Longitudinal Development of Sprint Performance and Force-Velocity-Power Characteristics: Influence of Biological Maturation.

ABSTRACT: Edwards, T, Weakley, J, Banyard, HG, Cripps, A, Piggott, B, Haff, GG, and Joyce, C. Longitudinal development of sprint performance and force-velocity-power characteristics: influence of biological maturation. J Strength Cond Res 37(11): 2178-2184, 2023-This study was designed to investigate the influence of biological maturation on the longitudinal development of sprint performance. Thirty-two subjects performed 2 assessments of maximal sprint performance that were separated by 18 months. Each sprint assessment was measured through a radar gun that collected instantaneous velocity with the velocity-time data used to derive sprint times and force-velocity-power characteristics. The biological maturity of each subject was assessed using a predictive equation, and subjects were grouped according to predicted years from peak height velocity (circa-PHV: -1.0 to 1.0; post-PHV: >1.0). A 2 × 2 mixed model analysis of variance was used to assess group × time interactions, and paired t -tests were used to assess the longitudinal changes for each maturity group. No significant group × time interactions were observed for any sprint time or force-velocity-power characteristic. The circa-PHV group experienced significant within-group changes in maximal theoretical velocity (6.35 vs. 5.47%; effect size [ES] = 1.26 vs. 0.52) and 5-m sprint time (-3.63% vs. -2.94%; ES = -0.64 vs. -0.52) compared with the post-PHV group. There was no significant change in the magnitude of relative theoretical maximum force in either group; however, both the circa-PHV and post-PHV groups significantly improved the orientation of force production at the start of the sprint (RFmax [4.91 vs. 4.46%; ES = 0.79 vs. 0.74, respectively]). Considering these findings, it is recommended that practitioners adopt training methods aimed to improve relative lower-limb force production, such as traditional strength training and sled pulling and pushing, to improve sprint performance and relative theoretical maximum force.

Comparison of Countermovement Jump and Squat Jump Performance Between 627 State and Non-State Representative Junior Australian Football Players.

ABSTRACT: Edwards, T, Weakley, J, Woods, CT, Breed, R, Benson, AC, Suchomel, TJ, and Banyard, HG. Comparison of countermovement jump and squat jump performance between 627 state and non-state representative junior Australian football players. J Strength Cond Res 37(3): 641-645, 2023-This cross-sectional study investigated differences in lower-body power of state and nonstate representative junior Australian football (AF) players through countermovement jump (CMJ) and squat jump (SJ) performance. A total of 627 players performed the CMJ and SJ at the end of the preseason phase over a 2-week period, with each player grouped according to their age (under 18 [U18] or under 16 [U16]), and highest competition level played (state representation and nonstate representation). One-way multivariate analysis of variance (MANOVA), follow up ANOVA's, and Cohen's d effect sizes were used to identify significant main effects and between-group differences. Statistical significance was set at α < 0.05. Significant small-to-moderate effect size differences were observed between competition level, with state U18 and U16 players recording greater CMJ and SJ height, and peak power (PP), compared with their nonstate representative peers, respectively. Similarly, significant small-to-moderate effect size differences existed between age groups, with nonstate U18 players recording greater CMJ and SJ height and PP than nonstate U16 counterparts. However, state U18 and state U16 only differed in CMJ PP. No differences were found between competition level or age groups for the difference between CMJ and SJ jump height (CMJSJ diff ). Together, these findings suggest that state and nonstate representative junior AFs may have a similar ability to use the stretch-shortening cycle, despite state representative players jumping higher in the CMJ and SJ.

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.

The Effect of a Heavy Resisted Sled-Pull Mesocycle on Sprint Performance in Junior Australian Football Players.

