INTRODUCTIONThe relationship between the percentage of a fatiguing ambulatory task completed and rating of perceived exertion (RPE) appears to be linear and scalar, with a relatively narrow "window." Recent evidence has suggested that a similar relationship may exist for muscularly demanding tasks.METHODSTo determine whether muscularly demanding tasks fit within this "ambulatory window," we tested resistance-trained athletes performing bench press and leg press with different loadings predicted to allow 5, 10, 20, and 30 repetitions and measured RPE (category ratio scale) at the end of the concentric action for each repetition.RESULTSThere was a regular, and strongly linear, pattern of growth of RPE for both bench press (r = .89) and leg press (r = .90) during the tasks that allowed 5.2 (1.2), 11.6 (1.9), 22.7 (2.0), and 30.8 (3.2) repetitions for bench press and 5.5 (1.5), 11.4 (1.6), 20.2 (3.0), and 32.4 (4.2) repetitions for leg press, respectively.CONCLUSIONSThe path of the RPE growth versus percentage task fit within the window evident for ambulatory tasks. The results suggest that the RPE versus percentage task completed relationship is scalar, relatively linear, and apparently independent of exercise mode.

Background: The purpose of this study was to examine the relationship between training load and next-day recovery in collegiate American football (AF) players during pre-season. Methods: Seventeen athletes (Linemen, n = 6; Non-linemen, n = 11) participated in the 14-day study wearing monitoring (accelerometer + heart rate) sensors during on-field practice sessions throughout pre-season to assess the physiological (PL), mechanical load (ML) and recording of session RPE (sRPE load) immediately post-practice. Prior to practice, participants completed a drop-jump reactive strength index (RSI) test and reported perceived recovery status (PRS). Loaded counter movement vertical jump was assessed before and after pre-season. Results: For every one unit increase in sRPE load, RSI declined by 0.03. Non-linemen had a lower RSI value of 73.1 units compared to linemen. For every one unit increase in ML, the PRS decreased by 0.01. Non-linemen recorded higher average ML during week 2 (ES = 1.17) compared to linemen. Non-linemen recorded higher RSI values in weeks 1 (ES = -1.41) and 2 (ES = -1.72) compared to linemen. All training load and recovery parameters were lower week 2 compared to week 1 (p < 0.05) for all players. Conclusions: Next-day RSI values were influenced by sRPE load while next-day PRS appears to be more influenced by ML. No difference in PL or sRPE load was observed been groups despite non-linemen completing a higher ML throughout the preseason. A combination of training load and recovery metrics may be needed to monitor the fatigue and state of readiness of each player.

The primary purpose of this study was to examine the acute effects of one versus two doses of a multi-ingredient pre-workout supplement on energy expenditure during moderate-intensity treadmill running. In addition, our second aim was to investigate the responses of associated metabolic factors (i.e., substrate utilization, measures of gas exchange), perceived exertion, and resting cardiovascular variables with one and two doses of the pre-workout supplement. Twelve females (mean ± SD: age = 25.3 ± 9.4 years; body mass = 61.2 ± 6.8 kg) completed three bouts of 30 min of treadmill running at 90% of their ventilatory threshold on separate days after consuming one dose of the pre-workout supplement (1-dose), two doses (2-dose), and a placebo. There were no differences among conditions for energy expenditure, fat or carbohydrate oxidation, respiratory exchange ratio, oxygen consumption, or heart rate across exercise time. The two-dose group, however, had lower (p = 0.036) ratings of perceived exertion (11.8 ± 1.7) than the one-dose (12.6 ± 1.7) and the placebo (12.3 ± 1.2) at the 20-min time point of exercise as well as greater resting systolic blood pressure (110 ± 10 mmHg) compared to the one-dose (106 ± 10 mmHg) and the placebo (104 ± 10 mmHg) conditions. Both the one-dose and two-dose conditions had greater increases in diastolic blood pressure compared to the placebo. Thus, our findings indicated that the present pre-workout supplement had no performance-enhancing benefits related to energy metabolism but did attenuate feelings of exertion.

