1RM Back Squat Research Articles

Relationship Between Functional Movement Screen and Athletic Performance

Parchmann, CJ and McBride, JM. Relationship between functional movement screen and athletic performance. J Strength Cond Res 25(12): 3378-3384, 2011-Tests such as the functional movement screen (FMS) and maximal strength (repetition maximum strength [1RM]) have been theorized to assist in predicting athletic performance capabilities. Some data exist concerning 1RM and athletic performance, but very limited data exist concerning the potential ability of FMS to assess athletic performance. The purpose of this investigation was to determine if FMS scores or 1RM is related to athletic performance, specifically in Division I golfers in terms of sprint times, vertical jump (VJ) height, agility T-test times, and club head velocity. Twenty-five National Collegiate Athletic Association Division I golfers (15 men, age = 20.0 ± 1.2 years, height = 176.8 ± 5.6 cm, body mass = 76.5 ± 13.4 kg, squat 1RM = 97.1 ± 21.0 kg) (10 women, age = 20.5 ± 0.8 years, height = 167.0 ± 5.6 cm, body mass = 70.7 ± 21.5 kg, squat 1RM = 50.3 ± 16.6) performed an FMS, 1RM testing, and field tests common in assessing athletic performance. Athletic performance tests included 10- and 20-m sprint time, VJ height, agility T-test time, and club head velocity. Strength testing included a 1RM back squat. Data for 1RM testing were normalized to body mass for comparisons. Correlations were determined between FMS, 1RMs, and athletic performance tests using Pearson product correlation coefficients (p ≤ 0.05). No significant correlations existed between FMS and 10-m sprint time (r = -0.136), 20-m sprint time (r = -0.107), VJ height (r = 0.249), agility T-test time (r = -0.146), and club head velocity (r = -0.064). The 1RM in the squat was significantly correlated to 10-m sprint time (r = -0.812), 20-m sprint time (r = -0.872), VJ height (r = 0.869), agility T-test time (r = -0.758), and club head velocity (r = 0.805). The lack of relationship suggests that FMS is not an adequate field test and does not relate to any aspect of athletic performance. Based on the data from this investigation, 1RM squat strength appears to be a good indicator of athletic performance.

The comparison between individual 2D modelling and experimental data in squat jumps

Intra-individual simulation needs accurate data about actuators (muscles) and force transmission (bones, joints) for obtaining accurate predictions. That work preludes to a more comprehensive 2D jump simulator, dealing with the...

An Investigation into the Acute Effects of Depth Jumps on Maximal Strength Performance

Research has demonstrated that high-load low-velocity (HLLV) exercises (≥85% 1 repetition maximum [1RM]) increase performance in subsequent low-load high-velocity (LLHV) exercises, when separated by a rest period ≥4 minutes. To date, few studies have investigated LLHV exercises on subsequent HLLV exercises. The purpose of this study was to compare the effects of 2, 4, or 6 depth jumps (DJs) on subsequent 1RM back squat performance. Fourteen subjects (age 22 ± 4 years, height 177 ± 10 cm, body mass 80.3 ± 14.4 kg) completed five 1RM back squat testing sessions, either control, retest, or 1 of 3 interventions (2, 4, or 6 DJs from a height of 33 cm, 4 minutes before the first 1RM attempt), in a counterbalanced order. Intraclass correlation coefficients demonstrated a high test-retest reliability for the 1RMs (r = 0.989, p < 0.001). Repeated-measures analysis of variance with Bonferroni post hoc analysis revealed significantly greater 1RM performance (140.71 ± 35.68 kg: p = 0.004, 140.50 ± 33.77 kg: p < 0.001, 141.43 ± 34.39 kg: p = 0.002, respectively) for each intervention (2, 4, or 6 repetitions, respectively) compared to the control condition (132.43 ± 34.56 kg). No significant differences were found between interventions (p > 0.05). The findings of this investigation demonstrate that the inclusion of 2, 4, or 6 DJs, 4 minutes before a maximal squat, enhances subsequent strength performance.

