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Purpose: To examine the construct validity and reliability of 2 single items for fatigue and recovery in dancers. The construct validity was assessed using reference instruments: the fatigue items of the Brunel Mood Scale (BRUMS) and the Short Recovery and Stress Scale (SRSS). A secondary aim was to explore the respondent interpretation of these 2 items using a concept identification approach. Methods: Two hundred forty-three (N = 243) dancers completed single-item fatigue and recovery (unipolar and bipolar), BRUMS, and SRSS once for construct validity. For reliability, 49 dancers completed the questionnaires twice, 1 week apart. Using a concept identification approach, 49 dancers were also asked comprehension and interpretation of fatigue and recovery. Results: The fatigue item correlated with SRSS stress items (rs =.37–.51) and BRUMs fatigue items (rs =.63–.66). The recovery item was only partially confirmed in terms of construct validity, when using the SRSS recovery items as reference (rs =.39–.43). Reliability was confirmed for the single items of fatigue (κ =.77–.78) and recovery (κ =.71–.78). Main responses for the concept of fatigue were tiredness (34.7%), muscle soreness (17.3%), and energy (13.0%). Main responses for the concept of recovery were muscle soreness (43.0%), tiredness (27.9%), and fatigue (24.0%). Conclusion: We provide preliminary confirmation of the validity and reliability of the single item fatigue in dancers. The recovery item was only partially confirmed in terms of construct validity, when using the SRSS recovery items as reference, but did display acceptable reliability and agreement. Further research is warranted further exploring other measurement properties. [ABSTRACT FROM AUTHOR]

Purpose: To describe the physiological (resting core temperature, exercising heart rate, and sweat rate) and psychophysical (rating of perceived exertion, thermal sensation, and thermal comfort) responses to a short-term heat acclimatization (HA) training camp in elite female rugby sevens athletes. Methods: Nineteen professional female rugby sevens athletes participated in a 5-day HA camp in Darwin, Australia (training average: 32.2°C and 58% relative humidity). Training involved normal team practice prescribed by appropriate staff. Markers of physiological and psychophysical adaptations to HA were collected at various stages during the camp. Partial eta-squared effect sizes (from linear mixed-effects models), rank-biserial correlations (from Freidman tests), and P values were used to assess changes across the protocol. Results: Resting core temperature did not significantly change. Exercising heart rate showed a large and significant reduction from day 1 to day 5 (175 [13] vs 171 [12] beats·min−1), as did sweat rate (1.1 [0.3] vs 1.0 [0.2] L·h–1). Thermal sensation showed a large and significant reduction between day 1 and day 5 (median [interquartile range] = 5 [5–5.5] vs 4.5 [4–5]). Changes in rating of perceived exertion and thermal comfort were unclear. Conclusions: Beneficial cardiovascular adaptations were observed simultaneously across a full squad of elite female rugby sevens players (without expensive facilities/equipment or modifying training content). However, beneficial changes in resting core temperature, sweat rate, and thermal/effort perceptions likely require a greater thermal impulse. These data contribute to the development of evidence-informed practice for minimal effective HA doses in female team-sport athletes, who are underrepresented in the current research. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to independently validate a wearable inertial sensor designed to monitor training and performance metrics in swimmers. Methods: A total of 4 male (21 [4] y, 1 national and 3 international) and 6 female (22 [3] y, 1 national and 5 international) swimmers completed 15 training sessions in an outdoor 50-m pool. Swimmers were fitted with a wearable device (TritonWear, 9-axis inertial measurement unit with triaxial accelerometer, gyroscope, and magnetometer), placed under the swim cap on top of the occipital protuberance. Video footage was captured for each session to establish criterion values. Absolute error, standardized effect, and Pearson correlation coefficient were used to determine the validity of the wearable device against video footage for total swim distance, total stroke count, mean stroke count, and mean velocity. A Fisher exact test was used to analyze the accuracy of stroke-type identification. Results: Total swim distance was underestimated by the device relative to video analysis. Absolute error was consistently higher for total and mean stroke count, and mean velocity, relative to video analysis. Across all sessions, the device incorrectly detected total time spent in backstroke, breaststroke, butterfly, and freestyle by 51% (15%). The device did not detect time spent in drill. Intraclass correlation coefficient results demonstrated excellent intrarater reliability between repeated measures across all swimming metrics. Conclusions: The wearable device investigated in this study does not accurately measure distance, stroke count, and velocity swimming metrics or detect stroke type. Its use as a training monitoring tool in swimming is limited. [ABSTRACT FROM AUTHOR]

