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Pablo Jodra, Raúl Domínguez, Antonio J. Sánchez-Oliver, Pablo Veiga-Herreros and Stephen J. Bailey

Purpose: Dietary supplementation with inorganic nitrate (NO3 ) can enhance high-intensity exercise performance by improving skeletal muscle contractility and metabolism, but the extent to which this might be linked to altered psychophysiological processes is presently unclear. The purpose of this study was to assess the effects of NO3 -rich beetroot juice (BJ) supplementation on profile of mood states, ratings of perceived exertion (RPE), and performance in a 30-second Wingate cycle test. Methods: In a double-blind, randomized, cross-over study, 15 subjects completed 2 laboratory sessions after ingesting NO3 -rich or NO3 -depleted (placebo) BJ. Participants initially completed the profile of mood states questionnaire. Subsequently, participants completed a warm-up followed by a 30-second all-out Wingate cycling test. After the Wingate test, participants immediately indicated the RPE of their leg muscles (RPEmuscular), cardiovascular system (RPEcardio), and general RPE (RPEgeneral). Results: Compared with the placebo condition, supplementation with BJ increased peak power output (W peak) (+4.4%, 11.5 [0.7] vs 11.1 [1.0] W·kg−1; P = .039) and lowered the time taken to reach W peak (7.3 [0.9] vs 8.7 [1.5] s; P = .002) during the Wingate test. The profile of mood states score linked to tension was increased prior to the Wingate test (4.8 [3.0] vs 3.4 [2.4]; P = .040), and RPEmuscular was lowered immediately following the Wingate test (17.7 [1.6] vs 18.3 [1.0]; P = .031), after BJ compared with placebo ingestion. Conclusions: Acute BJ supplementation improved pre-exercise tension, 30-second Wingate test performance, and lowered postexercise RPEmuscular.

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Justin J. Merrigan, James J. Tufano, Jonathan M. Oliver, Jason B. White, Jennifer B. Fields and Margaret T. Jones

Purpose: To examine rest redistribution (RR) effects on back squat kinetics and kinematics in resistance-trained women. Methods: Twelve women from strength and college sports (5.0 [2.2] y training history) participated in the randomized crossover design study with 72 hours between sessions (3 total). Participants completed 4 sets of 10 repetitions using traditional sets (120-s interset rest) and RR (30-s intraset rest in the middle of each set; 90-s interset rest) with 70% of their 1-repetition maximum. Kinetics and kinematics were sampled via force plate and 4 linear position transducers. The greatest value of repetitions 1 to 3 (peak repetition) was used to calculate percentage loss, [(repetition 10–peak repetition)/(peak repetition) × 100], and maintenance, {100–[(set mean–peak repetition)/(peak repetition)] × 100}, of velocity and power for each set. Repeated-measures analysis of variance was used for analyses (P < .05). Results: Mean and peak force did not differ between conditions. A condition × repetition interaction existed for peak power (P = .049) but not for peak velocity (P = .110). Peak power was greater in repetitions 7 to 9 (P < .05; d = 1.12–1.27) during RR. The percentage loss of velocity (95% confidence interval, –0.22% to –7.22%; P = .039) and power (95% confidence interval, –1.53% to –7.87%; P = .008) were reduced in RR. Mean velocity maintenance of sets 3 (P = .036; d = 1.90) and 4 (P = .015; d = 2.30) and mean power maintenance of set 4 (P = .006; d = 2.65) were greater in RR. Conclusion: By redistributing a portion of long interset rest into the middle of a set, velocity and power were better maintained. Therefore, redistributing rest may be beneficial for reducing fatigue in resistance-trained women.

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Arthur H. Bossi, Wouter P. Timmerman and James G. Hopker

Purpose: There are several published equations to calculate energy expenditure (EE) from gas exchanges. The authors assessed whether using different EE equations would affect gross efficiency (GE) estimates and their reliability. Methods: Eleven male and 3 female cyclists (age 33 [10] y; height: 178 [11] cm; body mass: 76.0 [15.1] kg; maximal oxygen uptake: 51.4 [5.1] mL·kg−1·min−1; peak power output: 4.69 [0.45] W·kg−1) completed 5 visits to the laboratory on separate occasions. In the first visit, participants completed a maximal ramp test to characterize their physiological profile. In visits 2 to 5, participants performed 4 identical submaximal exercise trials to assess GE and its reliability. Each trial included three 7-minute bouts at 60%, 70%, and 80% of the gas exchange threshold. EE was calculated with 4 equations by Péronnet and Massicotte, Lusk, Brouwer, and Garby and Astrup. Results: All 4 EE equations produced GE estimates that differed from each other (all P < .001). Reliability parameters were only affected when the typical error was expressed in absolute GE units, suggesting a negligible effect—related to the magnitude of GE produced by each EE equation. The mean coefficient of variation for GE across different exercise intensities and calculation methods was 4.2%. Conclusions: Although changing the EE equation does not affect GE reliability, exercise scientists and coaches should be aware that different EE equations produce different GE estimates. Researchers are advised to share their raw data to allow for GE recalculation, enabling comparison between previous and future studies.