Kildow, AR, Wright, G, Reh, RM, Jaime, S, and Doberstein, S. Can monitoring training load deter performance drop-off during off-season training in Division III American football players? J Strength Cond Res 33(7): 1745-1754, 2019-The primary aim of this observational investigation was to monitor performance of Division III American football players during off-season training while the secondary aim was to investigate differences in training adaptations between linemen and nonline players. Twenty-three subjects from the university's football team were recruited from an Exercise Science 100 conditioning class to participate in a 15-week off-season training program. Phase I consisted of concurrent strength and speed/endurance training (3-4 d·wk) for 7 weeks. Phase II consisted of strength training and spring football practice (3-4 d·wk) for 4 weeks. Countermovement jump, estimated one repetition maximum (1RM) bench press and back squat, 505 change of direction (COD), repeated 30-yard anaerobic sprint test (RAST), and body mass were all measured Pre, Mid, and Post training program. Two-way analysis of variance with repeated measures revealed no significant interaction between linemen and nonline players for all performance variables (p > 0.05). Over the course of the study, RSAT % decrement, 505 COD times, and estimated 1RM performance for bench and squat significantly improved (p ≤ 0.05). No significant changes were detected in CMJ, RSAT best time, or body mass. Results indicate that linemen and non-line players did not respond significantly different to the present training program. The 15-week training program produced improvements in COD skill, speed, anaerobic capacity, and muscular strength. Furthermore, all performance changes were maintained through the end of the study. Data from this study indicate that monitoring training load can give feedback to help augment performance and prevent performance decrements during the off-season.

Abstract Jagim, AR, Dominy, TA, Camic, CL, Wright, G, Doberstein, S, Jones, MT, and Oliver, JM. Acute effects of the elevation training mask on strength performance in recreational weightlifters. J Strength Cond Res 32(2): 482–489, 2018—The Elevation Training Mask 2.0 (ETM) is a novel device that purportedly simulates altitude training. The purpose of this study was to investigate the acute effects of the ETM on resistance exercise performance, metabolic stress markers, and ratings of mental fatigue. Twenty male recreational weight lifters completed 2 training sessions of back squat and bench press (6 sets of 10 repetitions at 85% of 5-repetition maximum and seventh set to failure) as well as a maximal effort sprint test (18% body mass) with the mask (ETM) and without the mask (NM). Training evaluation included baseline and postexercise blood lactate and oxygen saturation measures. Performance evaluation included peak and average velocity bar velocity, total volume load, total work, total repetitions completed, and sprint performance. Adverse side effects were reported in 12% (n = 3) of participants, which included feelings of light headedness, anxiety, and discomfort. No differences were found in repetitions or total workload in back squat (p = 0.07) or bench press (p = 0.08) between conditions. A lower peak velocity was identified during the back squat, bench press, and sprint test in the ETM condition (p = 0.04). Blood lactate values were lower after bench press and sprint during the ETM condition (p < 0.001). Significantly lower ratings of alertness and focus for task were found after squat, bench press, and sprint test in the ETM condition compared with the NM condition (p < 0.001). Wearing the ETM during bouts of resistance training did not hinder the ability to achieve desired training volumes during the resistance training session. However, wearing the ETM does seem to attenuate the ability to maintain working velocity during training bouts and negatively influence ratings of alertness and focus for task.