Purpose: To determine the effect of wearing a phase-change cooling vest in elite female rugby sevens athletes during (1) a simulated match-day warm-up in hot conditions prior to a training session and (2) a prematch warm-up during a tournament in cool conditions. Methods: This study consisted of 2 randomized independent group designs (separated by 16 d) where athletes completed the same 23- to 25-minute match-day warm-up (1) in hot conditions (range = 28.0°C to 35.1°C wet bulb globe temperature [WBGT]) prior to training and (2) in cool conditions (range = 18.8°C to 20.1°C WBGT) prior to a World Rugby Women's Sevens Series match. In both conditions, athletes were randomly assigned to wearing either (1) the standardized training/playing ensemble (synthetic rugby shorts and training tee/jersey) or (2) the standardized training/playing ensemble plus a commercial phase-change athletic cooling vest. Group-wise differences in core temperature rise from baseline, global positioning system–measured external locomotive output, and perceptual thermal load were compared. Results: Core temperature rise during a match warm-up was lower in the hot condition only (−0.65°C [95% confidence interval = −1.22°C to −0.08°C], η p 2 =.23 [95% confidence interval =.00 to.51], P =.028). No differences in various external-load variables were observed. Conclusions: Phase-change cooling vests can be worn by athletes prior to, and during, a prematch warm-up in hot conditions to limit excess core temperature rise without adverse effects on thermal perceptions or external locomotion output. [ABSTRACT FROM AUTHOR]

Purpose: To determine whether elite female rugby sevens players are exposed to core temperatures (Tc) during training in the heat that replicate the temperate match demands previously reported and to investigate whether additional clothing worn during a hot training session meaningfully increases the heat load experienced. Methods: A randomized parallel-group study design was employed, with all players completing the same approximately 70-minute training session (27.5°C–34.8°C wet bulb globe temperature) and wearing a standardized training ensemble (synthetic rugby shorts and training tee [control (CON); n = 8]) or additional clothing (standardized training ensemble plus compression garments and full tracksuit [additional clothing (AC); n = 6]). Groupwise differences in Tc, sweat rate, GPS-measured external locomotive output, rating of perceived exertion, and perceptual thermal load were compared. Results: Mean (P =.006, η p 2 =.88) and peak (P <.001, η p 2 =.97) Tc were higher in AC compared with CON during the training session. There were no differences in external load (F4,9 = 0.155, P =.956, Wilks Λ = 0.935, η p 2 =.06) or sweat rate (P =.054, Cohen d = 1.09). A higher rating of perceived exertion (P =.016, Cohen d = 1.49) was observed in AC compared with CON. No exertional-heat-illness symptomology was reported in either group. Conclusions: Player Tc is similar between training performed in hot environments and match play in temperate conditions when involved for >6 minutes. Additional clothing is a viable and effective method to increase heat strain in female rugby sevens players without compromising training specificity or external locomotive capacity. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the relationships between internal and external training load (TL) metrics with elite international women's basketball performance. Methods: Sessional ratings of perceived exertion, PlayerLoad™/minute, and training duration were collected from 13 elite international-level female basketball athletes (age 29.0 [3.7] y, stature 186.0 [9.8] cm, body mass 77.9 [11.6] kg) during the 18 weeks prior to the International Basketball Federation Olympic qualifying event for the 2016 Rio Olympic Games. Training stress balance, differential load, and the training efficiency index were calculated with 3 different smoothing methods. These TL metrics and their change in the last 21 days prior to competition were examined for their relationship to competition performance as coach ratings of performance. Results: For a number of TL variables, there were consistent significant small to moderate correlations with performance and significant small to large differences between successful and unsuccessful performances. However, these differences were only evident for external TL when using exponentially weighted moving averages to calculate TL. The variable that seemed most sensitive to performance was the change in training efficiency index in the last 21 days prior to competition (performance r =.47–.56, P <.001 and difference between successful and unsuccessful performance P <.001, f2 = 0.305–0.431). Conclusions: Internal and external TL variables were correlated with performance and distinguished between successful and unsuccessful performances among the same players during international women's basketball games. Manipulating TL in the last 3 weeks prior to competition may be worthwhile for basketball players' performance, especially in internal TL. [ABSTRACT FROM AUTHOR]

Purpose: To apply data reduction methods to athlete-monitoring measures to address the issue of data overload for practitioners of professional Australian football teams. Methods: Data were collected from 45 professional Australian footballers from 1 club during the 2018 Australian Football League season. External load was measured in training and matches by 10-Hz OptimEye S5 and ClearSky T6 GPS units. Internal load was measured via the session rate of perceived exertion method. Perceptual wellness was measured via questionnaires completed before training sessions with players providing a rating (1–5 Likert scale) of muscle soreness, sleep quality, fatigue, stress, and motivation. Percentage of maximum speed was calculated relative to individual maximum velocity recorded during preseason testing. Derivative external training load measures (total daily, weekly, and monthly) were calculated. Principal-component analyses (PCAs) were conducted for Daily and Chronic measures, and components were identified via scree plot inspection (eigenvalue > 1). Components underwent orthogonal rotation with a factor loading redundancy threshold of 0.70. Results: The Daily PCA identified components representing external load, perceived wellness, and internal load. The Chronic PCA identified components representing 28-d speed exposure, 28-d external load, 7-d external load, and 28-d internal load. Perceived soreness did not meet the redundancy threshold. Conclusions: Monitoring player exposure to maximum speed is more appropriate over chronic than short time frames to capture variations in between-matches training-cycle duration. Perceived soreness represents a distinct element of a player's perception of wellness. Summed-variable and single-variable approaches are novel methods of data reduction following PCA of athlete monitoring data. [ABSTRACT FROM AUTHOR]