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João Ribeiro, Luís Teixeira, Rui Lemos, Anderson S. Teixeira, Vitor Moreira, Pedro Silva and Fábio Y. Nakamura

Purpose : The current study aimed to compare the effects of plyometric (PT) versus optimum power load (OPL) training on physical performance of young high-level soccer players. Methods : Athletes were randomly divided into PT (horizontal and vertical drills) and OPL (squat + hip thrust exercises at the load of maximum power output) interventions, applied over 7 weeks during the in-season period. Squat and countermovement jumps, maximal sprint (10 and 30 m), and change of direction (COD; agility t test) were the pretraining and posttraining measured performance variables. Magnitude-based inference was used for within- and between-group comparisons. Results : OPL training induced moderate improvements in vertical squat jump (effect size [ES]: 0.97; 90% confidence interval [CI], 0.32–1.61) and countermovement jump (ES: 1.02; 90% CI, 0.46–1.57), 30-m sprint speed (ES: 1.02; 90% CI, 0.09–1.95), and COD performance (ES: 0.93; 90% CI, 0.50–1.36). After PT training method, vertical squat jump (ES: 1.08; 90% CI, 0.66–1.51) and countermovement jump (ES: 0.62; 90% CI, 0.18–1.06) were moderately increased, while small enhancements were noticed for 30-m sprint speed (ES: 0.21; 90% CI, −0.02 to 0.45) and COD performance (ES: 0.53; 90% CI, 0.24–0.81). The 10-m sprint speed possibly increased after PT intervention (small ES: 0.25; 90% CI, −0.05 to 0.54), but no substantial change (small ES: 0.36; 90% CI, −0.40 to 1.13) was noticed in OPL. For between-group analyses, the COD ability and 30-m sprint performances were possibly (small ES: 0.30; 90% CI, −0.20 to 0.81; Δ = +1.88%) and likely (moderate ES: 0.81; 90% CI, −0.16 to 1.78; Δ = +2.38%) more improved in the OPL than in the PT intervention, respectively. Conclusions : The 2 different training programs improved physical performance outcomes during the in-season period. However, the combination of vertically and horizontally based training exercises (squat + hip thrust) at optimum power zone led to superior gains in COD and 30-m linear sprint performances.

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Fergus O’Connor, Heidi R. Thornton, Dean Ritchie, Jay Anderson, Lindsay Bull, Alex Rigby, Zane Leonard, Steven Stern and Jonathan D. Bartlett

Sprint capacity is an important attribute for team-sport athletes, yet the most appropriate method to analyze it is unclear. Purpose: To examine the relationship between sprint workloads using relative versus absolute thresholds and lower-body soft-tissue and bone-stress injury incidence in professional Australian rules football. Methods: Fifty-three professional Australian rules football athletes’ noncontact soft-tissue and bone-stress lower-body injuries (N = 62) were recorded, and sprint workloads were quantified over ∼18 months using the global positioning system. Sprint volume (m) and exposures (n) were determined using 2 methods: absolute (>24.9 km·h−1) and relative (≥75%, ≥80%, ≥85%, ≥90%, ≥95% of maximal velocity). Relationships between threshold methods and injury incidence were assessed using logistic generalized additive models. Incidence rate ratios and model performances’ area under the curve were reported. Results: Mean (SD) maximal velocity for the group was 31.5 (1.4), range 28.6 to 34.9 km·h−1. In comparing relative and absolute thresholds, 75% maximal velocity equated to ~1.5 km·h−1 below the absolute speed threshold, while 80% and 85% maximal velocity were 0.1 and 1.7 km·h−1 above the absolute speed threshold, respectively. Model area under the curve ranged from 0.48 to 0.61. Very low and very high cumulative sprint loads ≥80% across a 4-week period, when measured relatively, resulted in higher incidence rate ratios (2.54–3.29), than absolute thresholds (1.18–1.58). Discussion: Monitoring sprinting volume relative to an athlete’s maximal velocity should be incorporated into athlete monitoring systems. Specifically, quantifying the distance covered at >80% maximal velocity will ensure greater accuracy in determining sprint workloads and associated injury risk.