The Effect of Whole-Body Vibration Training and Conventional Strength Training on Performance Measures in Female Athletes

The purpose of this study was to examine the effects of regular whole-body vibration (WBV) training on lower body strength and power. National Collegiate Athletic Association Division III softball athletes (n = 9) completed the 9-week protocol as part of their off-season strength and conditioning program. The athletes were randomly assigned to 1 of 2 groups. Week 1, pretesting included 3 repetition maximum (3RM) back squat, standing long jump (SLJ), and vertical countermovement jump (VCMJ). Phase I training (weeks 2-4) consisted of either WBV training (group 1) or conventional strength training (CST, group 2). The primary programmatic difference between WBV and CST was the inclusion of WBV sets after squat sets. Posttesting (3RM squat, SLJ, VCMJ) occurred at week 5. Phase II training (weeks 6-8) consisted of either WBV training (group 2) or CST (group 1). Posttesting was repeated at week 9 after the completion of phase II. Three 2 × 2 mixed factorial analyses of variance were computed. No significant differences (p > 0.05) were found between groups or between groups and testing period for the SLJ, VCMJ, and estimated 1RM back squat. Increases (p < 0.05) were observed in SLJ, VCMJ, and back squat from pretest to posttest 1. Back squat increased (p < 0.05) from posttest 1 to posttest 2. All the athletes experienced significantly greater (p < 0.05) percent changes from pretest to posttest 1 for SLJ and VCMJ. These results indicate that the inclusion of WBV as part of an off-season strength and conditioning program has no apparent benefit over CST methods for collegiate softball players.

The Acute Effects of Manipulating Volume and Load of Back Squats on Countermovement Vertical Jump Performance

The acute effects of manipulating the volume and load of back squats on subsequent countermovement vertical jump performance were investigated in the present study. Eleven National Collegiate Athletic Association division II female volleyball players performed 10 countermovement vertical jumps (CMJs) on a force platform 2 minutes after the last squat repetition of a high-load (HL) or high-volume (HV) squat protocol. Two minutes of rest was provided between each CMJ. The HL protocol culminated in the subjects having to perform 3 repetitions with a load equivalent to 90% 1 repetition maximum (1RM) back squat, whereas 12 repetitions with a load equivalent to 37% 1RM were performed in the HV protocol. During an initial familiarization session, knee angles were recorded during a series of CMJs, and these angles were used to control the depth of descent during all subsequent back squats. Jump height (JH) and vertical stiffness (VStiff) were calculated during each of the 10 CMJ, and the change in these variables after the 2 squat protocols was assessed using an analysis of variance model with repeated measures on 2 factors (Protocol [2-levels]; Time [2-levels]). There was no significant difference in JH after the HL and HV protocols (p > 0.05). A significant Protocol × Time interaction for VStiff resulted from the increase after the HL protocol being greater than that after the HV protocol (p = 0.03). The knee angles before the HL and HV protocols were significantly greater than those measured during the initial familiarization session (p = 0.001). Although neither squat protocol provided any benefit in improving JH, the heavy squat protocol produced greater increases in VStiff during the CMJ. Because of the increased VStiff caused by the HL protocol, volleyball coaches may consider using such protocols with their players to improve performance in jumps performed from a run such as the spike and on-court agility.

Comparison of Linear and Daily Undulating Periodization in Resistance Training Using Simple Measures of Overreaching