ABSTRACT: Edwards, T, Piggott, B, Banyard, HG, Haff, GG, and Joyce, C. The effect of a heavy resisted sled-pull mesocycle on sprint performance in junior Australian football players. J Strength Cond Res 37(2): 388-393, 2023-This study assessed the effect of heavy resisted sled-pull training on sprint times and force, velocity, and power characteristics in junior Australian football players. Twenty-six athletes completed a 6-week resisted sled-pull training intervention which included 10 training sessions and 1-week taper. Instantaneous velocity during 2 maximal 30 m sprints was recorded 1 week before and 1 week after the intervention with a radar gun. Velocity-time data were used to derive sprint performance and force, velocity, and power characteristics. A paired t -test assessed the within-group differences between preintervention and postintervention testing. Statistical significance was accepted at p ≤ 0.05. Hedges' g effect sizes (ESs) were used to determine the magnitude of change in dependent variables. Maximum velocity (ES = 1.33) and sprint times at all distances (ES range 0.80-1.41) significantly improved after heavy resisted sled-pull training. This was reflected in sprint force, velocity, and power characteristics with significant improvements in relative theoretical force (ES = 0.63), theoretical velocity (ES = 0.99), relative maximum power (ES = 1.04), and ratio of horizontal to vertical force (ES = 0.99). Despite the multifactorial nature of training and competing physical demands associated with preseason training, these findings imply that a short, resisted sled-pull training mesocycle may improve sprint performance and underlying force, velocity, and power characteristics in junior athletes.

Reliability and Minimal Detectable Change of Sprint Times and Force-Velocity-Power Characteristics.

ABSTRACT: Edwards, T, Banyard, HG, Piggott, B, Haff, GG, and Joyce, C. The reliability and minimal detectable change of sprint times and force-velocity-power characteristics. J Strength Cond Res 36(1): 268-272, 2022-Research has not yet provided critical information for practitioners to determine the minimal detectable change (MDC) in sprint times or force-velocity-power characteristics. Therefore, the aim of this study was to establish the interday reliability and MDC of sprint times and sprint force-velocity-power characteristics in junior Australian football (AF) players. Seventeen players were assessed using a radar device that recorded instantaneous velocity during 3 maximal 30-m sprint accelerations performed on 2 nonconsecutive days. Sprint force, velocity, and power characteristics were derived through inverse dynamics applied to the raw velocity-time data. Relative and absolute reliability was determined by calculating the intraclass correlation coefficient (ICC), coefficient of variation (CV), and MDC. Data analysis was assessed for (a) the first trial, (b) the best trial (the fastest 30-m split time), (c) the average of the first 2 trials, and (d) the average of all 3 trials from each testing session. The main findings were (a) absolute theoretical maximum force (F0), theoretical maximal velocity (V0), absolute and relative maximum power (Pmax), maximum ratio of force (RFmax), maximum velocity (Vmax), and all sprint distance times (5-30 m) displayed acceptable reliability (CV < 10% and ICC >0.75) and 2) the average of 2 and 3 trials was the best method of establishing reliable sprint times and force-velocity-power characteristics between sessions. This study provides important information for practitioners to determine the MDC in sprint times and force-velocity-power characteristics that allow coaches to identify true changes in performance.

Influence of age and maturation status on sprint acceleration characteristics in junior Australian football.

This study aimed to investigate the influence of chronological age and maturation status on sprint acceleration characteristics in junior Australian football (AF) players. Biological maturity of 109 subjects was assessed and subjects were grouped according to predicted years from peak height velocity (PHV) (pre-, mid-, and post-PHV) and chronological age (13 years, 14 years, and 15 years). A one-way multivariate analysis of variance and magnitude-based decisions were used to determine between-group differences. Instantaneous velocity was measured during two maximal 30m sprints via radar gun with the velocity-time data used to derive the force, velocity, and power characteristics. Chronologically, the greatest differences were observed between the 13 and 14 year old groups with the latter group producing likely greater relative maximum power (Pmax) (ES[effect size]=0.44) and theoretical maximal velocity (V0) (ES=0.49). The post-PHV group likely demonstrated a greater ability to apply force at faster velocity (V0; ES=0.59) and orient the force in a horizontal direction (Drf%; ES=-0.49) than the mid-PHV group. No differences in relative theoretical maximal force (F0) were observed between groups. Considering the findings, practitioners should aim to improve relative lower limb strength through heavy sled push or sled pulls and traditional strength training exercises to improve relative F0.

