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Gonzalez, AM, Accetta, MR, Spitz, RW, Mangine, GT, Ghigiarelli, JJ, and Sell, KM. Red spinach extract supplementation improves cycle time trial performance in recreationally active men and women. J Strength Cond Res XX(X): 000–000, 2019—To examine the effects of short-term red spinach extrac

Boone, JB, VanDusseldorp, TA, Feito, Y, and Mangine, GT. Relationships between sprinting, broad jump, and vertical jump kinetics are limited in elite, collegiate football athletes. J Strength Cond Res 35(5): 1306-1316, 2021-To evaluate the relationships and agreement in kinetics measured during a 10-yd sprint, a standing broad jump (SBJ), and a vertical jump (VJ), 73 collegiate football players (22.3 ± 0.8 years, 188 ± 7 cm, 113 ± 23 kg) volunteered for this cross-sectional study over a 3-year period. At the beginning of each athlete's off-season training phase and after a standard warm-up, each athlete completed 2-3 maximal trials of each test while tethered to a robotic, cable-resistance device (10-yd sprint and SBJ) or a linear position transducer (VJ alone). Force (N), velocity (m·s-1), and power (W) were measured during the first 2 steps, acceleration phase (units·step-1), and entire 10-yd sprint, and the entire SBJ and VJ. Spearman and partial correlations (controlling for stature) revealed small-to-moderate relationships (r = -0.30 to -0.34) between the second sprinting step and VJ force. Small negative relationships were also noted between sprinting and VJ force and power, but not when controlling for height. Agreement was determined by examining relationships between the differences in and averaged kinetics measured on each test. Trivial-to-small relationships (r < 0.29) were observed between sprinting (first step and 10-yd) and VJ velocity, and between VJ and SBJ velocity, although coefficient of variation (CV) ranged between 64 and 104%. All other relationships ranged from moderate-to-practically perfect with CVs exceeding 500%. Although some relationships exist between sprinting and jumping kinetics, their agreement is variable. These data suggest that coaches and athletes should not use one of these assessments in place of, or to predict performance in, the other assessments.

Purpose To examine the relationships between past competition performances and 2020 CrossFit® Open (CFO) performance. Methods A random selection from the top one thousand athletes (n = 220, 28.5 ± 4.4 years, 178 ± 7 cm, 87.5 ± 10.2 kg) were selected for this study. Overall and weekly performances (including ranks and scores) of the 2020 CFO, as well as overall ranks from all previous CFO, regional, and Games™ competitions in which they competed, were recorded from their publicly available online profile. The highest, lowest, average, and standard deviation (SD) of past rankings, as well as participation statistics (i.e., years since first appearance, total and consecutive appearances, and participation rate), were calculated for each competition stage. Relationships were then assessed between 2020 CFO performance and all past competition experience variables by calculating Kendall’s tau (τ) correlation coefficients and Bayes factors (BF10). Results Overall and weekly ranking of the 2020 CFO was extremely favored (p 10 > 100) to be related to the athlete’s highest previous CFO rank (τ = 0.26–0.39) and individual regional appearances (τ = − 0.26 to − 0.34), as well as individual Games™ appearances (overall and for weeks 1, 3, and 4; τ = − 0.20 to − 0.22, p 10 > 100). Evidence for all other significant relationships ranged from moderate to very strong (p 10 = 3–100) and varied among specific 2020 CFO workouts. Few associations were noted for team competition experience, and these were generally limited to Games™ appearances (τ = − 0.12 to − 0.18, p 10 = 3.3–100). Conclusions Although specific relationships were found between 2020 CFO performance and individual appearances at regional and Games™ competitions, the most consistent relationships were seen with participation and ranking in past CFO competitions.

To examine relationships between Brazilian Jiu Jitsu (BJJ) descriptors (belt rank, experience, gi preference, and fighting style), resistance training (RT) experience, and measures of body composition, strength (maximal handgrip, 3-5-repetition maximum [RM] in barbell glute bridge [GB], prone bench row [PBR], and bench press [BP]), and velocity (GB, PBR, and BP at 7 kg and 30–60% 1-RM), 13 experienced (4.3 ± 3.4 years) BJJ athletes were recruited for this cross-sectional, pilot study. Significant (p < 0.05) Kendall’s tau and Bayesian relationships were seen between belt rank and body fat percentage (τ = −0.53, BF10 = 6.5), BJJ experience and body fat percentage (τ = −0.44 to −0.66, BF10 = 2.6–30.8) and GB velocity (τ = −0.45 to −0.46, BF10 = 2.8–3.1), RT experience and strength (τ = 0.44 to 0.73, BF10 = 2.6–75.1) and velocity (τ = −0.44 to 0.47, BF10 = 2.6–3.3), gi preference-training and relative PBR strength (τ = 0.70, BF10 = 51.9), gi preference-competition and height and lean mass (τ = −0.57 to 0.67, BF10 = 5.3–12.4) and BP velocity (τ = −0.52 to 0.67, BF10 = 3.5–14.0). The relevance of body composition and performance measures to sport-specific training and research interpretation are differentially affected by a BJJ athlete’s experience (BJJ, belt rank, RT), gi preferences, and fighting style.

Mangine, GT, Serafini, PR, Stratton, MT, Olmos, AA, VanDusseldorp, TA, and Feito, Y. Effect of the repetitions-in-reserve resistance training strategy on bench press performance, perceived effort, and recovery in trained men. J Strength Cond Res 36(1): 1-9, 2022-This study examined the effects of the repetitions-in-reserve (RIR) strategy on resistance exercise performance, perceived effort, and recovery. Fourteen resistance-trained men (24.6 ± 3.0 years, 176 ± 5 cm, 85.7 ± 14.0 kg) completed 2 bench press protocols in a randomized crossover fashion. The protocols consisted of 4 sets at 80% of 1 repetition maximum (1RM) to a self-reported 3-RIR and a fifth set to failure or all 5 sets to failure (0-RIR). Barbell kinetics (velocity, rate of force development, and impulse), repetition volume, total work, and ratings of perceived exertion (RPE) were quantified on each set. Barbell kinetics were reassessed during one set of 3 repetitions at 80% 1RM completed at 24-hour, 48-hour, and 72-hour postexercise. Blood samples were collected before and after exercise at 6 hours, 24 hours, 48 hours, and 72 hours and analyzed for concentrations of creatine kinase (CK). Separate, 2-way repeated-measures analysis of variance revealed significant interactions (p0.001) where 3-RIR better maintained repetitions and work at greater average velocity (+0.6 m·s-1) and lower RPE (0-RIR = 10; 3-RIR = 8.2) across all sets. No differences were seen between conditions for CK at 6 hours postexercise (3-RIR: 32.2 ± 55.3%; 0-RIR: 40.8 ± 66.0%) or for CK and barbell kinetics at 24 hours to 72 hours postexercise. Although no differences were seen for recovery, the RIR strategy enabled work to be better sustained across sets at a lower perceived effort and higher average velocity. This strategy could be used to manage fatigue and better sustain effort and volume during a resistance training session.