This study was conducted in an effort to determine if a linear or nonlinear periodized resistance training program had a greater tendency to contribute to a state of overreaching over 8 weeks. Simple outcome measures were used in an effort to determine the onset of overreaching. These measures included average sleeping heart rate, standing broad jump, 10yard dash, seated medicine ball throw, ratings of perceived exertion (RPE), one repetition maximum (1RM) back squat, and 1RM bench press. The participants were 25 (18 female and 7 male) college students in the Kinesiology major at Western Washington University. Subjects were separated into one of three groups: a control, linear periodized (LP), or nonlinear periodized (DUP) training group. After 8 weeks both training groups significantly increased their 1RM back squat and bench press (p<0.05). The DUP group increased their mean 1RM bench press and back squat from 46.30 ±18.47 kg to 50.83 ±19.26 kg and 67.15 ±20.54 kg to 79.34 ± 23.80 kg, respectively. The LP group increased their mean 1RM bench press and back squat from 46.82 ± 25.96 kg to 51.14 ± 25.87 kg and 74.77 ± 33.22 kg to 84.09 ± 30.10 kg, respectively. All groups significantly improved (p<0.05) their standing long jump performance over the course of the study. The control group improved from a mean of 1.86 ± 0.13 m to 2.04 ± 0.17 m, LP from 1.89 ± 0.40 m to 2.03 ± 0.41 m, and DUP from 1.87 ± 0.42 m to 1.99 ± 0.40 m. Only the DUP group significantly improved their seated medicine ball throw performance (p<0.05) from a mean of 4.09 ± 0.78 m to 4.46 ± 0.69 m. The LP and DUP groups significantly decreased (p<0.05) their 10-yard dash times from a mean of 1.85 sec ± 0.15 to 1.75 sec ± 0.18 and 1.84 sec ± 0.14 to 1.77 sec ±0.14, respectively. Average sleeping heart rate and RPE did not change significantly in any group. The lack of a significant decrease in performance measures or increase in average sleeping heart rate or RPE in either training group caused the null hypothesis to be accepted.

Congruency of Velocity Output from Dual, Non-centered Accelerometers During Barbell Jump Squats

One or more transducers may be affixed at the end(s) of a barbell to measure mechanical variables during free-weight lifting tasks. It is unclear if transducer location might affect output, a potential problem if change in performance is being monitored. PURPOSE: To compare peak velocity using dual, non-centered accelerometers during low-load barbell jump squats. METHODS: Fifty-two subjects (27 women & 25 men) with free-weight squat training experience were recruited from a university population. Subjects performed duplicate load-spectrum countermovement jump squats (CMJ) and static jump squats (SJ) (20%, 30% & 40% of the back squat 1RM) on 2 separate days in a counterbalanced sequence. A triaxial accelerometer was directly affixed to each end of the barbell midway between the lateral-most aspect of the shoulder and the thumb side of each hand. Acceleration data were downsampled from 1.5 KHz to 500Hz by averaging every 3 data points. These data were then low-pass filtered (4th order Butterworth) with a cutoff frequency of 10Hz. Velocity was automatically determined from acceleration output by integration. Peak velocity data were obtained concurrently from the 2 accelerometers. Paired t-tests with a Bonferroni adjustment for 6 comparisons were used for data analysis. RESULTS: Accelerometer-derived peak velocities from the two instruments (A1, A2) were different for CMJ at the 30% 1RM load (p = 0.006) and for SJ at the 20% 1RM load (p = 0.001). Mean differences (A1 - A2) at 20, 30, & 40% 1RM loads, respectively, for the CMJ were 4.30, 3.64, and 2.19 cm · s -1, and for the SJ were 3.94, -1.61, and 1.75 cm · s -1. CONCLUSIONS: Exercises using free weights, such as low-load CMJ and SJ, involve multi planar movements. Placing accelerometers at the ends of the barbell during these exercises may affect velocity output and, therefore, may be problematic when monitoring change in performance. Placement of the accelerometer at the midpoint of the bar or use of a lifting apparatus with a horizontally-fixed bar may obviate lift-related discrepancies in velocity output. Although not tested herein, it is likely that linear position and linear velocity transducers would have similar constraints. As contiguous accelerometer placement was not tried herein, it is unclear what, if any, contribution the accelerometers made to measurement error.

Association of Accelerometer-Derived Jump Squat Peak Velocity with Drop Vertical Jump Displacement