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.

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.

Superior Changes in Jump, Sprint, and Change-of-Direction Performance but Not Maximal Strength Following 6 Weeks of Velocity-Based Training Compared With 1-Repetition-Maximum Percentage-Based Training.

PURPOSE: To compare the effects of velocity-based training (VBT) and 1-repetition-maximum (1RM) percentage-based training (PBT) on changes in strength, loaded countermovement jump (CMJ), and sprint performance. METHODS: A total of 24 resistance-trained males performed 6 weeks of full-depth free-weight back squats 3 times per week in a daily undulating format, with groups matched for sets and repetitions. The PBT group lifted with fixed relative loads varying from 59% to 85% of preintervention 1RM. The VBT group aimed for a sessional target velocity that was prescribed from pretraining individualized load-velocity profiles. Thus, real-time velocity feedback dictated the VBT set-by-set training load adjustments. Pretraining and posttraining assessments included the 1RM, peak velocity for CMJ at 30%1RM (PV-CMJ), 20-m sprint (including 5 and 10 m), and 505 change-of-direction test (COD). RESULTS: The VBT group maintained faster (effect size [ES] = 1.25) training repetitions with less perceived difficulty (ES = 0.72) compared with the PBT group. The VBT group had likely to very likely improvements in the COD (ES = -1.20 to -1.27), 5-m sprint (ES = -1.17), 10-m sprint (ES = -0.93), 1RM (ES = 0.89), and PV-CMJ (ES = 0.79). The PBT group had almost certain improvements in the 1RM (ES = 1.41) and possibly beneficial improvements in the COD (ES = -0.86). Very likely favorable between-groups effects were observed for VBT compared to PBT in the PV-CMJ (ES = 1.81), 5-m sprint (ES = 1.35), and 20-m sprint (ES = 1.27); likely favorable between-groups effects were observed in the 10-m sprint (ES = 1.24) and nondominant-leg COD (ES = 0.96), whereas the dominant-leg COD (ES = 0.67) was possibly favorable. PBT had small (ES = 0.57), but unclear differences for 1RM improvement compared to VBT. CONCLUSIONS: Both training methods improved 1RM and COD times, but PBT may be slightly favorable for stronger individuals focusing on maximal strength, whereas VBT was more beneficial for PV-CMJ, sprint, and COD improvements.

Using a Load-Velocity Relationship to Predict One repetition maximum in Free-Weight Exercise: A Comparison of the Different Methods.

Hughes, LJ, Banyard, HG, Dempsey, AR, and Scott, BR. Using a load-velocity relationship to predict one repetition maximum in free-weight exercise: a comparison of the different methods. J Strength Cond Res 33(9): 2409-2419, 2019-The purpose of this study was to investigate the reliability and validity of predicting 1 repetition maximum (1RM) in trained individuals using a load-velocity relationship. Twenty strength-trained men (age: 24.3 ± 2.9 years, height: 180.1 ± 5.9 cm, and body mass: 84.2 ± 10.5 kg) were recruited and visited the laboratory on 3 occasions. The load-velocity relationship was developed using the mean concentric velocity of repetitions performed at loads between 20 and 90% 1RM. Predicted 1RM was calculated using 3 different methods discussed in existing research: minimal velocity threshold 1RM (1RMMVT), load at zero velocity 1RM (1RMLD0), and force-velocity 1RM methods (1RMFV). The reliability of 1RM predictions was examined using intraclass correlation coefficient (ICC) and coefficient of variation (CV). 1RMMVT demonstrated the highest reliability (ICC = 0.92-0.96, CV = 3.6-5.0%), followed by 1RMLD0 (ICC = 0.78-0.82, CV = 8.2-8.6%) and 1RMFV (ICC = -0.28 to 0.00, CV = N/A). Both 1RMMVT and 1RMLD0 were very strongly correlated with measured 1RM (r = 0.91-0.95). The only method which was not significantly different to measured 1RM was the 1RMLD0 method. However, when analyzed on an individual basis (using Bland-Altman plots), all methods exhibited a high degree of variability. Overall, the results suggest that the 1RMMVT and 1RMLD0 predicted 1RM values could be used to monitor strength progress in trained individuals without the need for maximal testing. However, given the significant differences between 1RMMVT and measured 1RM, and the high variability associated with individual predictions performed using each method, they cannot be used interchangeably; therefore, it is recommended that predicted 1RM is not used to prescribe training loads as has been previously suggested.