Mangine, GT, Eggerth, A, Gough, J, Stratton, MT, Feito, Y, and VanDusseldorp, TA. Endocrine and body composition changes across a competitive season in collegiate speed-power track and field athletes. J Strength Cond Res 35(8): 2067-2074, 2021-Maintaining lean mass is important for track and field (TF) athletes who compete in speed-power events, but little is known about how lean mass and related hormones might change over an 8- to 10-month collegiate season. Therefore, to monitor changes in free testosterone (T), cortisol (C), and body composition in TF athletes across their entire competitive season, 9 female (20.3 ± 1.2 years, 169 ± 5 cm, and 67.6 ± 8.5 kg) and 7 male (21.1 ± 2.0 years, 181 ± 9 cm, and 77.3 ± 5.9 kg) Division I TF athletes provided resting and fasted blood samples at the onset of their indoor season (baseline), before and on returning from the indoor conference championships (ICCs), at the beginning and end of a heavy midseason training week (HVY), and before leaving for the National Collegiate Athletic Association (NCAA) Championships. Body composition was also assessed at each of these periods using a 4-compartment model. Except for a 20% reduction (p = 0.030) from ICCs to the onset of HVY in men only, linear mixed models with repeated measures did not reveal any changes in hormone concentrations. Compared with baseline, an overall increase in fat-free mass was observed at HVY (∼2.74%, p = 0.023) before it reduced by 3.81% before the NCAA Championships (p = 0.022). Despite variations in training and competition, resting concentrations of hormones indicative of anabolic status remained relatively consistent over the course of an entire season in speed-power TF athletes. Coaches and athletes may consider monitoring these variables to assess the athlete's response to the changing demands of a competitive season.

Toohey, JC, Townsend, JR, Johnson, SB, Toy, AM, Vantrease, WC, Bender, D, Crimi, CC, Stowers, KL, Ruiz, MD, VanDusseldorp, TA, Feito, Y, and Mangine, GT. Effects of probiotic (Bacillus subtilis) supplementation during offseason resistance training in female Division I athletes. J Strength Cond Res 34(11): 3173-3181, 2020-We examined the effects of probiotic (Bacillus subtilis) supplementation during offseason training in collegiate athletes. Twenty-three Division I female athletes (19.6 ± 1.0 years, 67.5 ± 7.4 kg, and 170.6 ± 6.8 cm) participated in this study and were randomized into either a probiotic (n = 11; DE111) or placebo (n = 12; PL) group while counterbalancing groups for sport. Athletes completed a 10-week resistance training program during the offseason, which consisted of 3-4 workouts per week of upper- and lower-body exercises and sport-specific training. Athletes consumed DE111 (DE111; 5 billion CFU/day) or PL supplement daily for the entire 10-week program. Before and after training, all athletes underwent 1 repetition maximum (1RM) strength testing (squat, deadlift, and bench press), performance testing (vertical jump and pro-agility), and isometric midthigh pull testing. Body composition (body fat [BF]%) was completed using BODPOD and bioelectrical impedance analysis, as well as muscle thickness (MT) measurement of the rectus femoris (RF) and vastus lateralis using ultrasonography. Separate repeated-measures analyses of variance were used to analyze all data. Significant (p ≤ 0.05) main effects for time were observed for improved squat 1RM, deadlift 1RM, bench press 1RM, vertical jump, RF MT, and BF%. Of these, a significant group × time interaction was noted for BF% (p = 0.015), where greater reductions were observed in DE111 (-2.05 ± 1.38%) compared with PL (-0.2 ± 1.6%). No other group differences were observed. These data suggest that probiotic consumption in conjunction with post-workout nutrition had no effect on physical performance but may improve body composition in female Division I soccer and volleyball players after offseason training.

The 2018 CrossFit Open (CFO) was the initial stage of an annual competition that consisted of five weekly workouts. Current evidence suggests that a variety of fitness parameters are important for progressing beyond this stage, but little is known about which are the most important. To examine relationships between CFO performance, experience, and physiological fitness, sixteen experienced (&gt, 2 years) athletes (30.7 &plusmn, 6.9 years, 171 &plusmn, 12 cm, 78.0 &plusmn, 16.2 kg) volunteered to provide information about their training and competitive history, and then complete a battery of physiological assessments prior to competing in the 2018 CFO. Athletes&rsquo, resting energy expenditure, hormone concentrations, body composition, muscle morphology, cardiorespiratory fitness, and isometric strength were assessed on two separate occasions. Spearman correlations demonstrated significant (p &lt, 0.05) relationships between most variables and performance on each workout. Stepwise regression revealed competition experience (R2 = 0.31&ndash, 0.63), body composition (R2 = 0.55&ndash, 0.80), vastus lateralis cross-sectional area (R2 = 0.29&ndash, 0.89), respiratory compensation threshold (R2 = 0.54&ndash, 0.75), and rate of force development (R2 = 0.30&ndash, 0.76) to be the most common predictors. Of these, body composition was the most important. These fitness parameters are known targets with established training recommendations. Though preliminary, athletes may use these data to effectively train for CFO competition.

