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Grégoire P. Millet and Kilian Jornet

Purpose: To present the acclimatization strategy employed by an elite athlete prior to 2 successful ascents to Mount Everest (including a “fastest known time”) in 1 wk. Methods: Training volume, training content, and altitude exposure were recorded daily. Vertical velocity was recorded by GPS (global positioning system) heart-rate monitor. Results: The subject first used a live high–train low and high preacclimatization method in normobaric hypoxia (NH). Daily, he combined sleeping in a hypoxic tent (total hours: ∼260) and exercising “as usual” in normoxia but also in NH (altitude >6000 m: 30 h), including at high intensity. The hypoxic sessions were performed at the second threshold on treadmill in NH at 6000 m, and the pulse saturation increased from 70% to 85% over 1 mo. Then, the subject was progressively exposed to hypobaric hypoxia, first in the Alps and then in the Himalayas. On day 18, he reached for the second time an altitude >8000 m with the fastest vertical velocity (350 m/h) ever measured between 6300 and 8400 m. Afterward, he climbed twice in a week to the summit of Mount Everest (8848 m, including a “fastest known time” of 26.5 h from Rongbuk Monastery, 5100 m). Conclusion: Overall, this acclimatization was successful and in line with the most recent recommendations: first, using live high–train low and high, and second, using hypobaric hypoxia at increasing altitudes for a better translation of the NH benefits to hypobaric hypoxia. This case study reports the preparation for the most outstanding performance ever acheived at an extreme altitude.

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Stephen S. Cheung

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Paul A. Solberg, Will G. Hopkins, Gøran Paulsen and Thomas A. Haugen

Purpose: To quantify age of peak performance and performance improvements in the years preceding peak age in elite weightlifting and powerlifting athletes using results from powerlifting World Championships in 2003–2017 and weightlifting World Championships and Olympic Games in 1998–2017. Methods: Individual performance trends were derived by fitting a quadratic curve separately to each athlete’s performance and age data. Effects were evaluated using magnitude-based inferences. Results: Peak age (mean [SD]) was 35 (7) y for powerlifters and 26 (3) y for weightlifters, a large most likely substantial difference of 9, ±1 y (mean, 90% confidence limit). Men showed possibly higher peak age than women in weightlifting (0.8, ±0.7 y; small) and a possibly lower peak age in powerlifting (1.3, ±1.8 y; trivial). Peak age of athletes who ever won a medal was very likely less than that of nonmedalists in weightlifting (1.3, ±0.6 y; small), while the difference in powerlifters was trivial but unclear. Five-year improvements prior to peak age were 12% (10%) for powerlifters and 9% (7%) for weightlifters, a small possibly substantial difference (2.9, ±2.1%). Women exhibited possibly greater improvements than men in powerlifting (2.7, ±3.8%; small) and very likely greater in weightlifting (3.5, ±1.6%; small). Medalists possibly improved less than nonmedalists among powerlifters (−1.7, ±2.3%; small), while the difference was likely trivial for weightlifters (2.3, ±1.8%). Conclusion: These novel insights on performance development will be useful for practitioners evaluating strategies for achieving success.

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Alejandro Pérez-Castilla, Antonio Piepoli, Gabriel Garrido-Blanca, Gabriel Delgado-García, Carlos Balsalobre-Fernández and Amador García-Ramos

Objective: To compare the accuracy of different devices to predict the bench-press 1-repetition maximum (1RM) from the individual load–velocity relationship modeled through the multiple- and 2-point methods. Methods: Eleven men performed an incremental test on a Smith machine against 5 loads (45–55–65–75–85%1RM), followed by 1RM attempts. The mean velocity was simultaneously measured by 1 linear velocity transducer (T-Force), 2 linear position transducers (Chronojump and Speed4Lift), 1 camera-based optoelectronic system (Velowin), 2 inertial measurement units (PUSH Band and Beast Sensor), and 1 smartphone application (My Lift). The velocity recorded at the 5 loads (45–55–65–75–85%1RM), or only at the 2 most distant loads (45–85%1RM), was considered for the multiple- and 2-point methods, respectively. Results: An acceptable and comparable accuracy in the estimation of the 1RM was observed for the T-Force, Chronojump, Speed4Lift, Velowin, and My Lift when using both the multiple- and 2-point methods (effect size ≤ 0.40; Pearson correlation coefficient [r] ≥ .94; standard error of the estimate [SEE] ≤ 4.46 kg), whereas the accuracy of the PUSH (effect size = 0.70–0.83; r = .93–.94; SEE = 4.45–4.80 kg), and especially the Beast Sensor (effect size = 0.36–0.84; r = .50–.68; SEE = 9.44–11.2 kg), was lower. Conclusions: These results highlight that the accuracy of 1RM prediction methods based on movement velocity is device dependent, with the inertial measurement units providing the least accurate estimate of the 1RM.