Purpose: To provide details on the nature and symptomatic profile of training maladaptation in competitive resistance-based athletes to examine whether there are symptoms that may be used as prognostic indicators of overtraining. Identifying prognostic tools to assess for training maladaptation is essential for avoiding severe overtraining conditions. Methods: A Web-based survey was distributed to a cross-sectional convenience sample of competitive athletes involved in sports with a significant resistance-training component. The 46-item anonymous survey was distributed via industry experts and social media from July to August 2019. Results: The final sample included 605 responses (completion rate: 84%). About 71% of the respondents indicated that they had previously experienced an unexplained decrease in performance. Among those, the majority reported a performance decrement lasting 1 wk to 1 mo (43.8%). General feelings of fatigue were the most frequent self-reported symptom of maladaptation. Acute training maladaptation, lasting <1 mo, was also accompanied by symptoms of musculoskeletal aches and pain. In the majority of cases (92.5%), training maladaptation was accompanied by additional nontraining stressors. A greater proportion of the respondents with more severe maladaptation (>4 mo) were training to muscle failure. Conclusion: The results from this study support the multifactorial nature of training maladaptation. The multidimensional nature of fatigue and individual variability in symptomatic responses precludes definitive prognostic symptoms or differential diagnostic factors of functional/nonfunctional overreaching or the overtraining syndrome in resistance exercise. [ABSTRACT FROM AUTHOR]

Purpose: To develop position-specific career performance trajectories and determine the age of peak performance of professional Australian Football players. Methods: Match performance data (Australian Football League [AFL] Player Rank) were collected for Australian Football players drafted via the AFL National Draft between 1999 and 2015 (N = 207). Players were subdivided into playing positions: forwards (n = 60; age 23 [3] y), defenders (n = 71; age 24 [4] y), midfielders (n = 58; age 24 [4] y), and ruckmen (n = 18; age 24 [3] y). Linear mixed models were fitted to the data to estimate individual career trajectories. Results: Forwards, midfielders, and defenders experienced peak match performance earlier than ruckmen (24–25 vs 27 y). Midfielders demonstrated the greatest between-subjects variability (intercept 0.580, age 0.0286) in comparison with ruckmen, who demonstrated the least variability (intercept 0.112, age 0.005) in AFL Player Rank throughout their careers. Age had the greatest influence on the career trajectory of midfielders (β [SE] = 0.226 [0.025], T = 9.10, P <.01) and the least effect on ruckmen (β [SE] = 0.114 [0.049], T = 2.30, P =.02). Conclusions: Professional Australian Football players peak in match performance between 24 and 27 years of age with age, having the greatest influence on the match performance of midfielders and the least on ruckmen. [ABSTRACT FROM AUTHOR]

Purpose: To examine the concurrent and construct validity of numerically blinded ratings of perceived exertion (RPEs). Methods: A total of 30 elite male youth soccer players (age 16.7 [0.5] y) were monitored during training and matches over a 17-wk in-season period. The players' external loads were determined via raw 10-Hz global positioning system. Heart rate (HR) was collected continuously and expressed as Bannister and Edwards training impulses, and minutes >80% of the players predetermined the maximum HR by the Yo-Yo Intermittent Recovery Test Level 1. RPE was collected confidentially 10 to 15 min after training/matches using 2 methods: (1) a traditional verbal response to the 0 to 100 category-ratio "centiMax" scale (RPE) and (2) numerically blinded RPE centiMax scale (RPEblind) with the response selected manually via a 5 × 7-in tablet "slider." The RPE and RPEblind were divided by 10 and multiplied by the duration to derive the sessional RPE. Linear mixed models compared ratings, and within-subject repeated-measures correlations assessed the sessional RPE versus HR and external load associations. Results: There were no differences between the RPE and RPEblind (0.19; 95% confidence intervals, −0.59 to 0.20 au, P =.326) or their session values (13.5; 95% confidence intervals, −17.0 to 44.0 au, P =.386), and the ratings were nearly perfectly correlated (r =.96). The associations between the sessional RPE versus HR and external load metrics were large to very large (r =.65–.81), with no differences between the RPE methods (P ≥.50). The RPEblind also reduced verbal anchor clustering and integer bias by 11% and 50%, respectively. Conclusions: RPEblind demonstrated concurrent and construct validity versus the traditional method, and may be used in situations where practitioners have concerns regarding the authenticity of athlete ratings. [ABSTRACT FROM AUTHOR]

