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Thermal Sensation After the 10-km Open-Water Swimming in Cool Water Depends on the Skin’s Thermal Sensitivity Rather Than Core Temperature

Tomomi Fujimoto, Yuiko Matsuura, Yasuhiro Baba, and Reira Hara

Purpose: To assess the core temperature fluctuations during 10-km open-water swimming (OWS) in cool water and the relationship between thermal sensation (TS) after 10-km OWS, core temperature, and local skin thermal sensitivity. Methods: Nine highly trained OWS swimmers (4 female; age 22 [3] y) completed a single 10-km trial in cool water (22.3 °C) wearing swimsuits for OWS. During the trial, core temperature was continuously recorded via ingestible temperature sensors, and TS after trial was also measured. Then, local skin warm/cool sensitivity was measured in the forearm. Results: All swimmers completed the 10-km OWS. Mean swimming speed for males and females were 1.39 (1.37–1.42 m/s) and 1.33 m/s (1.29–1.38 m/s), respectively. Core temperature increased in 8 out of 9 swimmers during 10-km OWS (P = .047), with an average increase of 0.8 °C. TS after 10-km OWS varied among swimmers. There were no correlations between post-OWS TS and post-OWS core temperature (P = .9333), whereas there was a negative correlation between post-OWS TS and local skin cool sensitivity (P = .0056). Conclusion: These results suggest that core temperature in elite swimmers might not decrease during 10-km OWS in the cool water temperature of official OWS. In addition, individual differences in TS after 10-km OWS may be related to skin cool sensitivity rather than core temperature.

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Erratum. Match Running Performance in Australian Football Is Related to Muscle Fiber Typology

International Journal of Sports Physiology and Performance

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Performance Management in Elite Football: A Teamwork Modeling Approach

Joao Marques and Karim Chamari

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The Force–Velocity Profiling Concept for Sprint Running Is a Dead End

Gertjan Ettema

Purpose: In this commentary, I present arguments against the use of the force–velocity profiling concept in design and adaptations of training programs targeting sprinting. The purpose of this commentary is to make sports practitioners more aware of the rationale behind the concept and explain why it does not work. Rationale: Force–velocity profiling is a mathematical way to present the velocity development during sprint behavior. Some details of this behavior may be accentuated by transforming it to other variables, but it does not add any new information about sprint performance. Thus, contrary to what is often claimed, the force–velocity profile does not represent maximal capacities (ability of force and velocity generation) of the athlete. It is claimed that through force–velocity profiling one may identify the optimal ratio of force and velocity capacities. Furthermore, proponents of the force–velocity profiling concept suggest that through directed training force and velocity capacities can be altered (inversely dependent) to obtain this optimal ratio, without changing the capacity to express power. Fundamentally, this idea is unfounded and implausible. Conclusion: At best, force–velocity profiling may be able to identify between-athletes differences. However, these can be more easily deduced directly from performance time traces.

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Six Weeks of Unilateral Flywheel Hip-Extension and Leg-Curl Training Improves Flywheel Eccentric Peak Power but Does Not Enhance Hamstring Isokinetic or Isometric Strength

Kevin L. de Keijzer, Stuart A. McErlain-Naylor, and Marco Beato

Purpose: This preregistered trial investigated how 6 weeks of unilateral flywheel leg-curl and hip-extension training impact isokinetic, isometric, and flywheel strength and power outcomes. Methods: The study involved 11 male university athletes (age 22 [2] y; body mass 77.2 [11.3] kg; height 1.74 [0.09] m) with one leg randomly allocated to flywheel training and one leg to control. Unilateral eccentric and isometric knee-flexion torque and flywheel unilateral leg-curl and hip-extension peak power were tested. Training intensity and volume (3–4 sets of 6 + 2 repetitions) were progressively increased. Results: The intervention enhanced hip-extension concentric (P < .01, d = 1.76, large) and eccentric (P < .01, d = 1.33, large) peak power more than the control (significant interaction effect). Similarly, eccentric (P = .023, d = 1.05, moderate) peak power was enhanced for the leg curl. No statistically significant differences between conditions were found for isokinetic eccentric (P = .086, d = 0.77, moderate) and isometric (P = .431, d = 0.36, small) knee-flexor strength or leg-curl concentric peak power (P = .339, d = 0.52, small). Statistical parametric mapping analysis of torque–angle curves also revealed no significant (P > .05) time–limb interaction effect at any joint angle. Conclusion: Unilateral flywheel hamstring training improved knee-flexor eccentric peak power during unilateral flywheel exercise but not flywheel concentric, isokinetic eccentric, or isometric (long-lever) knee-flexor strength.