Peak velocity during jump squats with relatively light loads would be expected to be positively associated with drop vertical jump (DVJ) displacement. A relatively convenient and inexpensive accelerometer-based dynamometer is now available for measuring velocity and other variables during such activities. PURPOSE: To determine the association of DVJ displacement with jump squat peak velocity measured by the aforementioned accelerometer. METHODS: Fifty-two subjects (25 men, 27 women) with a minimum of three months squat training experience were recruited from a university population. All performed a one repetition maximum (1RM) back squat to 90 degrees of knee flexion with an external load ≥ body weight prior to the experimental phase of the investigation. Subjects then practiced all activities to be assessed on two separate occasions. DVJ and jump squat testing was initiated in a counterbalanced sequence within one week of the last practice session and subsequently repeated 48 hrs later. Flight time data for jump displacement determination were collected using a uniaxial force platform channeled through a signal conditioner/amplifier interfaced to a PC via a 12-bit analog-digital converter and sampled at 500 Hz. Datapac 5™ was utilized for data extraction. Data were low-pass filtered (4th order, zero-lag Butterworth) with a cutoff frequency of 30 Hz. Jump squats consisted of two styles, static (SJ) and countermovement (CMJ), and were performed in duplicate using 20, 30, and 40% of each subject's back squat 1RM. Concurrent measures of peak velocity were obtained using triaxial accelerometers directly affixed to each end of the barbell midway between the lateral-most aspect of the shoulder and the thumb side of each hand. Acceleration data were downsampled from 1.5 KHz to 500 Hz by averaging every three data points via proprietary software. Jump squat velocity was then determined via integration. Since reliabilities for peak velocity using these devices have been shown elsewhere to be marginal, the two-day average for all pertinent variables was used in determining bivariate correlations (associations). Data were examined for combined men and women, men only, and women only. RESULTS: When considering all subjects (n≈48), all three loads, and both accelerometers, correlations were negligible to moderate (0.09 to 0.61). For men (n≈23), the correlations were low to moderate (0.28 to 0.57). For women (n≈25), the correlations were negligible to low (−0.02 to −0.30). CONCLUSION: The redundant accelerometer-based systems measured peak velocity output during low-load jump squats that had little association with DVJ performance for combined men and women as well as when women were considered in isolation. The associations of DVJ performance with peak velocity under the conditions used in this study were only slightly greater for men than for women. PRACTICAL APPLICATIONS: Within the constraints of this study, it appears that peak velocity during low-load jump squats has little association with DVJ performance in women and only a slightly greater association in men. Therefore, it appears that peak velocity during jump squats with relatively light loads explains little of the variability in DVJ performance. ACKNOWLEDGMENT: This study was supported in part by Myotest, Inc.

Recovery-Stress State: RESTQ-Sport Questionnaire Responses versus Training Load and Performance Changes In Division-I Football Players

PURPOSE: Determine if RESTQ-Sport questionnaire responses provide a valid assessment of weekly changes in training volume loads, and reveal significant associations with changes in sport performance testing. METHODS: 24 male, Division-I NCAA collegiate football players (ages 20 ± 1 yrs.) submitted RESTQ-Sport questionnaire responses, which were collected at least once per week (Tuesday or Thursday [n=7] and/or both days [n=17]), for 6 weeks, immediately following a combined resistance training and sport conditioning session. Pearson's Correlations were made between weekly scores for each RESTQ-Sport Scale (19 stress- and/or recovery-oriented scales total), and weekly undulations in training volume loads. Partial Pearson's Correlations were also made between the scale scores and overall (i.e. pre-post) change in sport performance testing parameters, controlling for pre-performance test scores. RESULTS: Weekly scale scores significantly associated with weekly volume load assignments (e.g. Week 2 Training Load v. Week 2: Emotional Stress scale [R =0.362, p=0.049], Fitness/Being in Shape scale [R =0.418, p=0.022], Burnout/Physical Activity scale [R =0.407, p=0.026], Self Efficacy scale [R =0.394, p=0.031]). Weekly scale scores significantly associated with changes in performance testing (e.g. Change in Back Squat 1RM v. Week 1: Fatigue scale [R =0.584, p=0.007], Somatic Complaints scale [R =0.514, p=0.020], General Well-Being scale [R = -0.464, p=0.039]). CONCLUSION: The collegiate football player's weekly subjective assessment of recovery-stress state, quantified via RESTQ-Sport Scale scores, appears to parallel weekly changes in training volume loads, or stress. Furthermore, RESTQ-Sport Scale scores appear to be predictive of overall change in sport performance testing (e.g. tests of speed [40-Yard Dash], agility [Pro-Shuttle], and speed-strength [1RM Power Clean]). This study explored a tool that aims to clarify an athlete's fitness status by assessing the balance between stress tolerance and recovery aptitude. The RESTQ-Sport questionnaire appears to provide athlete-specific scale scores that can be analyzed to provide a valid reflection of changes in training stress, and to predict an overall change in sport performance testing after a period of preparatory sport training.