Background: Athlete-reported outcome measures (AROMs) are frequently used in research and practice but no studies have examined their psychometric properties. Objectives: Part 1—identify the most commonly used AROMs in sport for monitoring training responses; part 2—assess risk of bias, measurement properties, and level of evidence, based on the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) guidelines. Study Appraisal and Synthesis Methods: Methodological quality of the studies, quality of measurement properties, and level of evidence were determined using the COSMIN checklist and criteria. Results: Part 1—from 9446 articles screened for title and abstract, 310 out of 334 full texts were included; 53.9% of the AROMs contained multiple items, while 46.1% contained single items. Part 2—from 1895 articles screened for title and abstract, 71 were selected. Most measurement properties of multiple-item AROMs were adequate, but content validity and measurement error were inadequate. With the exclusion of 2 studies examining reliability and responsiveness, no validity studies were found for single items. Conclusions: The measurement properties of multiple-item AROMs derived from psychometrics were acceptable (with the exclusion of content validity and measurement error). The single-item AROMs most frequently used in sport science have not been validated. Additionally, nonvalidated modified versions of the originally nonvalidated items are common. Until proper validation studies are completed, all conclusions based on these AROMs are questionable. Established reference methods, such as those of clinimetrics, should be used to develop and assess the validity of AROMs. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Purpose: To compare the metabolic cost of paddling on different commercially available kayak ergometers using a standardized kayak incremental exercise protocol. Methods: Six male sprint kayak athletes undertook an incremental exercise protocol on 3 different kayak ergometers utilizing a randomized counterbalanced pair-matched design. Results: Mean maximal aerobic power on the WEBA ergometer (265 [14] W) was significantly higher than on the Dansprint (238 [9] W) and KayakPro® (247 [21] W, P <.01, effect size [ES] = 0.80). At the fifth stage, absolute oxygen consumption on the WEBA (3.82 [0.25] L·min−1) was significantly lower (P < 0.05, ES = 0.20) than KayakPro and Dansprint (4.10 [0.28] and 4.08 [0.27] L·min−1, respectively). Blood lactate concentration response at the sixth stage was significantly lower for the WEBA (3.5 [0.8] mmol·L−1), compared with KayakPro and Dansprint (5.4 [1.2] and 5.6 [1.5] mmol·L−1, P =.012, ES = 0.20). Stroke rate was significantly higher, without any effect of pacing during the submaximal stages for the Dansprint, compared with the WEBA (P <.001, ES = 0.28) and KayakPro (P <.001, ES = 0.38). A pacing effect was present at the maximal stage for all ergometers. Conclusions: This study demonstrated that paddling on different kayak ergometers when controlling power output elicits different metabolic and work outputs. It is recommended that scientists and coaches avoid testing on different ergometers and regularly calibrate these devices. Moreover, when an ergometer has been calibrated against a first principle device, it is necessary to consider calibration of various drag settings, due to their impact on stroke rate. Further research should explore the relationship between drag settings and stroke rate. [ABSTRACT FROM AUTHOR]

The number of studies examining associations between training load and injury has increased exponentially. As a result, many new measures of exposure and training-load-based prognostic factors have been created. The acutexhronic workload ratio (ACWR) is the most popular. However, when recommending the manipulation of a prognostic factor in order to alter the likelihood of an event, one assumes a causal effect. This introduces a series of additional conceptual and methodological considerations that are problematic and should be considered. Because no studies have even tried to estimate causal effects properly, manipulating ACWR in practical settings in order to change injury rates remains a conjecture and an overinterpretation of the available data. Furthermore, there are known issues with the use of ratio data and unrecognized assumptions that negatively affect the ACWR metric for use as a causal prognostic factor. ACWR use in practical settings can lead to inappropriate recommendations, because its causal relation to injury has not been established, it is an inaccurate metric (failing to normalize the numerator by the denominator even when uncoupled), it has a lack of background rationale to support its causal role, it is an ambiguous metric, and it is not consistently and unidirectionally related to injury risk. Conclusion: There is no evidence supporting the use of ACWR in training-load-management systems or for training recommendations aimed at reducing injury risk. The statistical properties of the ratio make the ACWR an inaccurate metric and complicate its interpretation for practical applications. In addition, it adds noise and creates statistical artifacts. [ABSTRACT FROM AUTHOR]

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 l 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. [ABSTRACT FROM AUTHOR]

Purpose: To characterize player core temperature (Tc) across a World Rugby Women's Sevens Series tournament day (WRWSS) and determine the efficacy of commonly employed cold-water-immersion (CWI) protocols. Methods: Tc was measured in 12 elite female rugby sevens athletes across 3 games (G1–3) from day 1 of the Sydney WRWSS tournament. Symptoms of exertional heat illness, perceptual scales, CWI details, playing minutes, external-load data (measured by global positioning systems), and wet-bulb globe temperature (range 18.5°C–20.1°C) were also collected. Linear mixed models and magnitude-based inferences were used to assess differences in Tc between periods (G1–3 and warm-ups [WU]). Results: Average Tc was "very likely" lower (effect size; ±90% confidence limit −0.33; ±0.18) in G1 than in G2. Peak Tc was "very likely" (0.71; ±0.28) associated with increased playing time. CWI did not remove the accumulated Tc due to WU and match-play activity (∼1°C–2°C rise in Tc still present compared with Tc at WU onset for players ≥6-min match play). Conclusions: Elite WRWSS athletes experienced high Tc during WU (Tc peak 37.9–39.0°C) and matches (Tc peak 37.9–39.8°C), a magnitude known to reduce intermittent high-intensity physical performance (≥39°C). The CWI protocol resulted in players (≥6-min match play) with ∼1°C to 2°C raised Tc compared with Tc at WU onset. [ABSTRACT FROM AUTHOR]