Background:To what extent pre-season training camp may impact body composition and metabolism in collegiate football players is unknown.Objective:The purpose of this study was to assess changes in body composition, dietary habits and metabolism following pre-season training in Division III American football players.Methods:Seventeen Division III football players (Ht: 1.80±0.6 m; BM: 99.1±60.1 kg; FFM: 79.7±8.6 kg; BF%: 19.3±8.6%) had their body composition and resting energy expenditure (REE) assessed in a fasted state (>12 hr.) before and upon completion of pre-season training. Pre-season training consisted of 14 days of intense training.Results:Linemen had a higher body mass, fat-free mass (FFM), and fat mass likely contributing to the higher REE (p < 0.01). A main effect for time was observed regarding changes in FFM (p<0.001) and body fat % (p = 0.024). A significant interaction was observed for FFM with linemen experiencing a greater reduction in FFM (-1.73±0.37vs.-0.43±0.74 kg; p<0.001). Linemen (L) experienced a greater reduction in REE compared to non-linemen (NL) (L: -223.0±308.4vs.NL: 3.27±200.1 kcals; p=0.085) albeit not statistically significant. Non-linemen consumed a higher amount of daily calories (p=0.036), carbohydrates (p=0.046), and protein (p=0.024) when expressed relative to body mass.Conclusion:The greater size in linemen prior to pre-season likely contributed to their higher REE. However, the multiple training bouts appeared to reduce REE in linemen, which may have been driven by the observed losses in FFM and low protein intake. Further, pre-season training increased body fat % in all players.

The 505 involves a 10-m sprint past a timing gate, followed by a 1808 change-of-direction (COD) performed over 5 m. This methodological report investigated an adapted 505 (A505) designed to be football-specific by changing the distances to 10 and 5 yd. Twenty-five high school football players (6 linemen [LM]; 8 quarterbacks, running backs, and linebackers [QB/RB/LB]; 11 receivers and defensive backs [R/DB]) completed the A505 and 40-yd sprint. The difference between A505 and 0 to 10-yd time determined the COD deficit for each leg. In a follow-up session, 10 subjects completed the A505 again and 10 subjects completed the 505. Reliability was analyzed by t-tests to determine between-session differences, typical error (TE), and coefficient of variation. Test usefulness was examined via TE and smallest worthwhile change (SWC) differences. Pearson's correlations calculated relationships between the A505 and 505, and A505 and COD deficit with the 40-yd sprint. A 1-way analysis of variance (p <= 0.05) derived between-position differences in the A505 and COD deficit. There were no between-session differences for the A505 (p = 0.45-0.76; intraclass correlation coefficient = 0.84-0.95; TE = 2.03-4.13%). Additionally, the A505 was capable of detecting moderate performance changes (SWC0.5 > TE). The A505 correlated with the 505 and 40-yard sprint (r = 0.58-0.92), suggesting the modified version assessed similar qualities. Receivers and defensive backs were faster than LM in the A505 for both legs, and right-leg COD deficit. Quarterbacks, running backs, and linebackers were faster than LM in the right-leg A505. The A505 is reliable, can detect moderate performance changes, and can discriminate between football position groups.

The purpose of this study was to examine the effect that load has on the mechanics of the jump shrug. Fifteen track and field and club/intramural athletes (age 21.7 ± 1.3 y, height 180.9 ± 6.6 cm, body mass 84.7 ± 13.2 kg, 1-repetition-maximum (1RM) hang power clean 109.1 ± 17.2 kg) performed repetitions of the jump shrug at 30%, 45%, 65%, and 80% of their 1RM hang power clean. Jump height, peak landing force, and potential energy of the system at jump-shrug apex were compared between loads using a series of 1-way repeated-measures ANOVAs. Statistical differences in jump height (P < .001), peak landing force (P = .012), and potential energy of the system (P < .001) existed; however, there were no statistically significant pairwise comparisons in peak landing force between loads (P > .05). The greatest magnitudes of jump height, peak landing force, and potential energy of the system at the apex of the jump shrug occurred at 30% 1RM hang power clean and decreased as the external load increased from 45% to 80% 1RM hang power clean. Relationships between peak landing force and potential energy of the system at jump-shrug apex indicate that the landing forces produced during the jump shrug may be due to the landing strategy used by the athletes, especially at lighter loads. Practitioners may prescribe heavier loads during the jump-shrug exercise without viewing landing force as a potential limitation.