Gonzalez, AM, Pinzone, AG, Bram, J, Salisbury, JL, Lee, S, and Mangine, GT. Effect of multi-ingredient preworkout supplementation on repeated sprint performance in recreationally active men and women. J Strength Cond Res 34(4): 918-923, 2020-The purpose of this investigation was to examine the effects of acute supplementation of a multi-ingredient preworkout supplement (MIPS), containing a proprietary blend of ancient peat and apple extracts, creatine monohydrate, taurine, ribose, and magnesium, on sprint cycling performance. Seventeen recreationally active men and women (23.2 ± 5.9 years; 172.9 ± 14.3 cm; 82.4 ± 14.5 kg) underwent 2 testing sessions administered in a randomized, counterbalanced, double-blind fashion. Subjects were provided either MIPS or placebo (PL) one hour before performing a sprint cycling protocol, which consisted of ten 5-second "all-out" sprints interspersed by 55 seconds of unloaded pedaling. Average power (PAVG), peak power (PPK), average velocity (VAVG), and distance covered were recorded for each sprint. Separate linear mixed models revealed decrements (p < 0.05) compared to the first sprint in PAVG (75-229 W) and PPK (79-209 W) throughout all consecutive sprints after the initial sprint during PL. Likewise, diminished (p ≤ 0.029) VAVG (3.37-6.36 m·s) and distance covered (7.77-9.00 m) were noted after the third and fifth sprints, respectively, during PL. By contrast, during MIPS, only VAVG decreased (2.34-5.87 m·s, p ≤ 0.002) on consecutive sprints after the first sprint, whereas PAVG and PPK were maintained. In addition, a significant decrease (p = 0.045) in distance covered was only observed on the ninth sprint during MIPS. These data suggest that recreational athletes who consumed the MIPS formulation, one hour before a repeated sprinting session on a cycle ergometer, better maintained performance compared with PL.

This double-blind study examined effects of a protease enzyme blend (Prohydrolase&reg, ) added to whey protein on post-resistance exercise aminoacidemia and intramuscular anabolic signaling were investigated in ten resistance-trained males. Participants completed 4 sets of 8&ndash, 10 repetitions in the leg press and leg extension exercises at 75% of 1-repetition maximum. Participants then consumed either 250 mg of Prohydrolase&reg, + 26 g of whey protein (PW), 26 g whey alone (W), or non-nutritive control (CON) in counterbalanced order. Blood samples were obtained prior to exercise (baseline) and then immediately-post (IP), 30-, 60-, 90-, 120-, and 180-min post-exercise. Muscle biopsies were taken at baseline, 1-h (1H), and 3-h (3H) post-exercise. Phosphorylation of AKTSer437 was decreased (3H only: p &lt, 0.001), mTORSer2448 was increased (1H: p = 0.025, 3H: p = 0.009), and p70S6KThr412 remained unchanged similarly for each condition. Plasma leucine, branch-chained amino acids, and essential amino acid concentrations for PW were significantly higher than CON (p &lt, 0.05) at 30 min and similar to W. Compared to IP, PW was the only treatment with elevated plasma leucine levels at 30 min (p = 0.007, ∆ = 57.8 mmol/L, 95% Confidence Interval (CI): 20.0, 95.6) and EAA levels at 180 min (p = 0.003, ∆ = 179.1 mmol/L, 95% CI: 77.5, 280.7). Area under the curve amino acid analysis revealed no differences between PW and W. While no different than W, these data indicate that PW was the only group to produce elevated amino acid concentrations 30-min and 180-min post-ingestion.

Ultrasonography of the lower body typically encompasses supine rest due to fluid shifts affecting tissue size and composition. However, vastus lateralis (VL) examination is completed in the lateral recumbent position, and this positional change may influence morphology and its ability to predict function. This study aimed to examine the effect of position on VL morphology and its relationship with lower-body performance. Cross-sectional area (CSA), muscle thickness (MT), pennation angle (PA), echo intensity (UnCorEI), subcutaneous adipose tissue thickness (SFT), and echo intensity corrected for SFT (CorEI) were assessed in 31 resistance-trained males (23.0 ± 2.1 yrs; 1.79 ± 0.08 m; 87.4 ± 11.7 kg) immediately after transitioning from standing to supine (IP), after 15 min of standing (ST), and after 15 min of rest in three recumbent positions: supine (SUP), dominant lateral recumbent (DLR), non-dominant lateral recumbent (NDLR). Participants also completed unilateral vertical jumps, isometric/isokinetic tests, and a one-repetition maximum leg press. CSA, MT, PA, and SFT were greater in ST compared to NDLR, DLR, and SUP (p < 0.05). CSA, UnCorEI, and CorEI were different between recumbent positions; however no differences were observed for MT, PA, and SFT. Different magnitudes of relationships were observed between muscle morphological characteristics measured after rest in different positions and performance variables. Muscle morphology in IP generally appears to be the best predictor of performance for most variables, although utilizing the NDLR and DLR positions may provide comparable results, whereas morphology measured in ST and SUP provide weaker relationships with physical performance. IP also requires less time and fewer requirements on the technician and subject, thus researchers should consider this positioning for VL examination.

To evaluate the feasibility of on-site collection of subjective anxiety, autonomic nervous system activity, and salivary catecholamines surrounding high-intensity functional training (HIFT) competition, ten experienced HIFT competitors completed baseline assessments of anxiety and heart rate variability (HRV). Then, in two consecutive weeks (Workout 1 and 2) within the competition, HRV was recorded and examined in 5-min segments prior to exercise (PRE) and across a 30-min period after competitors completed their choice of the prescribed or scaled each workout. Subjective anxiety ratings and saliva samples were collected at PRE and immediately-(IP), 30-min (30P), and 60-min post-exercise (60P). Saliva samples were analyzed for concentrations of epinephrine and norepinephrine. Generalized linear mixed models with repeated measures revealed significant (p &lt, 0.05) differences between workouts for all measures. Compared to Workout 1, anxiety (~50%), epinephrine (173&ndash, 340%), norepinephrine (29&ndash, 234%) were greater in Workout 2 and various HRV-derived indices were more depressed. Additionally, some HRV-derived indices appeared to be modulated (p &lt, 0.05) by competitive level and sex at PRE and throughout the 30-min recovery period. These data suggest that autonomic activity may differ between the competitive and laboratory settings, and that the response may be further modulated by the workout&rsquo, s design, the athlete&rsquo, s sex, and competitive level.