Purpose: To examine the measurement reliability and sensitivity of common athlete monitoring tools in professional Australian Football players. Methods: Test–retest reliability (noise) and weekly variation (signal) data were collected from 42 professional Australian footballers from 1 club during a competition season. Perceptual wellness was measured via questionnaires completed before main training sessions (48, 72, and 96 h postmatch), with players providing a rating (1–5 Likert scale) regarding their muscle soreness, sleep quality, fatigue level, stress, and motivation. Eccentric hamstring force and countermovement jumps were assessed via proprietary systems once per week. Heart rate recovery was assessed via a standard submaximal run test on a grass-covered field with players wearing a heart rate monitor. The heart rate recovery was calculated by subtracting average heart rate during final 10 seconds of rest from average heart rate during final 30 seconds of exercise. Typical test error was reported as coefficient of variation percentage (CV%) and intraclass coefficients. Sensitivity was calculated by dividing weekly CV% by test CV% to produce a signal to noise ratio. Results: All measures displayed acceptable sensitivity. Signal to noise ratio ranged from 1.3 to 11.1. Intraclass coefficients ranged from.30 to.97 for all measures. Conclusions: The heart rate recovery test, countermovement jump test, eccentric hamstring force test, and perceptual wellness all possess acceptable measurement sensitivity. Signal to noise ratio analysis is a novel method of assessing measurement characteristics of monitoring tools. These data can be used by coaches and scientists to identify meaningful changes in common measures of fitness and fatigue in professional Australian football. [ABSTRACT FROM AUTHOR]

Physiological and psychological demands during training and competition generate fatigue and reduce an athlete's sport-specific performance capacity. The magnitude of this decrement depends on several characteristics of the exercise stimulus (eg, type, duration, and intensity), as well as on individual characteristics (eg, fitness, profile, and fatigue resistance). As such, the time required to fully recover is proportional to the level of fatigue, and the consequences of exercise-induced fatigue are manifold. Whatever the purpose of the ensuing exercise session (ie, training or competition), it is crucial to understand the importance of optimizing the period between exercise bouts in order to speed up the regenerative processes and facilitate recovery or set the next stimulus at the optimal time point. This implies having a fairly precise understanding of the fatigue mechanisms that contribute to the performance decrement. Failing to respect an athlete's recovery needs may lead to an excessive accumulation of fatigue and potentially "nonfunctional overreaching" or to maladaptive training. Although research in this area recently increased, considerations regarding the specific time frames for different physiological mechanisms in relation to exercise-induced fatigue are still missing. Furthermore, recommendations on the timing and dosing of recovery based on these time frames are limited. Therefore, the aim of this article is to describe time courses of recovery in relation to the exercise type and on different physiological levels. This summary supports coaches, athletes, and scientists in their decision-making process by considering the relationship of exercise type, physiology, and recovery. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Purpose: To examine the collective independent influence of a range of individual characteristics on physical and technical match performance during international rugby sevens matches. Methods: Data were collected from 20 international rugby sevens players from 1 team across 1 season. Activity profiles were measured using wearable microtechnology devices, and technical performance measures were collected from match video analysis. Subjective well-being measures were collected using a well-being questionnaire completed on the morning of main training days, and groin-squeeze assessments at 0° and 60° knee flexion were also conducted using a sphygmomanometer. Assessments of aerobic fitness were completed periodically across the season, including time to complete a 2-km run and final velocity during the 30:15 Intermittent Fitness Test (VIFT). A principal-components analysis was conducted to reduce the dimensionality of the physical and technical variables into single-factor values. Linear mixed models were then constructed to examine the collective influence of a range of individual contextual variables on physical and technical performance factors. Results: Increased muscle soreness, stress, and VIFT were associated with trivial to small increases in physical and technical performance values, whereas trivial to small decreases were associated with higher perceived recovery, body weight, and groin squeeze (0° knee flexion). Conclusions: A range of well-being metrics are required to account for a significant portion of the variance in physical and technical performance. These factors may be manipulated by coaches or practitioners to achieve favorable physiological readiness that may lead to improved match performance. [ABSTRACT FROM AUTHOR]