Stability Reliability, Precision, And Association Of Measures Of Average Rate Of Dynamic Force Development

Average rate of dynamic force development (ARDFD) may be calculated from direct and indirect measures of force obtained using force platforms (FP) and accelerometers (A), respectively. However, its utility during jump squats has not been established. PURPOSE: To determine the stability reliability and precision of ARDFD during jump squats calculated from FP and A data, and to ascertain the association between them. METHODS: Fifty-two subjects (27 women and 25 men) with squat training experience were recruited from a university population. All performed a back squat to 90° of knee flexion with an external load > body weight. Subjects used maximum acceleration in performing duplicate countermovement jump squats (CMJ) and static jump squats (SJ) at 20, 30, and 40% of their back squat 1RM on two separate days in a counterbalanced sequence. ARDFD was operationally defined as (Δ force from initiation of concentric phase to peak / Δ time). Data were obtained using a single uniaxial FP beneath the lifter's feet and a pair of A's affixed to opposite ends of the barbell. A-derived force was determined via inverse dynamics with mass considered the sum of body and barbell weights. Force data from FP and A systems were synchronized for ARDFD calculations. Stability reliability was assessed using intraclass correlation, precision by coefficient of variation, and association via Pearson correlation. RESULTS: With one exception (SJ @ 40% 1RM for one A), stability reliability for the different measurement systems met the minimum standard for all jump squat conditions (r > 0.71, n ≈ 44). However, with only one exception for the A's (SJ @ 30% 1RM, CV = 13.6%) and two for the FP (SJ @ 20 and 30% 1RM, CV = 12.2 and 14.5%, respectively), the minimum standard for precision was not attained (CV > 15.1%, n ≈ 44). Since precision was generally poor, two sessions were averaged for each of the dynamometers prior to assessing association. Correlations were high overall (r > 0.81, n ≈ 40). CONCLUSIONS: The different measurement systems generally produced reliable but imprecise ARDFD data. When two-day output was averaged, the association between the various measurement systems was high at all three loads for both types of jump squat. As operationally defined, ARDFD lacks sufficient precision to be a useful tool for monitoring small changes in performance.

Psychological Correlates of Performance in Female Athletes During a 12-Week Off-Season Strength and Conditioning Program

Examination of the relationship between performance testing and psychological measures before and after a 12-week strength and conditioning program was the study's purpose. Female NCAA Division-III soccer (n = 28), field hockey (n = 28), and softball (n = 19) athletes completed pre- and post-testing held 12 weeks apart. On day 1, athletes completed informed consent, 3 psychological measures (Profile of Mood States [POMS], Physical Self Perception Profile [PSPP], and Athlete's Self Perception of Physical Abilities [ASPPA]), and 2 strength tests (1 repetition maximum [1RM] bench, 1RM back squat). Day 2 consisted of the 30-yd sprint, pro agility run (PRO), vertical jump (VJ), and standing long jump (SLJ). All sports improved (p < 0.01) in 1RM bench and squat and reported increases in perceived Physical Strength on the PSPP (p < 0.01). Soccer athletes improved (p < 0.01) in VJ, SLJ, and PRO (p < 0.05). No differences were found in POMS scores. The POMS scores indicated that the athletes were not overtrained or experiencing staleness. A series of correlations showed relationships between physical and psychological measures. Specifically, Physical Strength was correlated with 1RM upper-body (r = 0.49, p < 0.01) and lower-body (r = 0.42, p < 0.01) strength. The PSPP Physical Strength was correlated with ASPPA ratings of upper-body (r = 0.68, p < 0.01) and lower-body (r = 0.57, p < 0.01) strength. The PSPP Sport Competence correlated with ASPPA ratings of power (r = 0.45, p < 0.01) and PRO (r = 0.38, p < 0.05). The study's results highlight the benefits of strength and conditioning. Furthermore, these results demonstrate how physical changes are related to athletes' physical self-perceptions and self-assessment of ability within their teams.

