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Alistair P. Murphy, Rob Duffield, Aaron Kellett, Dani Gescheit and Machar Reid

Purpose:

Difficulties in preserving physical capacities while on tennis tours necessitate targeted training prescription. This study analyzed training and match loads performed before and on tour for their relationship with posttour physical-capacity changes. A secondary aim was to determine whether the presence of a strength and conditioning (S&C) coach affected the type and volume of on-tour training load.

Methods:

The training and match loads of 30 high-performance junior tennis players were recorded over 8 wk: 4 wk before and 4 wk during an international tour. Fitness tests were conducted pretour and posttour, including double and single-leg (dominant and nondominant) countermovement jump, speed (5, 10, and 20 m), modified 5-0-5 agility, 10 × 20-m repeated-sprint ability, and multistage fitness tests. Tour training and match loads were categorized according to whether S&C support was present or absent.

Results:

Total and tennis training loads were significantly greater on tour than pretour (P ≤ .05, d > 0.8). Increases in on-tour, on-court training loads were moderately correlated with decrements in speed and aerobic power (r = .31-.52). Finally, S&C presence on tour significantly increased total, on-court, and off-court training load completed (P ≤ .05, d > 0.8).

Conclusions:

Training loads should be carefully prescribed to ensure that sufficient total and tennis loads are completed pretour. Specifically, speed and aerobic capacities may regress with increased training on tour. Finally, a practical observation was that on-tour S&C support resulted in increased S&C training load (around match loads), potentially countering the observed regression of physical capacities. Such a finding has the capacity to alter current physical-preparation structures in high-performance tennis environments with finite resources.

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Sarah Kölling, Rob Duffield, Daniel Erlacher, Ranel Venter and Shona L. Halson

The body of research that reports the relevance of sleep in high-performance sports is growing steadily. While the identification of sleep cycles and diagnosis of sleep disorders are limited to lab-based assessment via polysomnography, the development of activity-based devices estimating sleep patterns provides greater insight into the sleep behavior of athletes in ecological settings. Generally, small sleep quantity and/or poor quality appears to exist in many athletic populations, although this may be related to training and competition context. Typical sleep-affecting factors are the scheduling of training sessions and competitions, as well as impaired sleep onset as a result of increased arousal prior to competition or due to the use of electronic devices before bedtime. Further challenges are travel demands, which may be accompanied by jet-lag symptoms and disruption of sleep habits. Promotion of sleep may be approached via behavioral strategies such as sleep hygiene, extending nighttime sleep, or daytime napping. Pharmacological interventions should be limited to clinically induced treatments, as evidence among healthy and athletic populations is lacking. To optimize and manage sleep in athletes, it is recommended to implement routine sleep monitoring on an individual basis.

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Erin L. McCleave, Katie M. Slattery, Rob Duffield, Philo U. Saunders, Avish P. Sharma, Stephen Crowcroft and Aaron J. Coutts

Purpose: To determine whether combining training in heat with “Live High, Train Low” hypoxia (LHTL) further improves thermoregulatory and cardiovascular responses to a heat-tolerance test compared with independent heat training. Methods: A total of 25 trained runners (peak oxygen uptake = 64.1 [8.0] mL·min−1·kg−1) completed 3-wk training in 1 of 3 conditions: (1) heat training combined with “LHTL” hypoxia (H+H; FiO2 = 14.4% [3000 m], 13 h·d−1; train at <600 m, 33°C, 55% relative humidity [RH]), (2) heat training (HOT; live and train <600 m, 33°C, 55% RH), and (3) temperate training (CONT; live and train <600 m, 13°C, 55% RH). Heat adaptations were determined from a 45-min heat-response test (33°C, 55% RH, 65% velocity corresponding to the peak oxygen uptake) at baseline and immediately and 1 and 3 wk postexposure (baseline, post, 1 wkP, and 3 wkP, respectively). Core temperature, heart rate, sweat rate, sodium concentration, plasma volume, and perceptual responses were analyzed using magnitude-based inferences. Results: Submaximal heart rate (effect size [ES] = −0.60 [−0.89; −0.32]) and core temperature (ES = −0.55 [−0.99; −0.10]) were reduced in HOT until 1 wkP. Sweat rate (ES = 0.36 [0.12; 0.59]) and sweat sodium concentration (ES = −0.82 [−1.48; −0.16]) were, respectively, increased and decreased until 3 wkP in HOT. Submaximal heart rate (ES = −0.38 [−0.85; 0.08]) was likely reduced in H+H at 3 wkP, whereas CONT had unclear physiological changes. Perceived exertion and thermal sensation were reduced across all groups. Conclusions: Despite greater physiological stress from combined heat training and “LHTL” hypoxia, thermoregulatory adaptations are limited in comparison with independent heat training. The combined stimuli provide no additional physiological benefit during exercise in hot environments.

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Penelope S. Larsen, Cheyne E. Donges, Kym J. Guelfi, Greg C. Smith, David R. Adams and Rob Duffield

Aerobic exercise (AE) and strength exercise (SE) are reported to induce discrete and specific appetite-related responses; however, the effect of combining AE and SE (i.e., combined exercise; CE) remains relatively unknown. Twelve inactive overweight men (age: 48 ± 5 y; BMI: 29.9 ± 1.9 kg∙m2) completed four conditions in a random order: 1) nonexercise control (CON) (50 min seated rest); 2) AE (50 min cycling; 75% VO2peak); 3) SE (10 × 8 leg extensions; 75% 1RM); and 4) CE (50% SE + 50% AE). Perceived appetite, and appetiterelated peptides and metabolites were assessed before and up to 2 h postcondition (0P, 30P, 60P, 90P, 120P). Perceived appetite did not differ between trials (p < .05). Acylated ghrelin was lower at 0P in AE compared with CON (p = .039), while pancreatic polypeptide (PP) was elevated following AE compared with CON and CE. Glucose-dependent insulinotropic peptide (GIPtotal) was greater following all exercise conditions compared with CON, as was glucagon, although concentrations were generally highest in AE (p < .05). Glucose was acutely increased with SE and AE (p < .05), while insulin and C-peptide were higher after SE compared with all other conditions (p < .05). In inactive, middle-aged men AE, SE and CE each have their own distinct effects on circulating appetite-related peptides and metabolites. Despite these differential exercise-induced hormone responses, exercise mode appears to have little effect on perceived appetite compared with a resting control in this population.

