fundamental gross athletic movement assessment. From a total of 50 under 18 (U18) AF players; two groups were classified a priori based on selection level; talent identified (n = 25; state academy representatives) and non-talent identified (n = 25; state-based competition representatives). Players performed a fundamental gross athletic movement assessment based on the Athletic Ability Assessment (AAA), consisting of an overhead squat, double lunge (left and right legs), single leg Romanian deadlift (left and right legs), and a push up (six movement criterions). Movements were scored across three assessment points using a three-point scale (resulting in a possible score of nine for each movement). A multivariate analysis of variance revealed significant between group effects on four of the six movement criterions (d = 0.56 – 0.87; p = 0.01 – 0.02). Binary logistic regression models and a receiver operating characteristic curve inspection revealed that the overhead squat score provided the greatest group discrimination (β(SE) = -0.89(0.44); p < 0.05), with a score of 4.5 classifying 64% and 88% of the talent identified and non-talent identified groups, respectively. Results support the integration of this assessment into contemporary talent identification approaches in junior AF, as it may provide coaches with insight into a juniors developmental potential