Background Wearable devices are common in the health and fitness industry and provide valuable information to improve and achieve fitness goals. The Hexoskin shirt (Hx) is one such device that has been shown to be valid and reliable. The purpose of this pilot study was to compare the Hx to established methods during a maximal graded exercise test (TM) and a high-intensity functional training (HIFT) session. Methods Ten healthy individuals (31.0±7.6 years, 76.4±11.4 kg; 1.7±0.1 m) volunteered for this study and completed a TM and a HIFT exercise session. During both testing sessions, respiratory measures (respiratory rate [RR], and respiratory volume [RV]) were assessed using a portable metabolic system (Cosmed K4b2; K4), and heart rate (HR) was determined via ECG in a standard 12-lead configuration. The Hx was worn during both sessions. Results During TM, a 4% difference was noted for HR during cool down, while exercising HR and RV, along with RR during cool down were all under 10%. During HIFT, HR at rest and cool down, as well as RR during exercise were less than 10%. The variation between technologies for the remaining variables ranged between 12.3-39.9% and 10.9-41.1% for TM and HIFT, respectively. Conclusions The Hx smart garment may be utilized to provide select cardiorespiratory data in a TM and HIFT session. We recommend that the validity and reliability be fully established before the Hx smart garment is entirely utilized for all cardiorespiratory data and research purposes in a field-based environment.

To determine the agreement between the Open Barbell (OB) and Tendo weightlifting analyzer (TWA) for measuring barbell velocity, eleven men (19.4 &plusmn, 1.0 y) performed one set of 2&ndash, 3 repetitions at four sub-maximal percentage loads, [i.e., 30, 50, 70, and 90% one-repetition maximum (1RM)] in the back (BS) and front squat (FS) exercises. During each repetition, peak and mean barbell velocity were recorded by OB and TWA devices, and the average of the 2&ndash, 3 repetitions was used for analyses. Although the repeated measures analysis of variance revealed significantly (p &le, 0.005) greater peak and mean velocity scores from OB across all intensities, high intraclass correlation coefficients (ICC2,K = 0.790&ndash, 0.998), low standard error of measurement (SEM2,K = 0.040&ndash, 0.119 m&middot, s&minus, 1), and coefficients of variation (CV = 2&ndash, 4%) suggested consistency between devices. Positive (r = 0.491&ndash, 0.949) Pearson correlations between averages and differences (between devices) in peak velocity, as well as associated Bland-Altman plots, showed greater differences occurred as the velocity increased, particularly at low-moderate intensity loads. OB consistently provides greater barbell velocity scores compared to TWA, and the differences between devices were more apparent as the peak velocity increased with low-to-moderate loads. Strength coaches and athletes may find better agreement between devices if the mean velocity scores are only considered.

Spitz, RW, Gonzalez, AM, Ghigiarelli, JJ, Sell, KM, and Mangine, GT. Load-velocity relationships of the back vs. front squat exercises in resistance-trained men. J Strength Cond Res 33(2): 301-306, 2019-The purpose of this investigation was to describe and compare changes in barbell velocity in relation to relative load increases during the back squat (BS) and front squat (FS) exercises. Eleven National Collegiate Athletic Association Division I baseball position players (19.4 ± 1.0 years; 182.4 ± 6.5 cm; and 87.2 ± 7.4 kg) performed trials at maximum speed with loads of 30, 50, 70, and 90% of their predetermined 1 repetition maximum (1RM) for both BS and FS. Peak and mean velocity was recorded during each repetition using an accelerometer. Differences between exercises and relative loading were assessed by separate 2 × 4 (condition × relative load) repeated-measures analysis of variance for mean and peak velocity. In addition, the load-velocity relationship across submaximal loadings in BS and FS were further assessed by calculating their respective slopes and comparing slopes through a paired-samples t-test. No significant condition × relative load interactions were noted for mean velocity (p = 0.072) or peak velocity (p = 0.203). Likewise, no significant differences in the slope for BS and FS were noted for mean velocity (p = 0.057) or peak velocity (p = 0.196). However, significant main effects for relative load were noted for both mean and peak velocity (p < 0.001), whereby mean and peak velocity were progressively reduced across all relative loads (i.e., 30, 50, 70, and 90% 1RM) for both the BS and FS. Our results demonstrate that the load-velocity relationships of the BS and FS exercises seem to be similar; therefore, similar approaches may be used with these squat variations when monitoring barbell velocity or implementing velocity-based strength training.

AB The innate immune response is generally considered to have an important role in tissue remodeling after resistance exercise. Purpose: The purpose of this study was to compare changes in markers of monocyte recruitment after an acute bout of high-intensity (HVY) versus high-volume (VOL) lower-body resistance exercise. Methods: Ten resistance-trained men (24.7 +/- 3.4 yr, 90.1 +/- 11.3 kg, 176.0 +/- 4.9 cm) performed each protocol in a randomized, counterbalanced order. Blood samples were collected at baseline, immediately (IP), 30 min (30P), 1 h (1H), 2 h (2H), and 5 h (5H) postexercise. Plasma concentrations of monocyte chemoattractant protein 1 (MCP-1), tumor necrosis factor alpha (TNF-[alpha]), myoglobin, and cortisol were measured via assay. Tumor necrosis factor receptor 1 (TNFr1), macrophage-1 antigen (cluster of differentiation 11b [CD11b]), and C-C chemokine receptor 2 (CCR2) expression levels were measured using flow cytometry. TNFr1 and CD11b were assessed on CD14++CD16- monocytes, whereas CCR2 was assessed on CD14+ monocytes. Results: Plasma myoglobin concentrations were significantly greater after HVY compared with VOL (P < 0.001). Changes in plasma TNF-[alpha], MCP-1, and expression levels of CCR2 and CD11b were similar between HVY and VOL. When collapsed across groups, TNF-[alpha] was significantly increased at IP, 30P, 1H, and 2H (P values < 0.05), whereas MCP-1 was significantly elevated at all postexercise time points (P values < 0.05). CCR2 expression on CD14+ monocytes was significantly lower at IP, 1H, 2H, and 5H (P values < 0.05). CD11b expression on CD14++ CD16- was significantly greater at IP (P < 0.014) and 1H (P = 0.009). TNFr1 expression did not differ from baseline at any time point. Plasma cortisol concentrations did not seem to be related to receptor expression. Conclusions: Results indicate that both HVY and VOL protocols stimulate a robust proinflammatory response. However, no differences were noted between resistance exercise training paradigms.