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Background Multi-ingredient pre-workout supplements (MIPS) are popular among resistance trained individuals. Previous research has indicated that acute MIPS ingestion may increase muscular endurance when using a hypertrophy-based protocol but less is known in regard to their effects on strength performance and high intensity running capacity. Therefore, the purpose was to determine if short-term, MIPS ingestion influences strength performance and anaerobic running capacity.Methods In a double-blind, randomized, placebo controlled, crossover design; 12 males (19 ± 1 yrs.; 180 ± 12 cm; 89.3 ± 11 kg; 13.6 ± 4.9 %BF) had their body composition assessed followed by 5-repetition maximum (5RM) determination of back squat (BS; 119.3 ± 17.7 kg) and bench press (BP; 92.1 ± 17.8 kg) exercises. On two separate occasions subjects ingested a MIPS or a placebo (P) 30-minutes prior to performing a counter movement vertical jump test, 5 sets of 5 repetitions at 85 % of 5RM of BS and BP, followed by a single set to failure, and an anaerobic capacity sprint test to assess peak and mean power. Subjective markers of energy levels and fatigue were also assessed. Subjects returned one week later for a second testing session using counter treatment.Results MIPS resulted in a greater number of repetitions performed in the final set to failure in the BP (MIPS, 9.8 ± 1.7 repetitions; P, 9.1 ± 2; p = 0.03, d = 0.38), which led to a greater total volume load (set x repetitions x load) in the MIPS (753 ± 211 kg) compared to P (710 ± 226 kg; p =0.03, d = .20). MIPS ingestion improved subjective markers of fatigue (p = 0.01, d = 3.78) and alertness (p = 0.048, d = 2.72) following a bout of resistance training. An increase in mean power was observed in the MIPS condition (p = 0.03, d = 0.25) during the anaerobic sprint test.Conclusion Results suggest that acute ingestion of a MIPS study may increase upper body muscular endurance. In addition, acute MIPS ingestion improved mean power output during an anaerobic capacity sprint test. However, the practical significance of these performance related outcomes may be minimal due to the small effect sizes observed. MIPS ingestion does appear to positively influence subjective markers of fatigue and alertness during high-intensity exercise.

The purpose of the present study was to examine the effects of an acute dose of an arginine-based supplement on the physical working capacity at the fatigue threshold (PWCFT), lactate threshold (LT), ventilatory threshold (VT), and peak oxygen uptake during incremental cycle ergometry. This study used a double-blinded, placebo-controlled, within-subjects crossover design. Nineteen untrained men (mean age ± SD = 22.0 ± 1.7 years) were randomly assigned to ingest either the supplement (3.0 g of arginine, 300 mg of grape seed extract, and 300 mg of polyethylene glycol) or placebo (microcrystalline cellulose) and performed an incremental test on a cycle ergometer for determination of PWCFT, LT, VT, and peak oxygen uptake. Following a 1-week period, the subjects returned to the laboratory and ingested the opposite substance (either supplement or placebo) prior to completing another incremental test to be reassessed for PWCFT, LT, VT, and peak oxygen uptake. The paired-samples t tests indicated there were significant (P < 0.05) mean differences between the arginine and placebo conditions for the PWCFT (192 ± 42 vs. 168 ± 53 W, respectively) and VT (2546 ± 313 vs. 2452 ± 342 mL·min(-1)), but not the LT (135 ± 26 vs. 138 ± 22 W), absolute peak oxygen uptake (3663 ± 445 vs. 3645 ± 438 mL·min(-1)), or relative peak oxygen uptake (46.5 ± 6.0 vs. 46.2 ± 5.0 mL·kg(-1)·min(-1)). These findings suggested that the arginine-based supplement may be used on an acute basis for delaying the onset of neuromuscular fatigue (i.e., PWCFT) and improving the VT in untrained individuals.