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Annual Volume and Distribution of Physical Training in Norwegian Female Cross-Country Skiers and Biathletes: A Comparison Between Sports, Competition Levels, and Age Categories—The FENDURA Project

John O. Osborne, Guro S. Solli, Tina P. Engseth, Boye Welde, Bente Morseth, Dionne A. Noordhof, Øyvind Sandbakk, and Erik P. Andersson

Purpose: To describe and compare the annual physical training characteristics between Norwegian female cross-country (XC) skiers and biathletes across competition levels and age categories. Methods: Daily training sessions for 1 year were recorded for 45 XC skiers and 26 biathletes, comprising international/national team (inter[national]) and nonnational/regional team members (nonnational) of both junior and senior age. Endurance, strength, flexibility, speed, and power training sessions were recorded. Data included exercise modality, intensity, and duration. Data were analyzed using linear mixed-effects models. Results: The total annual physical training volume consisted of ∼90% endurance training for both groups, although XC skiers had significantly higher total volumes (∼10%; P = .003; d = 0.78) than biathletes. Senior XC skiers performed more training hours of skiing and/or roller skiing compared with biathletes over the season. However, biathletes compensated for this lower volume by more skating and a higher proportion of endurance training as skiing (81% [17%]) compared with XC skiers (68% [16%]; P < .001; d = 0.94). Overall, (inter)national-level athletes completed a higher annual training volume than non-national-level athletes (740 [90] h vs 649 [95] h; P = .004;d = 0.81). Although juniors reported less endurance volume than seniors, they maintained a relatively stable level of endurance training across the preparatory and competition period, unlike senior athletes. Conclusions: The higher annual physical training volume by XC skiers compared with biathletes is likely caused by the different demands of the 2 sports; XC skiing necessitates training for 2 skiing styles, while biathlon requires additional shooting practice. However, biathletes compensate with a higher proportion of ski training, particularly in the skating technique.

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Four Sessions of Repeated-Sprint Cycling Training With or Without Severe Hypoxia Do Not Modify Overground Running Sprint Force–Velocity Profile

Franck Brocherie, Sebastien Racinais, Anthony Couderc, Julien Piscione, and Olivier Girard

Purpose: To investigate the effect of cycling-based repeated-sprint training in hypoxia versus in normoxia on single overground running sprint performance and associated force–velocity (F–V) profile in world-class female rugby sevens players. Methods: Eighteen world-class female rugby sevens players were randomly assigned to repeated-sprint cycling training in normobaric hypoxia (n = 9) or normoxia (n = 9) groups. Training consisted of 4 sessions of repeated-sprint cycling training in normobaric hypoxia or in normoxia (4 × 5 × 5-s cycle sprints—25-s intersprint recovery performed in simulated altitude of ∼5000 m or in normoxia with 3-min interset rest in normoxia for both groups) in addition to rugby sevens training and strength and conditioning sessions within a 9-day intervention period before an international competition. Before and 1 day after the intervention, single 50-m overground running “all-out” sprint performance and associated F–V-related mechanical output were assessed. Results: No interaction (group × time; all P > .088), time effect (before vs 1 d after; all P > .296), or group effect (repeated-sprint cycling training in normobaric hypoxia vs in normoxia; all P > .325) was detected for 50-m overground running sprint performance and any derived F–V profiling variables. Conclusions: Four sessions of repeated-sprint training either in hypoxia or in normoxia performed over 9 days had no influence on single 50-m overground running sprint performance and associated F–V profile. In world-class female rugby sevens players, the intervention (training camp before an international competition) might have been too short to induce measurable changes. It is also plausible that implementing a similar program in players with likely different F–V profile may result in negligible mechanical effect.