Comparison Between Back Squat, Romanian Deadlift, and Barbell Hip Thrust for Leg and Hip Muscle Activities During Hip Extension.

Delgado, J, Drinkwater, EJ, Banyard, HG, Haff, GG, and Nosaka, K. Comparison between back squat, Romanian deadlift, and barbell hip thrust for leg and hip muscle activities during hip extension. J Strength Cond Res 33(10): 2595-2601, 2019-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's 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's 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.

Comparison of the Effects of Velocity-Based Training Methods and Traditional 1RM-Percent-Based Training Prescription on Acute Kinetic and Kinematic Variables.

PURPOSE: To compare kinetic and kinematic data from 3 different velocity-based training 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 4 randomized resistance-training sessions 96 h apart: PBT session involved 5 sets of 5 repetitions using 80% 1RM; load-velocity profile (LVP) session contained 5 sets of 5 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 consisted of 5 sets at 80% 1RM, but sets were terminated once the mean velocity (MV) dropped below 20% of the threshold velocity or when 5 repetitions were completed per set; and variable sets 20% velocity loss threshold 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 < .05) faster during the LVP (MV effect size [ES] = 1.05; PV ES = 1.12) and FSVL20 (MV ES = 0.81; PV ES = 0.98) sessions compared with PBT. Mean time under tension (TUT) and concentric TUT were significantly less during the LVP sessions compared with PBT. The FSVL20 sessions 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: Velocity-based training permits faster velocities and avoids additional unnecessary mechanical stress but maintains similar measures of force and power output compared with strength-oriented PBT in a single training session.

Using Load-Velocity Relationships to Quantify Training-Induced Fatigue.

Hughes, LJ, Banyard, HG, Dempsey, AR, Peiffer, JJ, and Scott, BR. Using load-velocity relationships to quantify training-induced fatigue. J Strength Cond Res 33(3): 762-773, 2019-The purpose of this study was to investigate using load-velocity relationships to quantify fluctuations in maximal strength (1 repetition maximum [1RM]), which occur as a result of training-induced fatigue. The 19 well-trained men (age: 24.3 ± 2.9 years, height: 180.1 ± 5.9 cm, body mass: 84.2 ± 10.5 kg, and squat 1RM: 151.1 ± 25.7 kg) who were recruited for this study attended 5 sessions. After baseline strength testing, individual load-velocity relationships were established using mean concentric velocity during visits 2, 4, and 5, with visit 3 consisting of a bout of fatiguing exercise (5 sets of squats performed to muscular failure with 70% 1RM). Predicted 1RM values were calculated using the minimal velocity threshold (1RMMVT), load at zero velocity (1RMLD0), and force-velocity (1RMFV) methods. Measured 1RM, maximal voluntary contractions, and perceived muscle soreness were used to examine the effects of fatigue in relation to the predicted 1RM scores. The 1RMMVT and 1RMLD0 demonstrated very strong and strong correlations with measured 1RM during each of the sessions (r = 0.90-0.96 and r = 0.77-0.84, respectively), while no strong significant correlations were observed for the 1RMFV. Further analysis using Bland-Altman plots demonstrated substantial interindividual variation associated with each method. These results suggest that load-velocity-based 1RM predictions are not accurate enough to be used for daily training load prescription, as has been previously suggested. Nevertheless, these predictions are practical to implement during an individual's warm-up and may be useful to indicate general fluctuations in performance potential, particularly if used in conjunction with other common monitoring methods.