McLain, TA, Wright, GA, Camic, CL, Kovacs, AJ, Hegge, JM, and Brice, GA. Development of an anaerobic sprint running test using a nonmotorized treadmill. J Strength Cond Res 29(8): 2197-2204, 2015The purpose of this study was to determine the test-retest reliability of a newly developed anaerobic sprint running test (ASRT) on a nonmotorized treadmill (NMT). Twenty-six collegiate male athletes (21.2 +/- 2.1 years; 181.3 +/- 6.5 cm; 79.0 +/- 9.3 kg) completed 3 trials of a 25-second maximal effort sprint on an NMT against a workload set to 18% of their individual body mass. Anaerobic power was determined by relative peak power output (PP) and anaerobic capacity was determined by relative mean power output (MP) during the test. Blood lactate (BLa) responses and fatigue index (FI) were also determined. Test-retest reliability was assessed by intraclass correlation coefficients (ICCs) and coefficients of variation (CV%). Results indicated no significant difference between the 3 trials for PP (T-1 = 29.95 +/- 6.51 Wkg(-1), T-2 = 28.57 +/- 5.55 Wkg(-1), T-3 = 29.47 +/- 5.94 Wkg(-1)), MP (T-1 = 20.97 +/- 3.64 Wkg(-1), T-2 = 20.50 +/- 3.46 Wkg(-1), T-3 = 21.17 +/- 3.79 Wkg(-1)), and FI (T-1 = 55 +/- 8%, T-2 = 51 +/- 8%, T-3 = 52 +/- 9%). Reliability between the 3 trials for PP (ICC: r = 0.96, CV: 7%) and MP (ICC: r = 0.97, CV: 6%) was considered high. Reliability for FI exhibited an ICC of r = 0.83 (CV: 6%). Postsprint BLa values were not significantly different (p = 0.49) between the 3 trials. Test-retest reliability for postsprint BLa was found to be good (r = 0.68, CV = 8.8%). The results of the study indicate that the ASRT is reliable for assessing PP and MP in highly motivated subjects. In addition, anaerobic testing using the ASRT may be a more sport-specific test to assess anaerobic performance for many coaches and athletes.

The purpose of this study was to investigate the effect of various loads on the force-time characteristics associated with peak power during the hang high pull (HHP). Fourteen athletic men (age: 21.6 +/- 1.3 years; height: 179.3 +/- 5.6 cm; body mass: 81.5 +/- 8.7 kg; 1 repetition maximum [1RM] hang power clean [HPC]: 104.9 +/- 15.1 kg) performed sets of the HHP at 30, 45, 65, and 80% of their 1RM HPC. Peak force, peak velocity, peak power, force at peak power, and velocity at peak power were compared between loads. Statistical differences in peak force (p = 0.001), peak velocity (p < 0.001), peak power (p = 0.015), force at peak power (p < 0.001), and velocity at peak power (p < 0.001) existed, with the greatest values for each variable occurring at 80, 30, 45, 80, and 30% 1RM HPC, respectively. Effect sizes between loads indicated that larger differences in velocity at peak power existed as compared with those displayed by force at peak power. It seems that differences in velocity may contribute to a greater extent to differences in peak power production as compared with force during the HHP. Further investigation of both force and velocity at peak power during weightlifting variations is necessary to provide insight on the contributing factors of power production. Specific load ranges should be prescribed to optimally train the variables associated with power development during the HHP.

The cost of running (CR), an important determinant of running performance, is usually measured during constant speed running. However, constant speed does not reflect the nature of competitive races in which stochastic variations in pace often occur. PURPOSE: This study was designed to evaluate whether variations in running speed influence CR in trained runners. METHODS: Twenty well-trained runners (12 m, VO2max=73±7 ml/kg; 8f, VO2mx=57±6 ml/kg) completed an incremental test to determine VO2max & ventilatory threshold (VT). Subsequently, they ran four 6-min bouts at an average speed ∼90% VT. Each interval was run with minute to minute pace variation around the subject’s average speed. The CR was measured over the last 2-min. The coefficient of variation (CV) of running speed was calculated to quantify pace variations; ± 0.0 m·s-1 (CV=0%), ± 0.04 m·s-1 (CV=1.4%), ± 0.13 m·s-1(CV=4.2%), and ± 0.22 m·s-1(CV=7%). RESULTS: No differences in CR, HR, RPE, or blood lactate (BLa) were found amongst the variations in running pace. CONCLUSION: Contrary to our hypothesis, pace variation, within the limits often seen in competitive races did not affect CR when measured at a running speed below VT.