Background: Specific mood states were examined during the CrossFit Open, a consecutive 5-week fitness competition involving five separate CrossFit&reg, workouts, to determine whether the unique design or strenuous workouts of the competition resulted in acute and/or chronic mood state alterations. Methods: Participants (n = 8) completed the Profile of Mood States (POMS) questionnaire one-week prior to the competition (baseline), prior to (PRE), immediately post (IP), 30-min post- (30P) and 60-min post-workout (60P) each week. Tension, depression, anger, confusion, fatigue and vigor were derived from the POMS, as was Total Mood Disturbance (TMD) and an Energy Index (EI). Results: Workout intensity exceeded 93% HRmax each week. No differences were observed between baseline and PRE-workout mood states across weeks, indicating little effect of the unique competition design. Significant (week x time) interactions were observed for TMD (p = 0.037), EI (p = 0.038) and fatigue (p = 0.005). Acute mood state fluctuations were consistent across each week, where mood states improved to and beyond PRE values 60-min post-workout. Conclusions: In competitors, the differences in workout design between each week did not influence mood states. This may be related to adaptation to this style of training, while the acute mood state alterations are likely due to the workout intensity.

Background CrossFit® practitioners commonly track progress by monitoring their ability to complete a variety of standardized benchmark workouts within a typical class setting. However, objective assessment of progress is challenging because normative data does not currently exist for any of these benchmark workouts. Therefore, the purpose of this study was to develop normative values for five common benchmark workouts (i.e., Fran, Grace, Helen, Filthy-50 [F50], and Fight-Gone-Bad [FGB]). Methods Performance data from 133,857 male (M) and female (F) profiles located on a publicly available website were collected and sorted by sex (i.e., male [M] and female [F]) and competitive age classification (i.e., teen [T], individual [I], or masters [M]) and screened for errors. Subsequently, 10,000 valid profiles were randomly selected for analysis. Results Means and standard deviations were calculated for each category for Fran (IM 250 ± 106 s; IF 331 ± 181 s; MM 311 ± 138 s; MF 368 ± 138 s; TM 316 ± 136 s; and TF 334 ± 120 s), Grace (IM 180 ± 90 s; IF 213 ± 96 s; MM 213 ± 93 s; MF 238 ± 100 s; TM 228 ± 63 s; and TF 223 ± 69 s), Helen (IM 9.5 ± 1.9 min; IF 11.1 ± 2.4 min; MM 10.2 ± 2.0 min; MF 11.5 ± 2.3 min; TM 9.4 ± 1.6 min; and TF 12.7 ± 1.9 min), F50 (IM 24.4 ± 5.9 min; IF 27.3 ± 6.9 min; MM 26.7 ± 6.1 min; MF 28.2 ± 6.0 min; TM 25.9 ± 7.9 min; and TF 28.3 ± 8.1 min), and FGB (IM 335 ± 65 repetitions; IF 292 ± 62 repetitions; MM 311 ± 59 repetitions; MF 280 ± 54 repetitions; TM 279 ± 44 repetitions; and TF 238 ± 35 repetitions). These values were then used to calculate normative percentile (in deciles) values for each category within each workout. Separate, one-way analyses of variance revealed significant (p

Mangine, GT, Huet, K, Williamson, C, Bechke, E, Serafini, P, Bender, D, Hudy, J, and Townsend, J. A resisted sprint improves rate of force development during a 20-m sprint in athletes. J Strength Cond Res 32(6): 1531-1537, 2018-This study examined the effect of a resisted sprint on 20-m sprinting kinetics. After a standardized warm-up, 23 (male = 10, female = 13) Division I basketball players completed 3 maximal 20-m sprint trials while tethered to a robotic resistance device. The first sprint (S1) used the minimal, necessary resistance (1 kg) to detect peak (PK) and average (AVG) sprinting power (P), velocity (V), and force (F); peak rate of force production (RFD) was also calculated. The second sprint (S2) was completed against a load equal to approximately 5% of the athlete's body mass. Minimal resistance (1 kg) was again used for the final sprint (S3). Approximately 4-9 minutes of rest was allotted between each sprint. Separate analyses of variance with repeated measures revealed significant (p ≤ 0.05) main effects for all sprinting kinetic measures except VPK (p = 0.067). Compared with S1, increased (p < 0.006) 20-m sprint time (3.4 ± 4.9%), PAVG (115.9 ± 33.2%), PPK (65.7 ± 23.7%), FAVG (134.1 ± 34.5%), FPK (65.3 ± 16.2%), and RFD (71.8 ± 22.2%) along with decreased (p < 0.001) stride length (-21 ± 15.3%) and VAVG (-6.6 ± 4.6%) were observed during S2. During S3, only RFD was improved (5.2 ± 7.1%, p < 0.001) compared with S1. In conclusion, completing a short, resisted sprint with a load equating to 5% of body mass before a short sprint (∼20-meters) does not seem to affect sprinting time or kinetics. However, it does appear to enhance RFD.

Gonzalez, AM, Spitz, RW, Ghigiarelli, JJ, Sell, KM, and Mangine, GT. Acute effect of citrulline malate supplementation on upper-body resistance exercise performance in recreationally resistance-trained men. J Strength Cond Res 32(11): 3088-3094, 2018-To investigate the effect of citrulline malate (CM) supplementation on upper-body resistance exercise performance, 12 recreationally resistance-trained men (21.4 ± 1.6 years; 163.0 ± 46.2 cm; 85.0 ± 12.4 kg) underwent 2 testing sessions administered in a randomized, double-blind fashion. During each visit, participants were provided either 8 g of CM or a placebo (PL) 40 minutes before beginning a standardized warm-up and initiating a barbell bench press resistance exercise protocol consisting of 5 sets of 15 repetitions at 75% 1 repetition maximum with 2-minute rest intervals. Participants were instructed to complete as many repetitions as possible until either reaching 15 repetitions or muscular failure. Total number of repetitions performed and power output were recorded for each set. Subjective measures of energy, focus, fatigue, and perceived exertion, along with muscle thickness of the triceps brachii, were assessed before and after exercise. Significant (p ≤ 0.05) main effects for time were observed for all variables except for subjective feelings of energy (p = 0.085). A group × time interaction (F = 2.86, p = 0.034, n = 0.21) was observed for repetitions performed, where participants performed more (p = 0.015) repetitions on set 3 during PL (5.7 ± 1.2 repetitions) compared with CM (4.6 ± 1.2 repetitions). However, during set 4, participants tended (p = 0.089) to perform more repetitions during CM (4.8 ± 1.8 repetitions) compared with PL (4.3 ± 1.3 repetitions). No other differences were observed between trials. Supplementation with 8 g of CM 40 minutes before the barbell bench press resistance exercise protocol did not increase exercise performance, augment the muscle swelling response to training, or alter subjective measures of focus, energy, and fatigue in recreationally resistance-trained men.