The Reliability of Individualized Load-Velocity Profiles.

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.

The efficacy of periodised resistance training on neuromuscular adaptation in older adults.

PURPOSE: This study compared the effect of periodised versus non-periodised (NP) resistance training on neuromuscular adaptions in older adults. METHODS: Forty-one apparently healthy untrained older adults (female = 21, male = 20; 70.9 ± 5.1 years; 166.3 ± 8.2 cm; 72.9 ± 13.4 kg) were recruited and randomly stratified to an NP, block periodised (BP), or daily undulating periodised (DUP) training group. Outcome measures were assessed at baseline and following a 22-week resistance training intervention (3 day week-1), including: muscle cross-sectional area (CSA), vertical jump performance, isometric and isokinetic peak torque, isometric rate of force development (RFD), and muscle activation. Thirty-three participants satisfied all study requirements and were included in analyses (female = 17, male = 16; 71.3 ± 5.4 years; 166.3 ± 8.5 cm; 72.5 ± 13.7 kg). RESULTS: Block periodisation, DUP, and NP resistance training induced statistically significant improvements in muscle CSA, vertical jump peak velocity, peak power and jump height, and peak isometric and isokinetic torque of the knee extensors at 60 and 180° s-1, with no between-group differences. Muscle activity and absolute RFD measures were statistically unchanged following resistance training across the entire cohort. CONCLUSIONS: Periodised resistance training, specifically BP and DUP, and NP resistance training are equally effective for promoting increases in muscular hypertrophy, strength, and power among untrained older adults. Consequently, periodisation strategies are not essential for optimising neuromuscular adaptations during the initial stages of resistance training in the aging population.

Validity of Various Methods for Determining Velocity, Force, and Power in the Back Squat.

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.

Identifying the Physical Fitness, Anthropometric and Athletic Movement Qualities Discriminant of Developmental Level in Elite Junior Australian Football: Implications for the Development of Talent.

Gaudion, SL, Doma, K, Sinclair, W, Banyard, HG, and Woods, CT. Identifying the physical fitness, anthropometric and athletic movement qualities discriminant of developmental level in elite junior Australian football: implications for the development of talent. J Strength Cond Res 31(7): 1830-1839, 2017-This study aimed to identify the physical fitness, anthropometric and athletic movement qualities discriminant of developmental level in elite junior Australian football (AF). From a total of 77 players, 2 groups were defined according to their developmental level; under 16 (U16) (n = 40, 15.6 to 15.9 years), and U18 (n = 37, 17.1 to 17.9 years). Players performed a test battery consisting of 7 physical fitness assessments, 2 anthropometric measurements, and a fundamental athletic movement assessment. A multivariate analysis of variance tested the main effect of developmental level (2 levels: U16 and U18) on the assessment criterions, whilst binary logistic regression models and receiver operating characteristic (ROC) curves were built to identify the qualities most discriminant of developmental level. A significant effect of developmental level was evident on 9 of the assessments (d = 0.27-0.88; p ≤ 0.05). However, it was a combination of body mass, dynamic vertical jump height (nondominant leg), repeat sprint time, and the score on the 20-m multistage fitness test that provided the greatest association with developmental level (Akaike's information criterion = 80.84). The ROC curve was maximized with a combined score of 180.7, successfully discriminating 89 and 60% of the U18 and U16 players, respectively (area under the curve = 79.3%). These results indicate that there are distinctive physical fitness and anthropometric qualities discriminant of developmental level within the junior AF talent pathway. Coaches should consider these differences when designing training interventions at the U16 level to assist with the development of prospective U18 AF players.