The National Basketball Association (NBA) has an extremely demanding competition schedule, requiring its athletes to compete in 82 regular-season games over a 6-mo period (∼3.4 games/wk). Despite the demanding schedule and high value of athletes, there is little public information on the specific game and training demands required to compete in the NBA. Although provisions in the NBA collective-bargaining agreement allow for research designed to improve player health and broaden medical knowledge, such information is sparse in the available literature. In relation to the physical demands of the NBA, the current lack of information likely results from multiple factors including limited understanding of (basketball-related) emerging technologies, impact of specific league rules, and steps taken to protect players in the age of Big Data. This article explores current limitations in describing specific game/training demands in the NBA and provides perspectives on how some of these challenges may be overcome. The authors propose that future collaborations between league entities, NBA clubs, commercial partners, and outside research institutions will enhance understanding of the physical demands in the NBA (and other health- and performance-related areas). More detailed understanding of physical demands (games, practices, and travel) and other health-related areas can augment player-centered decision making, leading to enhanced player care, increased availability, and improved physical performance. [ABSTRACT FROM AUTHOR]

Exercise is a stressor that induces various psychophysiological responses, which mediate cellular adaptations in many organ systems. To maximize this adaptive response, coaches and scientists need to control the stress applied to the athlete at the individual level. To achieve this, precise control and manipulation of the training load are required. In 2003, the authors introduced a theoretical framework to define and conceptualize the measurable constructs of the training process. They described training load as having 2 measurable components: internal and external load. The aim of this commentary is to extend, clarify, and refine both the theoretical framework and the definitions of internal and external training load to avoid misinterpretation of this concept. [ABSTRACT FROM AUTHOR]

Purpose: To examine the measurement properties of an adductor strength-assessment system in professional Australian footballers. Methods: Observational, longitudinal design. Test–retest reliability data were collected from 18 professional Australian footballers from 1 club on the same day during the 2017 Australian Football League season. Week-to-week variation data were collected on 45 professional Australian footballers from 1 club during the same season at 48, 72, and 120 h postmatch (rounds 1–23). Players lay beneath a GroinBar hip-strength testing system in supine position with their knee joints at an angle of 60°. Force (in newtons) was extracted for the left and right limbs of each player and a pain score from 0 to 10 (0 = no pain, 10 = maximum pain) was provided. Coefficient of variation (CV) and smallest worthwhile change were calculated on test–retest data. Signal-to-noise ratio was calculated for each major time point. Mean difference between force scores in a subgroup of players with and without groin pain (n = 18) was collected as evidence of construct validity for the system. Results: Test CV was 6.3% (4.9–9.0%). CV exceeded the smallest worthwhile change on both limbs. Intraclass correlation coefficient was.94. Signal-to-noise ratio ranged from 1.6 to 2.6 on average for 48, 72, and 120 h postmatch. Groin pain had a very likely moderate negative effect on adductor strength (effect size: 0.41). Conclusions: The system possesses greater measurement precision than dynamometry and sphygmomanometer adductor strength-assessment methods in professional Australian footballers. Increased groin pain reduced groin squeeze force production. Practitioners may interpret changes exceeding 6.3% in adductor strength as real. [ABSTRACT FROM AUTHOR]

Objectives: To examine the collective influence of a range of physical preparation elements on selected performance measures during Australian football match play. Design: Prospective and longitudinal. Methods: Data were collected from 34 professional Australian football players from the same club during the 2016 Australian Football League competition season. Match activity profiles and acute (7-d) and chronic (3-wk) training loads were collected using global positioning system devices. Training response was measured by well-being questionnaires completed prior to the main training session each week. Maximal aerobic running speed (MAS) was estimated by a 2-km time trial conducted during preseason. Coach ratings were collected from the senior coach and 4 assistants after each match on a 5-point Likert scale. Player ratings were obtained from a commercial statistics provider. Fifteen matches were analyzed. Linear mixed models were constructed to examine the collective influence of training-related factors on 4 performance measures. Results: Muscle soreness had a small positive effect (ES: 0.12) on Champion Data rating points. Three-week average high-speed running distance had a small negative effect (ES: 0.14) on coach ratings. MAS had large to moderate positive effects (ES: 0.55 to 0.47) on relative total and high-speed running distances. Acute total and chronic average total running distance had small positive (ES: 0.13) and negative (ES: 0.14) effects on relative total and high-speed running distance performed during matches, respectively. Conclusions: MAS should be developed to enhance players' running performance during competition. Monitoring of physical preparation data may assist in reducing injury and illness and increasing player availability but not enhance football performance. [ABSTRACT FROM AUTHOR]

There is a common expression in sports that "there is no 'I' in team." However, collectively, there is actually a very important "I" in sport teams—the individual athlete/player. Each player has his or her own unique characteristics including physical, physiological, and psychological traits. Due to these unique characteristics, each player requires individual provision—whether it be an injury risk profile and targeted prevention strategy or treatment/rehabilitation for injury, dietary regimen, recovery, or psychological intervention. The aim of this commentary is to highlight how 4 high-performance teams from various professional football codes are analyzing individual player data. [ABSTRACT FROM AUTHOR]