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Ben T. Stephenson, Sven P. Hoekstra, Keith Tolfrey and Victoria L. Goosey-Tolfrey

Purpose: Paratriathletes may display impairments in autonomic (sudomotor and/or vasomotor function) or behavioral (drinking and/or pacing of effort) thermoregulation. As such, this study aimed to describe the thermoregulatory profile of athletes competing in the heat. Methods: Core temperature (T c) was recorded at 30-second intervals in 28 mixed-impairment paratriathletes during competition in a hot environment (air temperature = 33°C, relative humidity = 35%–41%, and water temperature = 25°C–27°C), via an ingestible temperature sensor (BodyCap e-Celsius). Furthermore, in a subset of 9 athletes, skin temperature was measured. Athletes’ wetsuit use was noted while heat illness symptoms were self-reported postrace. Results: In total, 22 athletes displayed a T c ≥ 39.5°C with 8 athletes ≥40.0°C. There were increases across the average T c for swim, bike, and run sections (P ≤ .016). There was no change in skin temperature during the race (P ≥ .086). Visually impaired athletes displayed a significantly greater T c during the run section than athletes in a wheelchair (P ≤ .021). Athletes wearing a wetsuit (57% athletes) had a greater T c when swimming (P ≤ .032), whereas those reporting heat illness symptoms (57% athletes) displayed a greater T c at various time points (P ≤ .046). Conclusions: Paratriathletes face significant thermal strain during competition in the heat, as evidenced by high T c, relative to previous research in able-bodied athletes and a high incidence of self-reported heat illness symptomatology. Differences in the T c profile exist depending on athletes’ race category and wetsuit use.

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Guillaume P. Ducrocq, Thomas J. Hureau, Olivier Meste and Grégory M. Blain

Context: Drop jumps and high-intensity interval running are relevant training methods to improve explosiveness and endurance performance, respectively. Combined training effects might, however, be achieved by performing interval drop jumping. Purpose: To determine the acute effects of interval drop jumping on oxygen uptake (V˙O2)—index of cardioventilatory/oxidative stimulation level and peripheral fatigue—a limiting factor of explosiveness. Methods: Thirteen participants performed three 11-minute interval training sessions during which they ran 15 seconds at 120% of the velocity that elicited maximal V˙O2 (V˙O2max) (ITrun), or drop jumped at 7 (ITDJ7) or 9 (ITDJ9) jumps per 15 seconds, interspersed with 15 seconds of passive recovery. V˙O2 and the time spent above 90% of V˙O2max (V˙TO2max) were collected. Peripheral fatigue was quantified via preexercise to postexercise changes in evoked potentiated quadriceps twitch (ΔQT). Power output was estimated during ITDJs using optical sensors. Results: All participants reached 90% of V˙O2max or higher during ITrun and ITDJ9, but only 11 did during ITDJ7. V˙TO2max was not different between ITrun and ITDJ9 (145 [76] vs 141 [151] s; P = .92) but was reduced during ITDJ7 (28 [26] s; P = .002). Mean ΔQT in ITDJ9 and ITDJ7 was not different (−17% [9%] vs −14% [8%]; P = .73) and greater than in ITrun (−8% [7%]; P = .001). No alteration in power output was found during ITDJs (37 [10] W·kg−1). Conclusion: Interval drop jumping at a high work rate stimulated the cardioventilatory and oxidative systems to the same extent as interval running, while the exercise-induced increase in fatigue did not compromise drop jump performance. Interval drop jumping might be a relevant strategy to get concomitant improvements in endurance and explosive performance.

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Blake D. McLean, Kevin White, Christopher J. Gore and Justin Kemp

Purpose: There is debate as to which environmental intervention produces the most benefit for team sport athletes, particularly comparing heat and altitude. This quasi-experimental study aimed to compare blood volume (BV) responses with heat and altitude training camps in Australian footballers. Methods: The BV of 7 professional Australian footballers (91.8 [10.5] kg, 191.8 [10.1] cm) was measured throughout 3 consecutive spring/summer preseasons. During each preseason, players participated in altitude (year 1 and year 2) and heat (year 3) environmental training camps. Year 1 and year 2 altitude camps were in November/December in the United States, whereas the year 3 heat camp was in February/March in Australia after a full exposure to summer heat. BV, red cell volume, and plasma volume (PV) were measured at least 3 times during each preseason. Results: Red cell volume increased substantially following altitude in both year 1 (d = 0.67) and year 2 (d = 1.03), before returning to baseline 4 weeks postaltitude. Immediately following altitude, concurrent decreases in PV were observed during year 1 (d = −0.40) and year 2 (d = −0.98). With spring/summer training in year 3, BV and PV were substantially higher in January than temporally matched postaltitude measurements during year 1 (BV: d = −0.93, PV: d = −1.07) and year 2 (BV: d = −1.99, PV: d = −2.25), with year 3 total BV, red cell volume, and PV not changing further despite the 6-day heat intervention. Conclusions: We found greater BV after training throughout spring/summer conditions, compared with interrupting spring/summer exposure to train at altitude in the cold, with no additional benefits observed from a heat camp following spring/summer training.