Townsend, JR, Bender, D, Vantrease, WC, Hudy, J, Huet, K, Williamson, C, Bechke, E, Serafini, PR, and Mangine, GT. Isometric midthigh pull performance is associated with athletic performance and sprinting kinetics in Division I men and women's basketball players. J Strength Cond Res 33(10): 2665-2673, 2019- The relationships between isometric mid-thigh pull (IMTP) force, athletic performance measures, and sprint kinetics in Division I men's and women's basketball players were investigated. Twenty-three (male = 8, female = 15) Division 1 basketball players completed a maximal 20-m sprint trial while tethered to a device that provided kinetic feedback (peak and average sprinting power, velocity and force). Additionally, 1 repetition maximum (1RM) front squat, 1RM hang clean, vertical jump height, and agility (proagility and lane agility) tests were performed. Rate of force development (RFD) at 50, 100, 150, 200 and 250 milliseconds of IMTP and peak force (PF) were also collected. Pearson's product-moment correlation analysis was used to examine the relationships between these measures. Significant (p ≤ 0.05) relationships were observed between IMTP PF and sprint time over all distances (5-20 m; r = -0.62 to 0.69), average sprint velocity (r = 0.50-0.70), peak sprint velocity (r = 0.50-0.54), average sprint force (r = 0.48-0.69), and average sprint power (r = 0.62-0.73). Sprinting kinetic measures (average force and power) over the first 5 m were also significantly (p ≤ 0.05) related to IMTP RFD (50-250 ms; r = 0.42-0.62). Results indicate that IMTP variables are significantly associated with 20-m sprint kinetics. Specifically, IMTP RFD appears to be related to the initial acceleration kinetics of a sprint. Strength and conditioning professionals can possibly implement the IMTP for improved assessment and monitoring of athletic performance and training.

Serafini, PR, Feito, Y, and Mangine, GT. Self-reported measures of strength and sport-specific skills distinguish ranking in an international online fitness competition. J Strength Cond Res 32(12): 3483-3493, 2018-To determine if self-reported performance measures could distinguish ranking during the 2016 CrossFit Open, data from 3,000 male (n = 1,500; 27.2 ± 8.4 years; 85.2 ± 7.9 kg; 177.0 ± 6.5 cm) and women (n = 1500, 28.7 ± 4.9 years; 63.7 ± 5.8 kg; 163.7 ± 6.6 cm) competitors was used for this study. Competitors were split by gender and grouped into quintiles (Q1-Q5) based upon their final ranking. Quintiles were compared for one-repetition maximum (1RM) squat, deadlift, clean and jerk (CJ), snatch, 400 m sprint, 5,000 m run, and benchmark workouts (Fran, Helen, Grace, Filthy-50, and Fight-Gone-Bad). Separate one-way analyses of variance revealed that all competitors in Q1 reported greater (p ≤ 0.05) 1RM loads for squat (men: 201.6 ± 19.1 kg; women: 126.1 ± 13.0 kg), deadlift (men: 232.4 ± 20.5 kg; women: 148.3 ± 14.5 kg), CJ (men: 148.9 ± 12.1 kg; women: 95.7 ± 8.4 kg), and snatch (men: 119.4 ± 10.9 kg; women 76.5 ± 7.6 kg) compared with other quintiles. In addition, men in Q1 (59.3 ± 5.9 seconds) reported faster (p ≤ 0.05) 400 m times than Q3 only (62.6 ± 7.3 seconds), but were not different from any group in the 5,000 m run. Women in Q2 (67.5 ± 8.8 seconds) reported faster (p ≤ 0.05) 400 m times than Q3-Q5 (73.5-74.8 seconds), and faster (21.3 ± 1.8 minutes, p < 0.02) 5,000 m times than Q4 (22.6 ± 2.2 minutes) and Q5 (22.6 ± 1.9 minutes). Faster (p ≤ 0.05) Fran times were reported by Q1 (men: 138.2 ± 13.3 seconds; women: 159.4 ± 28.3 seconds) compared with other groups, while the results of other workouts were variable. These data indicate that the most successful athletes excel in all areas of fitness/skill, while lower-ranking athletes should focus on developing strength and power after achieving sufficient proficiency in sport-specific skills.

To determine if unilateral measures of muscle architecture in the rectus femoris (RF) and vastus lateralis (VL) were related to (and predictive of) sprinting speed and unilateral (and bilateral) force (FRC) and power (POW) during a 30 s maximal sprint on the Woodway Curve 3.0 non-motorized treadmill. Twenty-eight healthy, physically active men (n = 14) and women (n = 14) (age = 22.9 ± 2.4 years; body mass = 77.1 ± 16.2 kg; height = 171.6 ± 11.2 cm; body-fa t = 19.4 ± 8.1%) completed one familiarization and one 30-s maximal sprint on the TM to obtain maximal sprinting speed, POW and FRC. Muscle thickness (MT), cross-sectional area (CSA) and echo intensity (ECHO) of the RF and VL in the dominant (DOM; determined by unilateral sprinting power) and non-dominant (ND) legs were measured via ultrasound. Pearson correlations indicated several significant (p < 0.05) relationships between sprinting performance [POW (peak, DOM and ND), FRC (peak, DOM, ND) and sprinting time] and muscle architecture. Stepwise regression indicated that POW(DOM) was predictive of ipsilateral RF (MT and CSA) and VL (CSA and ECHO), while POW(ND) was predictive of ipsilateral RF (MT and CSA) and VL (CSA); sprinting power/force asymmetry was not predictive of architecture asymmetry. Sprinting time was best predicted by peak power and peak force, though muscle quality (ECHO) and the bilateral percent difference in VL (CSA) were strong architectural predictors. Muscle architecture is related to (and predictive of) TM sprinting performance, while unilateral POW is predictive of ipsilateral architecture. However, the extent to which architecture and other factors (i.e. neuromuscular control and sprinting technique) affect TM performance remains unknown.