Purpose: To determine the relationship between drill type and accelerometer-derived loads during various team-sport activities and examine the influence of unit fitting on these loads. Methods: Sixteen rugby league players were fitted with microtechnology devices in either manufacturer vests or playing jerseys before completing standardized running, agility, and tackling drills. Two-dimensional (2D) and 3-dimensional (3D) accelerometer loads (BodyLoad™) per kilometer were compared across drills and fittings (ie, vest and jersey). Results: When fitted in a vest, 2D BodyLoad was higher during tackling (21.5 [14.8] AU/km) than during running (9.5 [2.5] AU/km) and agility (10.3 [2.7] AU/km). Jersey fitting resulted in more than 2-fold higher BodyLoad during running (2D = 9.5 [2.7] vs 29.3 [14.8] AU/km, 3D = 48.5 [14.8] vs 111.5 [45.4] AU/km) and agility (2D = 10.3 [2.7] vs 21.0 [8.1] AU/km, 3D = 40.4 [13.6] vs 77.7 [26.8] AU/km) compared with a vest fitting. Jersey fitting also produced higher BodyLoad during tackling drills (2D = 21.5 [14.8] vs 27.8 [18.6] AU/km, 3D = 42.0 [21.4] vs 63.2 [33.1] AU/km). Conclusions: This study provides evidence supporting the construct validity of 2D BodyLoad for assessing collision/tackling load in rugby league training drills. Conversely, the large values obtained from 3D BodyLoad (which includes the vertical load vector) appear to mask small increases in load during tackling drills, rendering 3D BodyLoad insensitive to changes in contact load. Unit fitting has a large influence on accumulated accelerometer loads during all drills, which is likely related to greater incidental unit movement when units are fitted in jerseys. Therefore, it is recommended that athletes wear microtechnology units in manufacturer-provided vests to provide valid and reliable information. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Context: The relationship between pretraining subjective wellness and external and internal training load in American college football is unclear. Purpose: To examine the relationship of pretraining subjective wellness (sleep quality, muscle soreness, energy, wellness Z score) with player load and session rating of perceived exertion (s-RPE-TL) in American college football players. Methods: Subjective wellness (measured using 5-point, Likert-scale questionnaires), external load (derived from GPS and accelerometry), and s-RPE-TL were collected during 3 typical training sessions per week for the second half of an American college football season (8 wk). The relationship of pretraining subjective wellness with player load and s-RPE training load was analyzed using linear mixed models with a random intercept for athlete and a random slope for training session. Standardized mean differences (SMDs) denote the effect magnitude. Results: A 1-unit increase in wellness Z score and energy was associated with trivial 2.3% (90% confidence interval [CI] 0.5, 4.2; SMD 0.12) and 2.6% (90% CI 0.1, 5.2; SMD 0.13) increases in player load, respectively. A 1-unit increase in muscle soreness (players felt less sore) corresponded to a trivial 4.4%(90% CI -8.4, -0.3; SMD -0.05) decrease in s-RPE training load. Conclusion: Measuring pretraining subjective wellness may provide information about players' capacity to perform in a training session and could be a key determinant of their response to the imposed training demands American college football. Hence, monitoring subjective wellness may aid in the individualization of training prescription in American college football players. [ABSTRACT FROM AUTHOR]

Purpose: To examine the influence of a range of individual player characteristics and match-related factors on activity profiles during professional Australian football matches. Methods: Global positioning system (GPS) profiles were collected from 34 professional Australian football players from the same club over 15 competition matches. GPS data were classified into relative total and high-speed running (HSR; >20 km/h) distances. Individual player aerobic fitness was determined from a 2-km time trial conducted during the preseason. Each match was classified according to match location, season phase, recovery length, opposition strength, and match outcome. The total number of stoppages during the match was obtained from a commercial statistics provider. A linear mixed model was constructed to examine the influence of player characteristics and match-related factors on both relative total and HSR outputs. Results: Player aerobic fitness had a large effect on relative total and HSR distances. Away matches and matches lost produced only small reductions in relative HSR distances, while the number of rotations also had a small positive effect. Matches won, more player rotations, and playing against strong opposition all resulted in small to moderate increases in relative total distance, while early season phase, increased number of stoppages, and away matches resulted in small to moderate reductions in relative total distance Conclusions: There is a likely interplay of factors that influence running performance during Australian football matches. The results highlight the need to consider a variety of contextual factors when interpreting physical output from matches. [ABSTRACT FROM AUTHOR]

Methods: This study compared 3 commercially available ergometers for within- and between-brands difference to a first-principle calibration rig. Results: All ergometers underestimated true mean power, with errors of 27.6% ± 3.7%, 4.5% ± 3.5%, and 22.5% ± 1.9% for the KayakPro, WEBA, and Dansprint, respectively. Within-brand ergometer power differences ranged from 17 ± 9 to 22 ± 11 W for the KayakPro, 3 ± 4 to 4 ± 4 W for the WEBA, and 5 ± 3 to 5 ± 4 W for the Dansprint. The linear-regression analysis showed that most kayak ergometers have a stable coefficient of variation (0.9-1.7%) with a moderate effect size. Conclusion: Taken collectively, these findings show that different ergometers present inconsistent outcomes. Therefore, we suggest that athlete testing be conducted on the same ergometer brand, preferably the same ergometer. Optimally, that ergometer should be calibrated using a first-principle device before any athlete testing block. [ABSTRACT FROM AUTHOR]