Cluster Sets: Permitting Greater Mechanical Stress Without Decreasing Relative Velocity.

PURPOSE: To determine the effects of intraset rest frequency and training load on muscle time under tension, external work, and external mechanical power output during back-squat protocols with similar changes in velocity. METHODS: Twelve strength-trained men (26.0 ± 4.2 y, 83.1 ± 8.8 kg, 1.75 ± 0.06 m, 1.88:0.19 one-repetition-maximum [1RM] body mass) performed 3 sets of 12 back squats using 3 different set structures: traditional sets with 60% 1RM (TS), cluster sets of 4 with 75% 1RM (CS4), and cluster sets of 2 with 80% 1RM (CS2). Repeated-measures ANOVAs were used to determine differences in peak force (PF), mean force (MF), peak velocity (PV), mean velocity (MV), peak power (PP), mean power (MP), total work (TW), total time under tension (TUT), percentage mean velocity loss (%MVL), and percentage peak velocity loss (%PVL) between protocols. RESULTS: Compared with TS and CS4, CS2 resulted in greater MF, TW, and TUT in addition to less MV, PV, and MP. Similarly, CS4 resulted in greater MF, TW, and TUT in addition to less MV, PV, and MP than TS did. There were no differences between protocols for %MVL, %PVL, PF, or PP. CONCLUSIONS: These data show that the intraset rest provided in CS4 and CS2 allowed for greater external loads than with TS, increasing TW and TUT while resulting in similar PP and %VL. Therefore, cluster-set structures may function as an alternative method to traditional strength- or hypertrophy-oriented training by increasing training load without increasing %VL or decreasing PP.

Reliability and Validity of the Load-Velocity Relationship to Predict the 1RM Back Squat.

Banyard, HG, Nosaka, K, and Haff, GG. Reliability and validity of the load-velocity relationship to predict the 1RM back squat. J Strength Cond Res 31(7): 1897-1904, 2017-This study investigated the reliability and validity of the load-velocity relationship to predict the free-weight back squat one repetition maximum (1RM). Seventeen strength-trained males performed three 1RM assessments on 3 separate days. All repetitions were performed to full depth with maximal concentric effort. Predicted 1RMs were calculated by entering the mean concentric velocity of the 1RM (V1RM) into an individualized linear regression equation, which was derived from the load-velocity relationship of 3 (20, 40, 60% of 1RM), 4 (20, 40, 60, 80% of 1RM), or 5 (20, 40, 60, 80, 90% of 1RM) incremental warm-up sets. The actual 1RM (140.3 ± 27.2 kg) was very stable between 3 trials (ICC = 0.99; SEM = 2.9 kg; CV = 2.1%; ES = 0.11). Predicted 1RM from 5 warm-up sets up to and including 90% of 1RM was the most reliable (ICC = 0.92; SEM = 8.6 kg; CV = 5.7%; ES = -0.02) and valid (r = 0.93; SEE = 10.6 kg; CV = 7.4%; ES = 0.71) of the predicted 1RM methods. However, all predicted 1RMs were significantly different (p ≤ 0.05; ES = 0.71-1.04) from the actual 1RM. Individual variation for the actual 1RM was small between trials ranging from -5.6 to 4.8% compared with the most accurate predictive method up to 90% of 1RM, which was more variable (-5.5 to 27.8%). Importantly, the V1RM (0.24 ± 0.06 m·s) was unreliable between trials (ICC = 0.42; SEM = 0.05 m·s; CV = 22.5%; ES = 0.14). The load-velocity relationship for the full depth free-weight back squat showed moderate reliability and validity but could not accurately predict 1RM, which was stable between trials. Thus, the load-velocity relationship 1RM prediction method used in this study cannot accurately modify sessional training loads because of large V1RM variability.

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 (ß(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.