The purpose of this study was to determine the relationship between visual tracking speed (VTS) and reaction time (RT) on basketball-specific measures of performance. Twelve professional basketball players were tested before the 2012-13 season. Visual tracking speed was obtained from 1 core session (20 trials) of the multiple object tracking test, whereas RT was measured by fixed- and variable-region choice reaction tests, using a light-based testing device. Performance in VTS and RT was compared with basketball-specific measures of performance (assists [AST]; turnovers [TO]; assist-to-turnover ratio [AST/TO]; steals [STL]) during the regular basketball season. All performance measures were reported per 100 minutes played. Performance differences between backcourt (guards; n = 5) and frontcourt (forward/centers; n = 7) positions were also examined. Relationships were most likely present between VTS and AST (r = 0.78; p < 0.003), STL (r = 0.77; p < 0.003), and AST/TO (r = 0.78; p < 0.003), whereas a likely relationship was also observed with TO (r = 0.49; p < 0.109). Reaction time was not related to any of the basketball-specific performance measures. Backcourt players were most likely to outperform frontcourt players in AST and very likely to do so for VTS, TO, and AST/TO. In conclusion, VTS seems to be related to a basketball player's ability to see and respond to various stimuli on the basketball court that results in more positive plays as reflected by greater number of AST and STL and lower turnovers.

Exercise routines in which intensity fluctuates, such as Spinning and Treading, are gaining in popularity in fitness industry. However, literature on how this dynamic protocol may affect the exercise metabolism is lacking. The present investigation was undertaken to examine the effect of intensity fluctuation and its magnitude on oxygen uptake and substrate utilization during exercise and recovery. Fifteen men and 15 women were randomly assigned into 1 of the 3 groups consisting of 10 participants of equal gender. Each group performed one of the three 30-minute exercise protocols that yielded the same total power output: (a) cycling at a constant power output of 75 W (P1), (b) cycling with power output alternating between 50 and 100 W every 5 minutes (P2), and (c) cycling with power output alternating between 25 and 125 W every 5 minutes (P3). Each exercise session was followed by a 25-minute recovery. Oxygen uptake (VO2), carbon dioxide production (VCO2), and respiratory exchanged ratio were measured at rest and during exercise and recovery. Rates of carbohydrate (COX) and fat oxidation (FOX) were calculated based on VO2 and VCO2 using the stoichiometric equations. VO2 in ml·kg-1·min-1 did not differ across the 3 protocols during exercise, but was higher (p ≤ 0.05) in P2 (4.92 ± 0.51) or P3 (4.94 ± 0.24) than P1 (4.17 ± 0.19) during recovery. COX in mg·kg-1·min-1 was higher (p ≤ 0.05) in P3 (17.68 ± 1.30) than in P1 (12.22 ± 1.55) or P2 (12.06 ± 1.47) during exercise and higher in P3 (4.17 ± 0.45) than in P1 (2.60 ± 0.36) during recovery. FOX in mg·kg-1·min-1 was lower (p ≤ 0.05) in P3 (2.61 ± 0.47) than in P1 (4.30 ± 0.60) or P2 (4.22 ± 0.47) during exercise but remained similar across the 3 protocols during recovery. These data indicate that intensity fluctuation of sufficient magnitude can alter exercise metabolism independent of the total power output or overall intensity. The 2 variable intensity protocols used in the study (i.e., P2 and P3) are equally effective in augmenting postexercise V[Combining Dot Above]O2, but the protocol with a greater magnitude of fluctuation also elicits greater COX coupled with reduced FOX during exercise.

The purpose of this investigation was to determine which physiological assessments best predicted high-intensity running (HIR) performance during a women's collegiate soccer game. A secondary purpose was to examine the relationships among physiological performance measures including muscle architecture on soccer performance (distance covered, HIR, and sprints during the game) during a competitive collegiate women's soccer game. Ten National Collegiate Athletic Association (NCAA) Division I women soccer players performed physiological assessments within a 2-week period before a competitive regulation soccer game performed during the spring season. Testing consisted of height, body mass, ultrasound measurement of dominant (DOMleg), and nondominant leg (NDOMleg) vastus lateralis for muscle thickness (MT) and pennation angle (PA), VO2max, running economy, and Wingate anaerobic test (WAnT) for peak power (PP), mean power (MP), and fatigue rate (FR). During the game, distance run, HIR, and sprints were measured using a 10-Hz global positioning system. Stepwise regression revealed that VO2max, dominant leg thickness, and dominant leg PA were the strongest predictors of HIR distance during the game (R = 0.989, SEE = 115.5 m, p = 0.001). V[Combining Dot Above]O2max was significantly correlated with total distance run (r = 0.831; p = 0.003), HIR (r = 0.755; p = 0.012), WAnTPP (r = -0.737; p = 0.015), WAnTPP·kg (r = -0.706; p = 0.022), and WAnTFR (r = -0.713; p = 0.021). DOMlegMT was significantly correlated with WAnTFR (r = 0.893; p = 0.001). DOMlegPA was significantly correlated with WAnTFR (r = 0.740; p = 0.023). The NDOMlegPA was significantly correlated to peak running velocity (r = 0.781; p = 0.013) and WAnT MP·kg (r = 0.801; p = 0.01). Results of this study indicate that V[Combining Dot Above]O2max and muscle architecture are important characteristics of NCAA Division I women soccer players and may predict HIR distance during a competitive contest.