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Boris Dugonjić, Saša Krstulović and Goran Kuvačić

The aim of this observational cross-sectional survey was to determine the prevalence of rapid weight loss (RWL) in elite kickboxers. Kickboxers (61 males; age = 24.2 ± 4.6 years, weight = 73.9 ± 12.8 kg, and height = 179.2 ± 7.9 cm) from eight European countries completed a Rapid Weight Loss Questionnaire regarding prevalence, magnitude, and methods of RWL. All athletes (100%) were practicing RWL before the competition with a Rapid Weight Loss Questionnaire score of 52.4 ±12.9. Most kickboxers ‘usually lose between 2% and 5% of their body mass, whereas ∼30% lose between 6% and 8%. However, it is alarming that almost 30% reported cutting 10% of body weight or more sometime during their kickboxing career. Almost half of the athletes always practice gradual dieting (45.9%) and increased exercising (44.3%) to reduce body mass. Kickboxers usually reduce weight three to four times during a year, usually 7–15 days before a competition. More than a third (34.4%) started with RWL practice under the age of 17. There was no significant difference between weight divisions in weight management behaviors (p = .5, F = 0.6; η2 = .0) and no relation between the main characteristics of elite kickboxing athletes and the total RWL score. In conclusion, RWL practices in kickboxing athletes are somewhat specific and different when compared with other combat sports, which can be explained by greater number of weight classes and specific weigh-in protocol.

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Diogo V. Leal, Lee Taylor and John Hough

Purpose: Progressively overloading the body to improve physical performance may lead to detrimental states of overreaching/overtraining syndrome. Blunted cycling-induced cortisol and testosterone concentrations have been suggested to indicate overreaching after intensified training periods. However, a running-based protocol is yet to be developed or demonstrated as reproducible. This study developed two 30-min running protocols, (1) 50/70 (based on individualized physical capacity) and (2) RPETP (self-paced), and measured the reproducibility of plasma cortisol and testosterone responses. Methods: Thirteen recreationally active, healthy men completed each protocol (50/70 and RPETP) on 3 occasions. Venous blood was drawn preexercise, postexercise, and 30 min postexercise. Results: Cortisol was unaffected (both P > .05; 50/70, ηp2 = .090; RPETP, ηp2 = .252), while testosterone was elevated (both P < .05; 50/70, 35%, ηp2 = .714; RPETP, 42%, ηp2 = .892) with low intraindividual coefficients of variation (CVi) as mean (SD) (50/70, 7% [5%]; RPETP, 12% [9%]). Heart rate (50/70, effect size [ES] = 0.39; RPETP, ES = −0.03), speed (RPETP, ES = −0.09), and rating of perceived exertion (50/70 ES = −0.06) were unchanged across trials (all CVi < 5%, P < .05). RPETP showed greater physiological strain (P < .01). Conclusions: Both tests elicited reproducible physiological and testosterone responses, but RPETP induced greater testosterone changes (likely due to increased physiological strain) and could therefore be considered a more sensitive tool to potentially detect overtraining syndrome. Advantageously for the practitioner, RPETP does not require a priori exercise-intensity determination, unlike the 50/70, enhancing its integration into practice.

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Thomas A. Haugen, Felix Breitschädel and Stephen Seiler

Purpose: To quantify possible differences in sprint mechanical outputs in handball and basketball players according to playing standard and position. Methods: Sprint tests of 298 male players were analyzed. Theoretical maximal velocity (v 0), horizontal force (F 0), horizontal power (P max), force–velocity slope (S FV), ratio of force (RFmax), and index of force application technique (D RF) were calculated from anthropometric and spatiotemporal data using an inverse dynamic approach applied to the center-of-mass movement. Results: National-team handball players displayed clearly superior 10-m times (0.03, ±0.02 s), 40-m times (0.12, ±0.07 s), F 0 (0.1, ±0.2 N·kg−1), v 0 (0.3, ±0.2 m·s−1), and P max (0.9, ±0.5 W·kg−1) than corresponding top-division players. Wings differed from the other positions in terms of superior 10-m times (0.02, ±0.01 to 0.07, ±0.02 s), 40-m times (0.07, ±0.05 to 0.27, ±0.07 s), F 0 (0.2, ±0.1 to 0.4, ±0.2 N·kg−1), v 0 (0.1, ±0.1 to 0.5, ±0.1 m·s−1), P max (0.7, ±0.4 to 2.0, ±0.5 W·kg−1), and RFmax (0.6, ±0.4 to 1.3, ±0.4%). In basketball, guards differed from forwards in terms of superior 10-m times (0.03, ±0.02 s), 40-m times (0.10, ±0.08 s), v 0 (0.2, ±0.1 m·s−1), P max (0.6, ±0.6 W·kg−1), and RFmax (0.4, ±0.3%). The effect magnitudes of the substantial differences observed ranged from small to large. Conclusions: The present results provide an overall picture of the force–velocity profile continuum in sprinting handball and basketball players and serve as useful background information for practitioners when diagnosing individual players and prescribing training programs.