Effect of Preseason Concurrent Muscular Strength and High-Intensity Interval Training in Professional Soccer Players

This study examined the effect of concurrent muscular strength and high-intensity running interval training on professional soccer players' explosive performances and aerobic endurance. Thirty-nine players participated in the study, where both the experimental group (EG, n = 20) and control group (CG, n = 19) participated in 8 weeks of regular soccer training, with the EG receiving additional muscular strength and high-intensity interval training twice per week throughout. Muscular strength training consisted of 4 sets of 6RM (repetition maximum) of high-pull, jump squat, bench press, back half squat, and chin-up exercises. The high-intensity interval training consisted of 16 intervals each of 15-second sprints at 120% of individual maximal aerobic speed interspersed with 15 seconds of rest. EG significantly increased (p < or = 0.05) 1RM back half squat and bench press but showed no changes in body mass. Within-subject improvement was significantly higher (p < or = 0.01) in the EG compared with the CG for vertical jump height, 10-m and 30-m sprint times, distances covered in the Yo-Yo Intermittent Recovery Test and maximal aerobic speed test, and maximal aerobic speed. High-intensity interval running can be concurrently performed with high load muscular strength training to enhance soccer players' explosive performances and aerobic endurance.

Comparative Force Outputs From Non-Centered Accelerometers During Loaded Barbell Jump Squats

The direct acquisition of ground reaction force data during isoinertial resistance tasks typically requires a force platform. As this is not always practical, alternative devices have been used to estimate dynamic force by directly measuring other variables and then using inverse dynamics to calculate it. For example, linear position and linear velocity transducers have been tethered to bars and used for this purpose. Recently, a dynamometer incorporating an accelerometer and no tether became available for this application. However, since barbell equipment inherently allows for asymmetrical movement through multiple planes, it follows that force output may differ depending upon bar orientation, especially deviations from horizontal. Furthermore, differences related to dynamometer placement and/or variations in the lifting movement pattern could be problematic if training-induced changes are to be monitored. To determine if peak force differed during barbell jump squats using non-centered accelerometer placements. 52 subjects (27 women & 25 men) with squat training experience were recruited from a university population. Subjects performed duplicate loadspectrum countermovement jump squats (CMJ) and static jump squats (SJ) (20%, 30% & 40% of their back squat 1RM) on two separate days in a counterbalanced sequence. A triaxial accelerometer device was directly affixed to each end of the barbell midway between the lateral-most aspect of the shoulder and the thumb side of each hand. Acceleration data were downsampled from 1.5 KHz to 500Hz by averaging every 3 data points. These data were then low-pass filtered (4th order Butterworth) with a cutoff frequency of 10Hz via proprietary software. Force was determined via inverse dynamics with mass considered the sum of body and barbell weights. Peak force data from the two dynamometers were always obtained from the same trial. Paired t-tests were used for data analysis. Dynamometers provided similar peak force values for both CMJ and SJ at 20% and 40% 1RM loads (p > .05) and different values at the 30% 1RM load (p < .01). Mean differences (20, 30, & 40%, respectively) for the CMJ were 9.8N, 15.1N, 8.1N and for the SJ were -1.5N, 15.4N, 5.9N (Table 1). For relatively light countermovement and static jump squats, dynamometer placement on both ends of barbell may result in differential peak force output. It appears that accelerometer placement during jump squats should either be as close as possible to the center of the bar or a squat machine with a horizontally-fixed bar should be used. Although not tested herein, it is likely that linear position and linear velocity transducers would have the identical constraints. As contiguous accelerometer placement was not tried herein, it is unclear what, if any, contribution the dynamometers made to measurement error.