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Carolina F. Wilke, Felipe Augusto P. Fernandes, Flávio Vinícius C. Martins, Anísio M. Lacerda, Fabio Y. Nakamura, Samuel P. Wanner and Rob Duffield

Purpose : To investigate the existence of faster vs slower recovery profiles in futsal and factors distinguishing them. Methods: 22 male futsal players were evaluated in countermovement jump, 10-m sprint, creatine kinase, total quality of recovery (TQR), and Brunel Mood Scale (fatigue and vigor) before and immediately and 3, 24, and 48 h posttraining. Hierarchical cluster analysis allocated players to different recovery profiles using the area under the curve (AUC) of the percentage differences from baseline. One-way ANOVA compared the time course of each variable and players’ characteristics between clusters. Results : Three clusters were identified and labeled faster recovery (FR), slower physiological recovery (SLphy), and slower perceptual recovery (SLperc). FR presented better AUC in 10-m sprint than SLphy (P = .001) and SLperc (P = .008), as well as better TQR SLphy (P = .018) and SLperc (P = .026). SLperc showed better AUC in countermovement jump than SLphy (P = .014) but presented worse fatigue AUC than SLphy (P = .014) and FR (P = .008). AUC of creatine kinase was worse in SLphy than in FR (P = .001) and SLperc (P < .001). The SLphy players were younger than SLperc players (P = .027), whereas FR were slower 10-m sprinters than SLphy players (P = .003) and SLperc (P = .013) and tended to have higher maximal oxygen consumption than SLphy (effect size =1.13). Conclusion : Different posttraining recovery profiles exist in futsal players, possibly influenced by their physical abilities and age/experience.

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Michael Kellmann, Maurizio Bertollo, Laurent Bosquet, Michel Brink, Aaron J. Coutts, Rob Duffield, Daniel Erlacher, Shona L. Halson, Anne Hecksteden, Jahan Heidari, K. Wolfgang Kallus, Romain Meeusen, Iñigo Mujika, Claudio Robazza, Sabrina Skorski, Ranel Venter and Jürgen Beckmann

The relationship between recovery and fatigue and its impact on performance has attracted the interest of sport science for many years. An adequate balance between stress (training and competition load, other life demands) and recovery is essential for athletes to achieve continuous high-level performance. Research has focused on the examination of physiological and psychological recovery strategies to compensate external and internal training and competition loads. A systematic monitoring of recovery and the subsequent implementation of recovery routines aims at maximizing performance and preventing negative developments such as underrecovery, nonfunctional overreaching, the overtraining syndrome, injuries, or illnesses. Due to the inter- and intraindividual variability of responses to training, competition, and recovery strategies, a diverse set of expertise is required to address the multifaceted phenomena of recovery, performance, and their interactions to transfer knowledge from sport science to sport practice. For this purpose, a symposium on Recovery and Performance was organized at the Technical University Munich Science and Study Center Raitenhaslach (Germany) in September 2016. Various international experts from many disciplines and research areas gathered to discuss and share their knowledge of recovery for performance enhancement in a variety of settings. The results of this meeting are outlined in this consensus statement that provides central definitions, theoretical frameworks, and practical implications as a synopsis of the current knowledge of recovery and performance. While our understanding of the complex relationship between recovery and performance has significantly increased through research, some important issues for future investigations are also elaborated.

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Jessica M. Stephens, Ken Sharpe, Christopher Gore, Joanna Miller, Gary J. Slater, Nathan Versey, Jeremiah Peiffer, Rob Duffield, Geoffrey M. Minett, David Crampton, Alan Dunne, Christopher D. Askew and Shona L. Halson

Purpose: To examine the effect of postexercise cold-water immersion (CWI) protocols, compared with control (CON), on the magnitude and time course of core temperature (T c) responses. Methods: Pooled-data analyses were used to examine the T c responses of 157 subjects from previous postexercise CWI trials in the authors’ laboratories. CWI protocols varied with different combinations of temperature, duration, immersion depth, and mode (continuous vs intermittent). T c was examined as a double difference (ΔΔT c), calculated as the change in T c in CWI condition minus the corresponding change in CON. The effect of CWI on ΔΔT c was assessed using separate linear mixed models across 2 time components (component 1, immersion; component 2, postintervention). Results: Intermittent CWI resulted in a mean decrease in ΔΔT c that was 0.25°C (0.10°C) (estimate [SE]) greater than continuous CWI during the immersion component (P = .02). There was a significant effect of CWI temperature during the immersion component (P = .05), where reductions in water temperature of 1°C resulted in decreases in ΔΔT c of 0.03°C (0.01°C). Similarly, the effect of CWI duration was significant during the immersion component (P = .01), where every 1 min of immersion resulted in a decrease in ΔΔT c of 0.02°C (0.01°C). The peak difference in T c between the CWI and CON interventions during the postimmersion component occurred at 60 min postintervention. Conclusions: Variations in CWI mode, duration, and temperature may have a significant effect on the extent of change in T c. Careful consideration should be given to determine the optimal amount of core cooling before deciding which combination of protocol factors to prescribe.