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Match Running Performance in Australian Football Is Related to Muscle Fiber Typology

Henry J. Hopwood, Phillip M. Bellinger, Heidi R. Compton, Matthew N. Bourne, Wim Derave, Eline Lievens, Ben Kennedy, and Clare L. Minahan

Purpose: To examine the association between muscle fiber typology and match running performance in professional Australian football (AF) athletes. Methods: An observational time–motion analysis was performed on 23 professional AF athletes during 224 games throughout the 2020 competitive season. Athletes were categorized by position as hybrid, small, or tall. Athlete running performance was measured using Global Navigation Satellite System devices. Mean total match running performance and maximal mean intensity values were calculated for moving mean durations between 1 and 10 minutes for speed (in meters per minute), high-speed-running distance (HSR, >4.17 m·s−1), and acceleration (in meters per second squared), while intercept and slopes were calculated using power law. Carnosine content was quantified by proton magnetic resonance spectroscopy in the gastrocnemius and soleus and expressed as a carnosine aggregate z score (CAZ score) to estimate muscle fiber typology. Mixed linear models were used to determine the association between CAZ score and running performance. Results: The mean (range) CAZ score was −0.60 (−1.89 to 1.25), indicating that most athletes possessed a greater estimated proportion of type I muscle fibers. A greater estimated proportion of type I fibers (ie, lower CAZ score) was associated with a larger accumulation of HSR (>4.17 m·s−1) and an increased ability to maintain HSR as the peak period duration increased. Conclusion: AF athletes with a greater estimated proportion of type I muscle fibers were associated with a greater capacity to accumulate distance running at high speeds, as well as a greater capacity to maintain higher output of HSR running during peak periods as duration increases.

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Accuracy of Heart-Rate-Recovery Parameters Assessed From a Wrist-Worn Photoplethysmography Monitor (Polar Unite)

Quentin Bretonneau, Etienne Peruque-Gayou, Etienne Wolfs, and Laurent Bosquet

Purpose: The accuracy of heart rate (HR) measured with a wrist-worn photoplethysmography (PPG) monitor is altered during rest–exercise and exercise–rest transitions, which questions the validity of postexercise HR-recovery (HRR) parameters estimated from this device. Methods: Thirty participants (50% female) randomly performed two 13-minute sequences (3′ rest, 5′ submaximal-intensity exercise, and 5′ passive recovery) on treadmill and bicycle ergometers. HR was measured concomitantly with a 10-lead electrocardiogram (ECG) and a wrist-worn PPG monitor (Polar Unite). HRR was assessed by calculating Δ60 (the difference between HR during exercise and HR 60 s after exercise cessation) and by fitting HRR data into a monoexponential model. Results: By focusing on Δ60 and τ (the time constant of the monoexponential curve), levels of association (r) of the Unite versus the 10-lead ECG were high to very high (.73 < r < .93), and coefficients of variation were >20% (in absolute value), except for Δ60 in the bicycle ergometer condition (11.7%). In 97% of cases, the decrease in HR after exercise appeared later with the Unite. By adjusting the time window used for the analysis according to this time lag, coefficients of variation of Δ60 decreased below 10% in the bicycle ergometer condition. Conclusions: If a wrist-worn PPG monitor is used to assess HRR, we recommend performing the submaximal-intensity exercise on a bicycle ergometer and focusing on Δ60. Furthermore, to obtain a more accurate Δ60, the time lag between the end of the exercise and the effective decrease in HR should also be considered before the calculation.

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Remote Determination of Critical Speed and Critical Power in Recreational Runners

Ben Hunter, Adam Ledger, and Daniel Muniz-Pumares

Purpose: This study aimed to compare estimations of critical speed (CS) and work completed above CS (D′), and their analogies for running power (critical power [CP] and W′), derived from raw data obtained from habitual training (HAB) and intentional maximal efforts in the form of time trials (TTs) and 3-minute all-out tests (3MTs) in recreational runners. The test–retest reliability of the 3MT was further analyzed. Methods: Twenty-three recreational runners (4 female) used a foot pod to record speed, altitude, and power output for 8 consecutive weeks. CS and D′, and CP and W′, were calculated from the best 3-, 7-, and 12-minute segments recorded in the first 6 weeks of their HAB and in random order in weeks 7 and 8 from 3 TTs (3, 7, and 12 min) and three 3MTs (to assess test–retest reliability). Results: There was no difference between estimations of CS or CP derived from HAB, TT, and 3MT (3.44 [0.63], 3.42 [0.53], and 3.76 [0.57] m · s−1 and 281 [41], 290 [45], and 305 [54] W, respectively), and strong agreement between HAB and TT for CS (r = .669) and CP (r = .916). Limited agreement existed between estimates of D′/W′. Moderate reliability of D′/W′ was demonstrated between the first and second 3MTs, whereas excellent reliability was demonstrated for CS/CP. Conclusion: These data suggest that estimations of CS/CP can be derived remotely, from either HAB, TT, or 3MT, although the lower agreement between D′/W′ warrants caution when using these measures interchangeably.