Previous studies using altitude as an experimental factor have suggested that the pacing template (the pattern in which power output is regulated at the start of an event before afferent receptors provide feedback) is very robust, causing athletes to start time trials (TT) at the same power output (PO) even when FiO2 is reduced. PURPOSE: This study was designed to evaluate whether glycogen depletion (GD) as an experimental factor would also influence the pacing strategy in a 4km cycle TT. METHODS: Well-trained, task-habituated, sub-elite cyclists/triathletes (6 m/4f; VO2max=61±7/49±6 ml/kg) completed two 4km TTs. Following the 1st TT, they completed 10x 1km intervals at POmax (HR∼180, BLa∼11, RPE∼9) to induce GD, then ate a low CHO diet for 24 hr. Responses during warm-up (Control vs GD) indicated increased HR (154±11 vs 160±6) & RPE (4.7±0.9 vs 6.2±1.1) and reduced BLa (4.0±1.4 vs 3.3±0.9 mmol*l-1), consistent with GD. RESULTS: Time to complete the TT increased significantly with GD (397±27 vs 404±44 s) with increases in RPE at 50% distance (7.0±0.9 vs 7.8±0.) and decreases in BLa at 50 & 100% distance (9.8±1.6 vs 7.7±2.0 & 13.6±1,8 vs 10.6±2.4 mmol*l-1), consistent with GD. PO was not different in the opening and closing 10% segments, but was significantly lower in the middle 80% of the GD ride. CONCLUSION: Results suggest that, as with altitude as an experimental factor, GD also interferes with performance, but does not change the pacing template (e.g. pattern of PO early in the TT). These data provide additional evidence for the robust nature of the pacing template.

The purpose of this study was to develop and analyze a sport-specific conditioning test for wrestling that will incorporate the physiological demands of a match. Sixteen D-III collegiate wrestlers performed 2 tests to assess physical conditioning. The developed test (sandbag test) used a bag filled with sand that was repeatedly thrown over a course of seven 1-minute rounds. Average time per throw (T/T) was determined each round. The sandbag test was compared with a previously established repeated sprint protocol of maximal effort arm cranking on an upper body ergometer (UBE). Mean power output was determined for each sprint. Both the UBE test and the sandbag test were compared using performance decrement (%fatigue), blood lactate (BLa), and peak heart rate (HRpeak) values. Test-retest reliability for the sandbag test was found to be almost perfect using T/T (intraclass correlation coefficient, r = 0.96). No significant differences in %fatigue were found between the UBE test and the sandbag test (p = 0.600), BLa (p = 0.283), and HRpeak (p = 0.214). Further analysis by weight class (light-weight class [LWC] and heavy-weight class [HWC]) found a significant interaction for %fatigue between groups for the sandbag test and UBE (p = 0.001), but no interactions were observed for BLa (p = 0.198) or HRpeak (p = 0.990). Although no significant differences were found in %fatigue between the 2 tests when the data were grouped together, a clear difference was found between the LWC and HWC groups only in the sandbag test, indicating that this test may be more sensitive than the UBE. Coaches can assess their wrestlers with this reliable, inexpensive, and time-efficient sandbag test.

