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Stephen Crowcroft, Katie Slattery, Erin McCleave and Aaron J. Coutts

Purpose: To assess a coach’s subjective assessment of their athletes’ performances and whether the use of athlete-monitoring tools could improve on the coach’s prediction to identify performance changes. Methods: Eight highly trained swimmers (7 male and 1 female, age 21.6 [2.0] y) recorded perceived fatigue, total quality recovery, and heart-rate variability over a 9-month period. Prior to each race of the swimmers’ main 2 events, the coach (n = 1) was presented with their previous race results and asked to predict their race time. All race results (n = 93) with aligning coach’s predictions were recorded and classified as a dichotomous outcome (0 = no change; 1 = performance decrement or improvement [change +/− > or < smallest meaningful change]). A generalized estimating equation was used to assess the coach’s accuracy and the contribution of monitoring variables to the model fit. The probability from generalized estimating equation models was assessed with receiver operating characteristic curves to identify the model’s accuracy from the area under the curve analysis. Results: The coach’s predictions had the highest diagnostic accuracy to identify both decrements (area under the curve: 0.93; 95% confidence interval, 0.88–0.99) and improvements (area under the curve: 0.89; 95% confidence interval, 0.83–0.96) in performance. Conclusions: These findings highlight the high accuracy of a coach’s subjective assessment of performance. Furthermore, the findings provide a future benchmark for athlete-monitoring systems to be able to improve on a coach’s existing understanding of swimming performance.

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Stephen Crowcroft, Erin McCleave, Katie Slattery and Aaron J. Coutts


To assess measurement sensitivity and diagnostic characteristics of athlete-monitoring tools to identify performance change.


Fourteen nationally competitive swimmers (11 male, 3 female; age 21.2 ± 3.2 y) recorded daily monitoring over 15 mo. The self-report group (n = 7) reported general health, energy levels, motivation, stress, recovery, soreness, and wellness. The combined group (n = 7) recorded sleep quality, perceived fatigue, total quality recovery (TQR), and heart-rate variability. The week-to-week change in mean weekly values was presented as coefficient of variance (CV%). Reliability was assessed on 3 occasions and expressed as the typical error CV%. Week-to-week change was divided by the reliability of each measure to calculate the signal-to-noise ratio. The diagnostic characteristics for both groups were assessed with receiver-operating-curve analysis, where area under the curve (AUC), Youden index, sensitivity, and specificity of measures were reported. A minimum AUC of .70 and lower confidence interval (CI) >.50 classified a “good” diagnostic tool to assess performance change.


Week-to-week variability was greater than reliability for soreness (3.1), general health (3.0), wellness% (2.0), motivation (1.6), sleep (2.6), TQR (1.8), fatigue (1.4), R-R interval (2.5), and LnRMSSD:RR (1.3). Only general health was a “good” diagnostic tool to assess decreased performance (AUC –.70, 95% CI, .61–.80).


Many monitoring variables are sensitive to changes in fitness and fatigue. However, no single monitoring variable could discriminate performance change. As such the use of a multidimensional system that may be able to better account for variations in fitness and fatigue should be considered.

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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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Erin L. McCleave, Katie M. Slattery, Rob Duffield, Stephen Crowcroft, Chris R. Abbiss, Lee K. Wallace and Aaron J. Coutts

Purpose: To examine whether concurrent heat and intermittent hypoxic training can improve endurance performance and physiological responses relative to independent heat or temperate interval training. Methods: Well-trained male cyclists (N = 29) completed 3 weeks of moderate- to high-intensity interval training (4 × 60 min·wk−1) in 1 of 3 conditions: (1) heat (HOT: 32°C, 50% relative humidity, 20.8% fraction of inspired oxygen, (2) heat + hypoxia (H+H: 32°C, 50% relative humidity, 16.2% fraction of inspired oxygen), or (3) temperate environment (CONT: 22°C, 50% relative humidity, 20.8% fraction of inspired oxygen). Performance 20-km time trials (TTs) were conducted in both temperate (TTtemperate) and assigned condition (TTenvironment) before (base), immediately after (mid), and after a 3-week taper (end). Measures of hemoglobin mass, plasma volume, and blood volume were also assessed. Results: There was improved 20-km TT performance to a similar extent across all groups in both TTtemperate (mean ±90% confidence interval HOT, −2.8% ±1.8%; H+H, −2.0% ±1.5%; CONT, −2.0% ±1.8%) and TTenvironment (HOT, −3.3% ±1.7%; H+H, −3.1% ±1.6%; CONT, −3.2% ±1.1%). Plasma volume (HOT, 3.8% ±4.7%; H+H, 3.3% ±4.7%) and blood volume (HOT, 3.0% ±4.1%; H+H, 4.6% ±3.9%) were both increased at mid in HOT and H+H over CONT. Increased hemoglobin mass was observed in H+H only (3.0% ±1.8%). Conclusion: Three weeks of interval training in heat, concurrent heat and hypoxia, or temperate environments improve 20-km TT performance to the same extent. Despite indications of physiological adaptations, the addition of independent heat or concurrent heat and hypoxia provided no greater performance benefits in a temperate environment than temperate training alone.

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Peter M. Fowler, Wade Knez, Heidi R. Thornton, Charli Sargent, Amy E. Mendham, Stephen Crowcroft, Joanna Miller, Shona Halson and Rob Duffield

Purpose: To assess the efficacy of a combined light exposure and sleep hygiene intervention to improve team-sport performance following eastward long-haul transmeridian travel. Methods: Twenty physically trained males underwent testing at 09:00 and 17:00 hours local time on 4 consecutive days at home (baseline) and the first 4 days following 21 hours of air travel east across 8 time zones. In a randomized, matched-pairs design, participants traveled with (INT; n = 10) or without (CON; n = 10) a light exposure and sleep hygiene intervention. Performance was assessed via countermovement jump, 20-m sprint, T test, and Yo-Yo Intermittent Recovery Level 1 tests, together with perceptual measures of jet lag, fatigue, mood, and motivation. Sleep was measured using wrist activity monitors in conjunction with self-report diaries. Results: Magnitude-based inference and standardized effect-size analysis indicated there was a very likely improvement in the mean change in countermovement jump peak power (effect size 1.10, ±0.55), and likely improvement in 5-m (0.54, ±0.67) and 20-m (0.74, ±0.71) sprint time in INT compared with CON across the 4 days posttravel. Sleep duration was most likely greater in INT both during travel (1.61, ±0.82) and across the 4 nights following travel (1.28, ±0.58) compared with CON. Finally, perceived mood and motivation were likely worse (0.73, ±0.88 and 0.63, ±0.87) across the 4 days posttravel in CON compared with INT. Conclusions: Combined light exposure and sleep hygiene improved speed and power but not intermittent-sprint performance up to 96 hours following long-haul transmeridian travel. The reduction of sleep disruption during and following travel is a likely contributor to improved performance.