The purpose of this study was to investigate age-related changes in anthropometric and performance variables in professional baseball players. Baseball players (n = 1,157) from several professional baseball organizations were categorized into 7 cohorts based upon age. All adolescent athletes were categorized as age group 1 (AG1), whereas the next 5 groups (AG2-AG6) consisted of players 20-22, 23-25, 26-28, 29-31, and 31-34 years, respectively. The final group (AG7) comprised athletes ≥35 years. All performance assessments were part of the athlete's normal preseason training camp testing routine. Field assessments were used to analyze lower-body power, speed, agility, grip strength, and body composition. The players were heaviest between the ages of 29 and 31 (AG5), and their body mass in that age group was 10.1% (p = 0.004) greater than that of AG1. A 7.0% increase (p = 0.000) in lean body mass occurred between AG1 and AG5. No differences in 10-yd sprint times or agility were seen across any age group or position. A 2.0 seconds (p = 0.001) slower run time for the 300-yd shuttle was seen between AG4 and AG5 for all positions combined. Elevations in grip strength were seen at AG4 compared with AG1 (p = 0.001) and AG2 (p = 0.007) for all positions combined. No other differences were noted. Lower-body power was increased for all positions combined from AG1 to AG3 (p = 0.007). This pattern was similar to that observed in position players, but a 12.4% decrease (p = 0.024) in VJMP was seen between AG7 and AG5 in pitchers. Results of this study indicate that lower-body power is maintained in baseball players until the age of 29-31, whereas speed, agility, and grip strength are maintained in players able to play past the age of 35 years. Age-related differences observed in this study suggest that athletes focus on their strength and conditioning programs to extend the length of their professional careers.

Mangine, GT, Hoffman, JR, Gonzalez, AM, Townsend, JR, Wells, AJ, Jajtner, AR, Beyer, KS, Boone, CH, Wang, R, Miramonti, AA, LaMonica, MB, Fukuda, DH, Witta, EL, Ratamess, NA, and Stout, JR. Exercise-induced hormone elevations are related to muscle growth. J Strength Cond Res 31(1): 45-53, 2017-Partial least squares regression structural equation modeling (PLS-SEM) was used to examine relationships between the endocrine response to resistance exercise and muscle hypertrophy in resistance-trained men. Pretesting (PRE) measures of muscle size (thickness and cross-sectional area) of the vastus lateralis and rectus femoris were collected in 26 resistance-trained men. Participants were randomly selected to complete a high-volume (VOL, n = 13, 10-12RM, 1-minute rest) or high-intensity (INT, n = 13, 3-5RM, 3-minute rest) resistance training program. Blood samples were collected at baseline, immediately postexercise, 30-minute, and 60-minute postexercise during weeks 1 (week 1) and 8 (week 8) of training. The hormonal responses (testosterone, growth hormone [22 kD], insulin-like growth factor-1, cortisol, and insulin) to each training session were evaluated using area-under-the-curve (AUC) analyses. Relationships between muscle size (PRE), AUC values (week 1 + week 8) for each hormone, and muscle size (POST) were assessed using a consistent PLS-SEM algorithm and tested for statistical significance (p ≤ 0.05) using a 1,000 samples consistent bootstrapping analysis. Group-wise comparisons for each relationship were assessed through independent t-tests. The model explained 73.4% (p < 0.001) of variance in muscle size at POST. Significant pathways between testosterone and muscle size at PRE (p = 0.043) and muscle size at POST (p = 0.032) were observed. The ability to explain muscle size at POST improved when the model was analyzed by group (INT: R = 0.882; VOL: R = 0.987; p < 0.001). No group differences in modal quality were found. Exercise-induced testosterone elevations, independent of the training programs used in this study, seem to be related to muscle growth.

The purpose of the present study was to investigate the additive effects of ballistic training to a traditional heavy resistance training program on upper- and lower-body maximal strength. Seventeen resistance-trained men were randomly assigned to 1 of 2 groups: (i) a combined ballistic and heavy resistance training group (COM; age = 21.4 +/- 1.7 years, body mass = 82.7 +/- 15.1 kg) or (ii) a heavy resistance training group (HR; age = 20.1 +/- 1.2 years, body mass = 81.0 +/- 9.2 kg) and subsequently participated in an 8-week periodized training program. Training was performed 3 days per week, that is, 6-8 exercises per workout (6-8 traditional exercises for HR; 4-6 traditional + 2 ballistic exercises in COM) for 3-8 repetitions. A significant increase in 1-repetition maximum (1RM) squat was shown in both groups (COM = 15.2%; HR = 17.3%) with no difference observed between groups. However, 1RM bench press increased to a significantly greater extent (P = 0.04) in COM than HR (11.6% vs. 7.1%, respectively). For peak power attained during the jump squat, an interaction (P = 0.02) was observed where the 5.4% increase in COM and -3.2% reduction in HR were statistically significant. Nonsignificant increases were observed in peak plyometric push-up power in COM (8.5%) and HR (3.4%). Lean body mass increased significantly in both groups, with no between-group differences observed. The results of this study support the inclusion of ballistic exercises into a heavy resistance training program for increasing 1RM bench press and enhancing lower-body power.

The purpose of the present investigation was to examine strength performance of 6 common resistance training exercises using free weight bars of different thickness. Eleven resistance-trained men (8.2 +/- 2.6 years of experience; age: 22.1 +/- 1.6 years; body mass: 90.5 +/- 8.9 kg) underwent 1 repetition maximum (1RM) strength testing on 6 occasions in random order for the deadlift, bent-over row, upright row, bench press, seated shoulder press, and arm curl exercises under 3 conditions using: (a) a standard Olympic bar (OL), (b) a 2-inch thick bar (5.08 cm grip span), and (c) a 3-inch thick bar (7.62 cm grip span). Significant (p < 0.05) interactions were observed for the "pulling" exercises. For the deadlift and bent-over row, highest 1RM values were obtained with OL, followed by the 2- and 3-inch bar. Significant 1RM performance decrements for the 2- and 3-inch bars were approximately 28.3 and 55.0%, respectively, for the deadlift; decrements for the 2- and 3-inch bars were approximately 8.9 and 37.3%, respectively, for the bent-over row. For the upright row and arm curl, similar 1RMs were obtained for OL and the 2-inch bar. However, a significant performance reduction was observed using the 3-inch bar (approximately 26.1% for the upright row and 17.6% for the arm curl). The reductions in 1RM loads correlated significantly to hand size and maximal isometric grip strength (r = -0.55 to -0.73). No differences were observed between bars for the bench press or shoulder press. In conclusion, the use of 2- and 3-inch thick bars may result in initial weight reductions primarily for pulling exercises presumably due to greater reliance on maximal grip strength and larger hand size.