Respiratory gas exchange threshold measurements are a reference standard for measuring sustainable exercise capacity (McLellan and Skinner, 1981). A recent consensus report suggested that ‘threshold based’ exercise prescription may be superior (Mezzani et al., 2012) to the relative percent of VO2 reserve or heart rate (HR) reserve that has been the standard for exercise prescription for a generation (ACSM, 2014). Further, respiratory gas exchange has technical requirements that place it out of the range of the health-fitness community. An alternative approach, which takes advantage of the fact that air moving into and out of the respiratory system creates sound (detectable as breathing frequency and sound volume) might provide an viable approach to threshold determination (Foster et al., 2012). This approach suggests that ventilatory threshold (VT) can be identified by an increase in breathing frequency and that respiratory compensation threshold (RCT) can be identified by a large increase in the perceived sound intensity. Breath sounds from digital recording are at least potentially capable of being analyzed in a way that allows investigators to distinguish changes in the acoustic character of breathing. The purpose of this study was to determine whether acoustic analysis of breath sounds, based on a proprietary algorithm and similar to that used previously (Foster et al., 2012), was systematically related to VT and RCT. The subjects were healthy young adults aged 1855 (males n = 9, females n = 11). The university human subjects committee approved protocol and the subjects provided written informed consent prior to participation. The subjects performed two incremental cycle ergometer exercise tests until maximal exertion, with at least 24 hr between tests. Power Output began at 25W and was incremented 25 W every two minutes. HR and the Rating of Perceived Exertion (RPE) were recorded during the last thirty seconds of each stage using radiotelemetry and RPE was measured using the Category Ratio scale. Breath sound recordings were captured using a small microphone inserted into a Hans Rudolph breathing valve through the saliva port. Acoustic analysis from the last 30s of each exercise stage was analyzed from digital recordings for breathing frequency and a variable referred to as ‘intensity’ (obtained from the expiratory phase of the acoustic signature); which is conceptually similar to tidal volume divided by the expiratory time. Blinded to information from respiratory gas analysis, the acoustic signature was analyzed based on the first derivative of change in breathing frequency and sound intensity. Candidates for the VT and RCT were identified and compared to the VT and RCT defined from respiratory gas analysis using standard methods (Foster and Cotter, 2005). Comparisons between VT and RCT determined by gas exchange and acoustic analysis were made using repeated measures ANOVA, reproducibility was determined using paired t-tests and intraclass correlations (ICC). There were small, but significant, differences in the gas exchange vs acoustic analysis for power output (PO) at VT (105 ± 37 vs 111 ± 30W, r = 0.66) and RCT (174 ± 40 vs 162 ± 34W, r = 0.79) and HR at VT (114 ± 14 vs 119 ± 11 bpm, r = 0.74) and RCT (148 ± 16 vs 142 ± 14 bpm, r = 0.84) (Figure 1). There was a tendency for the acoustic analysis to slightly overestimate PO at VT, and slightly underestimate PO at RCT. The small magnitude of the differences in mean values for gas exchange vs acoustic analysis and strong correlations between respiratory gas exchange and acoustic anlaysis support the concept that acoustic analysis might prove to be a viable surrogate for respiratory gas analysis.

This study examined the impact of load on lower body performance variables during the hang power clean. Fourteen men performed the hang power clean at loads of 30%, 45%, 65%, and 80% 1RM. Peak force, velocity, power, force at peak power, velocity at peak power, and rate of force development were compared at each load. The greatest peak force occurred at 80% 1RM. Peak force at 30% 1RM was statistically lower than peak force at 45% (p = 0.022), 65% (p = 0.010), and 80% 1RM (p = 0.018). Force at peak power at 65% and 80% 1RM was statistically greater than force at peak power at 30% (p < 0.01) and 45% 1RM (p < 0.01). The greatest rate of force development occurred at 30% 1RM, but was not statistically different from the rate of force development at 45%, 65%, and 80% 1RM. The rate of force development at 65% 1RM was statistically greater than the rate of force development at 80% 1RM (p = 0.035). No other statistical differences existed in any variable existed. Changes in load affected the peak force, force at peak power, and rate of force development, but not the peak velocity, power, or velocity at peak power.

The aim of this study was to compare the kinematic profile between the hang power clean (HPC) and jump shrug (JS). Eighteen college students performed repetitions of the HPC and JS at 40, 60, and 80% of their 1RM HPC. Two trials at each load for each exercise were completed and the peak joint velocity of the hip, knee, and ankle joints were compared using a series of 2 x 3 repeated measures ANOVA. The peak joint velocity of the hip, knee, and ankle during the JS was statistically greater than the HPC at all loads. Statistically significant differences in hip joint velocity existed between repetitions at 40 and 80% 1RM HPC as well as between 60 and 80% 1RM HPC. Joint velocity during the JS was superior to the HPC at all loads examined. Differences in technique between exercises and loads may alter lower extremity joint velocity.