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Olfa Turki, Wissem Dhahbi, Sabri Gueid, Sami Hmaied, Marouen Souaifi and Riadh Khalifa

Purpose: To explore the effect of 4 different warm-up strategies using weighted vests and to determine the specific optimal recovery duration required to optimize the repeated change-of-direction (RCOD) performance in young soccer players. Methods: A total of 19 male soccer players (age 18 [0.88] y, body mass 69.85 [7.68] kg, body height 1.75 [0.07] m, body mass index 22.87 [2.23] kg·m−2, and body fat percentage 12.53% [2.59%]) completed the following loaded warm-up protocols in a randomized, counterbalanced cross-over, within-participants order and on separate days: weighted vest with a loading of 5% (WUV5%), 10% (WUV10%), 15% (WUV15%) body mass, and an unloaded condition (control). RCOD performance (total time, peak time, and fatigue index) was collected during the preintervention phase (5 min after the dynamic stretching sequence) for baseline values and immediately (at 15 min), at 4- and 8-minute postwarm-up intervention. Results: For each postwarm-up tested, recovery times (ie, 15 s, 4 min, and 8 min), of both total and peak times were faster following WUV5%, WUV10%, and WUV15%, compared with the unloaded condition (P ≤.001–.031, d = 1.28–2.31 [large]). There were no significant differences (P = .09–1.00, d = 0.03–0.72 [trivial–moderate]) in-between recovery times in both total and peak times following WUV5%, WUV10%, and WUV15%. However, baseline fatigue index score was significantly worse than all other scores (P ≤.001–.002, d = 1.35–2.46 [large]) following the loaded conditions. Conclusions: The findings demonstrated that a dynamic loaded warm-up increases an athlete’s initial RCOD performance up to the 8-minute postwarm-up intervention. Therefore, strength coaches need to consider using weighted vests during the warm-up for trained athletes in order to acutely optimize RCODs.

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Carl Foster, Jos J. de Koning, Christian Thiel, Bram Versteeg, Daniel A. Boullosa, Daniel Bok and John P. Porcari

Background: Pacing studies suggest the distribution of effort for optimizing performance. Cross-sectional studies of 1-mile world records (WRs) suggest that WR progression includes a smaller coefficient of variation of velocity. Purpose: This study evaluates whether intraindividual pacing used by elite runners to break their own WR (1 mile, 5 km, and 10 km) is related to the evolution of pacing strategy. We provide supportive data from analysis in subelite runners. Methods: Men’s WR performances (with 400-m or 1-km splits) in 1 mile, 5 km, and 10 km were retrieved from the IAAF database (from 1924 to present). Data were analyzed relative to pacing pattern when a runner improved their own WR. Similar analyses are presented for 10-km performance in subelite runners before and after intensified training. Results: WR performance was improved in 1 mile (mean [SD]: 3:59.4 [11.2] to 3:57.2 [8.6]), 5 km (13:27 [0:33] to 13:21 [0:33]), and 10 km (28:35 [1:27] to 28:21 [1:21]). The average coefficient of variation did not change in the 1 mile (3.4% [1.8%] to 3.6% [1.6%]), 5 km (2.4% [0.9%] to 2.2% [0.8%]), or 10 km (1.4% [0.1%] to 1.5% [0.6%]) with improved WR. When velocity was normalized to the percentage mean velocity for each race, the pacing pattern was almost identical. Very similar patterns were observed in subelite runners in the 10 km. When time improved from 49:20 (5:30) to 45:56 (4:58), normalized velocity was similar, terminal RPE increased (8.4 [1.6] to 9.1 [0.8]), coefficient of variation was unchanged (4.4% [1.1%] to 4.8% [2.1%]), and VO2max increased (49.8 [7.4] to 55.3 [8.8] mL·min−1·kg−1). Conclusion: The results suggest that when runners break their own best performances, they employ the same pacing pattern, which is different from when WRs are improved in cross-sectional data.