Effect of Potentiating Exercise Volume on Vertical Jump Parameters in Recreationally Trained Men

High-force activities have demonstrated postactivation potentiation (PAP) and may enhance performance in athletes; however, the efficacy of high-force activities to generate PAP in recreationally trained men remains unclear. The purpose of this study was to investigate the effect of high-force back squat volume on vertical jump (VJ) height, ground reaction force (GRF), impulse (IMP), and takeoff velocity (TOV) in recreationally trained men. Sixteen recreationally trained men (age 24.56 +/- 2.10 years, height 174.53 +/- 8.54 cm, mass 84.59 +/- 14.75 kg, and 1 repetition maximum [1RM] back squat 124.71 +/- 17.58 kg) with at least 1 year of back squat experience completed 5 testing sessions separated by a minimum of 72 hours' rest. On session 1, subjects completed VJ testing without a potentiating exercise intervention (control condition) in a test-retest fashion (3 VJs, 5 minutes seated rest, and 3 more VJs) and performed 1RM back squat testing. Subjects completed the subsequent 4 testing sessions in a test-retest fashion (3 VJs, experimental condition, 5 minutes seated rest, and 3 more VJs) in random order. The 4 experimental conditions required subjects to perform the back squat using a load of 85% 1RM with volumes of 1 x 2, 1 x 3, 1 x 4, or 1 x 5. Analysis of variance revealed no significant (p > 0.05) condition by time interactions for any dependent variable; however, there were significant (p < 0.05) main effects for time for GRF (pre 2,123.74 +/- 422.86 N, > post 2,094.53 +/- 390.99 N) and IMP (pre 210.88 +/- 100.97 Nxs, > post 204.63 +/- 106.14 Nxs) but not for VJ or TOV. These results suggest that 85% 1RM back squat volume assignments do not produce a VJ potentiation response in recreationally trained men.

Physiological Profile of Women's Lacrosse Players

Increasing participation rates for women's lacrosse necessitate a clear understanding of fitness parameters for this athlete group. However, limited sport-specific information is available. We described the physiological profile of an NCAA Division I women's lacrosse team to provide current data for this specific athlete group. A descriptive analysis was used to assess physiologic variables. Twenty-four members (age 20.0 +/- 1.4 years, mass 64.7 +/- 9.6 kg, height 163.2 +/- 25.6 cm) of an NCAA Division I women's lacrosse team volunteered and provided consent. Fitness tests were conducted by the same researcher and were selected from standard physical fitness assessments. Tests included cardiovascular endurance (Bruce Protocol VO2max test and 1-mile run), flexibility (sit-and-reach test), muscular endurance (push-ups, sit-ups, and 60% of 1RM back squat), muscular strength (one-repetition maximum [1RM] back squat and 1RM bench press), body composition (BOD POD), muscle torque (quadriceps maximal voluntary isometric contraction), grip strength (hand dynamometer), vertical jump (Vertec vertical column), endurance strength (100- and 200-yard sprints), and Q-angle. Our results indicate that our sample of lacrosse players exhibited similar fitness characteristics to basketball, soccer, and track athletes. However, we found only average flexibility and a higher percentage of body fat, indicating possible areas for improvement in lacrosse training programs.

Acute Effects of Augmented Eccentric Loading on Jump Squat Performance

The purpose of this study was to determine the acute effects of a spectrum of eccentric loads on force, velocity, and power during the concentric portion of maximal-effort jump squats utilizing a repeated measures design. Thirteen resistance-trained men (age = 22.8 +/- 2.9 years, weight = 87.1 +/- 11.8 kg, 163.5 +/- 28.6 kg squat 1 repetition maximum [1RM]; mean +/- SD), who routinely incorporated back squats into their training, participated as subjects in this investigation. Jump squat performance was assessed using 4 experimental conditions. The first of these conditions consisted of an isoinertial load equal to 30% of back squat 1RM. The remaining conditions consisted of jump squats with a concentric load of 30% 1RM, subsequent to the application of experimental augmented eccentric loading (AEL) conditions of 20, 50, and 80% of back squat 1RM, respectively. All subjects performed 2 sets of 1RM of maximum-effort jump squats with all experimental conditions in a counter-balanced sequence. Forty-eight hours after completing the first testing session, subjects repeated the experimental testing protocol to establish stability reliability. Peak performance values for the reliable variables of force, velocity, and power, as well as force and power values obtained at 20-ms intervals during the initial 400 ms of the concentric jump squat range of motion, showed no statistical difference (p > 0.05) across the experimental AEL loads. These results suggest that load-spectrum AEL prior to a 30% 1RM jump squat fails to acutely enhance force, velocity, and power.