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Thiago S. Duarte, Danilo L. Alves, Danilo R. Coimbra, Bernardo Miloski, João C. Bouzas Marins and Maurício G. Bara Filho

Purpose: To analyze the technical and tactical training load in professional volleyball players, using subjective internal training load (session rating of perceived exertion  [SRPE]) and objective internal training load (training impulse of the heart rate [HR]) and the relationship between them. Methods: The sample was composed of 15 male professional volleyball players. They were monitored during 37 training sessions that included both technical (n = 23) and tactical (n = 14) training. Technical and training load was calculated using SRPE and training impulse of the HR. Results: Significant correlations were found between the methods in tactical (r = .616) and technical training (r = −.414). Furthermore, it was noted that technical training occurs up to 80% of HRmax (zone 3) and tactical training between 70% and 90% of HRmax (zones 3–4). Conclusions: The training impulse of the HR method has proved to be effective for training-load control during tactical training. However, it was limited compared with technical training. Thus, the use of SRPE is presented as a more reliable method in the different types of technical training in volleyball.

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Alba Reguant-Closa, Margaret M. Harris, Tim G. Lohman and Nanna L. Meyer

Nutrition education visual tools are designed to help the general population translate science into practice. The purpose of this study was to validate the Athlete’s Plate (AP) to ensure that it meets the current sport nutrition recommendations for athletes. Twelve registered dietitians (RDs; 10 female and 2 male) volunteered for the study. Each registered dietitian was asked to create three real and virtual plates at three different times corresponding to breakfast, lunch, and dinner, and the three different AP training loads, easy (E), moderate (M), and hard (H), divided into two weight categories (male 75 kg and female 60 kg). Data of the real and virtual plates were evaluated using Computrition software (v. 18.1; Computrition, Chatsworth, CA). Statistical analyses were conducted by SPSS (version 23.0; IBM, Armonk, NY) to compare the difference between each training load category (E, M, and H) and the recommendations. No statistically significant differences were found among the created plates and the recommendations for energy, carbohydrates, fat, and fiber for E, M, and H. Protein relative to body mass (BM) was higher than recommended for E (1.9 ± 0.3 g·kg−1 BM·day−1, p = .003), M (2.3 ± 0.3 g·kg−1 BM·day−1, p < .001), and H (2.9+0.5 g·kg−1 BM·day−1, p < .001). No differences were found for the macronutrient distribution by gender when correcting for kilograms of body mass. The authors conclude that the AP meets the nutrition recommendations for athletes at different training intensities for energy, carbohydrates, fat, and fiber, but exceeds the recommendations for protein. Further research should consider this protein discrepancy and develop an AP model that meets, besides health and performance goals, contemporary guidelines for sustainability.

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Paul F.J. Merkes, Paolo Menaspà and Chris R. Abbiss

Purpose: To determine the validity of the Velocomp PowerPod power meter in comparison with the Verve Cycling InfoCrank power meter. Methods: This research involved 2 separate studies. In study 1, 12 recreational male road cyclists completed 7 maximal cycling efforts of a known duration (2 times 5 s and 15, 30, 60, 240, and 600 s). In study 2, 4 elite male road cyclists completed 13 outdoor cycling sessions. In both studies, power output of cyclists was continuously measured using both the PowerPod and InfoCrank power meters. Maximal mean power output was calculated for durations of 1, 5, 15, 30, 60, 240, and 600 seconds plus the average power output in study 2. Results: Power output determined by the PowerPod was almost perfectly correlated with the InfoCrank (r > .996; P < .001) in both studies. Using a rolling resistance previously reported, power output was similar between power meters in study 1 (P = .989), but not in study 2 (P = .045). Rolling resistance estimated by the PowerPod was higher than what has been previously reported; this might have occurred because of errors in the subjective device setup. This overestimation of rolling resistance increased the power output readings. Conclusion: Accuracy of rolling resistance seems to be very important in determining power output using the PowerPod. When using a rolling resistance based on previous literature, the PowerPod showed high validity when compared with the InfoCrank in a controlled field test (study 1) but less so in a dynamic environment (study 2).