STRENGTH FACTORS RELATED TO MAXIMAL POWER OUTPUT DURING JUMP SQUATS WITH AN OPTIMAL LOAD

The relationship between maximum lower body strength, as measured by an estimated 1RM back squat, and power output during jump squats has not yet been quantified. This research is a preliminary attempt to understand how maximum squat strength is associated with peak power output during jump squats with a load that permits optimal power output. PURPOSE: To determine what factors are associated with peak power output during jump squats with an optimal load. METHODS: Fourteen male NCAA Division I collegiate volleyball players (body mass: 87 +/− 12.4kg) completed two testing protocols. The first testing protocol was a 1RM squat testing session. During this session a 7–10 repetition maximum load, on a free weight barbell back squat, was determined. This 7–10 RM was then converted to an estimated 1RM using the Brown equation [1RM = (repetitions × 0.0328 + 0.9849) × weight]. During the second testing session, which occurred 7 days after the first session, sets of two jump squats were used to determine the optimal load for power output. The subjects began performing the jump squats with an unloaded bar and then used progressively heavier weights in subsequent sets until the load that produced the maximum power output was isolated. Vertical ground reaction forces were measured using a force platform (Kistler Quattro Jump, Kistler, Switzerland) mounted under the smith machine in which the subjects performed their jump squats. A linear transducer (Ballistic Measurement System, Innervations, IN, USA) was used to measure bar displacement. This force and velocity data was multiplied together to obtain instantaneous power during the jump squats. A Pearson Correlation test with significance set at 0.05 was used to determine associations among the variables. RESULTS: The mean and standard deviations for the 1RM testing, peak power, and optimal load were 137.7 +/− 25.7 kg, 6795 +/− 1027 W, and 30.2 +/− 3.9 kg respectively. The ratio optimal load/1RM was 22.5 +/− 4.3%. There were no significant correlations found between the estimated 1RM and either peak power or the optimal load at which peak power occurred. There were significant negative correlations between total contact time and 1RM and contact time and peak power during the squat jump. CONCLUSION: These results suggest that there is no direct relationship between 1RM strength measured by the squat and power output in the jump squat. However, 1RM squat strength is inversely related to contact time during the squat jumps.

The Relationship Between Training Status and Intensity on Muscle Activation and Relative Submaximal Lifting Capacity During the Back Squat

The purpose of this study was to compare the relative activation of the vastus lateralis (VL) and vastus medialis (VM) muscles among subjects of different training statuses during the completion of a single set of the back squat performed until failure (SSTF) at an intensity of 85% of the 1 repetition maximum (1RM). Nine trained (TR) and 7 untrained (UT) subjects performed 2 1RM tests followed by an SSTF at 85% of the 1RM on 3 separate days. Activation of VL and VM was recorded using surface electrodes during both the 1RM and SSTF. The data were digitally filtered, rectified, and integrated (IEMG) for the 1RM and each repetition of the SSTF. The SSTF 1EMGs were expressed as a percentage of 1RM IEMG (%1RM IEMG) for the first repetition, as well as 40, 60, 80, and 100% of the repetitions completed in the SSTF. The TR was significantly stronger than UT in 1RM back squat strength. The TR and UT exhibited similar VL activation. The TR had significantly greater activation for VM than UT. The combined activation (COMB) of these 2 muscles revealed significantly greater muscle activation by TR than UT. The TR used a significantly greater %1RM IEMG at 40, 80, and 100% of completed repetitions for VL. The %1RM IEMG for TR was also significantly greater at 80 and 100% of the completed repetitions for VM. The COMB %1RM IEMG for TR was significantly greater than that of UT at 80 and 100% of completed reps. The TR completed significantly more repetitions (9.67 ± 0.91 repetitions) than UT (7.14 ± 0.74 repetitions) in the SSTF. The results indicate that TR can utilize a greater %1RM IEMG. This may contribute to an increase in relative submaximal lifting capacity and invalidate the method of defining training intensity utilizing a percentage of the 1RM for a specific number of repetitions.