Purpose: To describe the training demands of contemporary dance and determine the validity of using the session rating of perceived exertion (sRPE) to monitor exercise intensity and training load in this activity. In addition, the authors examined the contribution of training (ie, accelerometry and heart rate) and non-training-related factors (ie, sleep and wellness) to perceived exertion during dance training. Methods: Training load and ActiGraphy for 16 elite amateur contemporary dancers were collected during a 49-d period, using heart-rate monitors, accelerometry, and sRPE. Within-individual correlation analysis was used to determine relationships between sRPE and several other measures of training intensity and load. Stepwise multiple regressions were used to determine a predictive equation to estimate sRPE during dance training. Results: Average weekly training load was 4283 ± 2442 arbitrary units (AU), monotony 2.13 ± 0.92 AU, strain 10677 ± 9438 AU, and average weekly vector magnitude load 1809,707 ± 1015,402 AU. There were large to very large within-individual correlations between training-load sRPE and various other internal and external measures of intensity and load. The stepwise multiple-regression analysis also revealed that 49.7% of the adjusted variance in training-load sRPE was explained by peak heart rate, metabolic equivalents, soreness, motivation, and sleep quality (y = -4.637 + 13.817%HRpeak + 0.316 METS + 0.100 soreness + 0.116 motivation - 0.204 sleep quality). Conclusion: The current findings demonstrate the validity of the sRPE method for quantifying training load in dance, that dancers undertake very high training loads, and a combination of training and nontraining factors contribute to perceived exertion in dance training. [ABSTRACT FROM AUTHOR]

Monitoring the load placed on athletes in both training and competition has become a very hot topic in sport science. Both scientists and coaches routinely monitor training loads using multidisciplinary approaches, and the pursuit of the best methodologies to capture and interpret data has produced an exponential increase in empirical and applied research. Indeed, the field has developed with such speed in recent years that it has given rise to industries aimed at developing new and novel paradigms to allow us to precisely quantify the internal and external loads placed on athletes and to help protect them from injury and ill health. In February 2016, a conference on "Monitoring Athlete Training Loads--The Hows and the Whys" was convened in Doha, Qatar, which brought together experts from around the world to share their applied research and contemporary practices in this rapidly growing field and also to investigate where it may branch to in the future. This consensus statement brings together the key findings and recommendations from this conference in a shared conceptual framework for use by coaches, sport-science and -medicine staff, and other related professionals who have an interest in monitoring athlete training loads and serves to provide an outline on what athlete-load monitoring is and how it is being applied in research and practice, why load monitoring is important and what the underlying rationale and prospective goals of monitoring are, and where athlete-load monitoring is heading in the future. [ABSTRACT FROM AUTHOR]

Purpose: To assess measurement sensitivity and diagnostic characteristics of athlete-monitoring tools to identify performance change. Methods: 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. Results: 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). Conclusion: 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. [ABSTRACT FROM AUTHOR]

Athlete-tracking devices that include global positioning system (GPS) and microelectrical mechanical system (MEMS) components are now commonplace in sport research and practice. These devices provide large amounts of data that are used to inform decision making on athlete training and performance. However, the data obtained from these devices are often provided without clear explanation of how these metrics are obtained. At present, there is no clear consensus regarding how these data should be handled and reported in a sport context. Therefore, the aim of this review was to examine the factors that affect the data produced by these athlete-tracking devices and to provide guidelines for collecting, processing, and reporting of data. Many factors including device sampling rate, positioning and fitting of devices, satellite signal, and data-filtering methods can affect the measures obtained from GPS and MEMS devices. Therefore researchers are encouraged to report device brand/model, sampling frequency, number of satellites, horizontal dilution of precision, and software/firmware versions in any published research. In addition, details of inclusion/exclusion criteria for data obtained from these devices are also recommended. Considerations for the application of speed zones to evaluate the magnitude and distribution of different locomotor activities recorded by GPS are also presented, alongside recommendations for both industry practice and future research directions. Through a standard approach to data collection and procedure reporting, researchers and practitioners will be able to make more confident comparisons from their data, which will improve the understanding and impact these devices can have on athlete performance. [ABSTRACT FROM AUTHOR]

Purpose: Faster heart-rate recovery (HRR) after high to maximal exercise (≥90% of maximal heart rate) has been reported in athletes suspected of functional overreaching (f-OR). This study investigated whether this response would also occur at lower exercise intensity. Methods: Responses of HRR and rating of perceived exertion (RPE) were compared during an incremental intermittent running protocol to exhaustion in 20 experienced male triathletes (8 control subjects and 13 overload subjects led to f-OR) before and immediately after an overload training period and after a 1-wk taper. Results: Both groups demonstrated an increase in HRR values immediately after the training period, but this change was very likely to almost certainly larger in the f-OR group at all running intensities (large to very large differences, eg, +16 ± 7 vs +3 ± 5 beats/min, in the f-OR and control groups at 11 km/h, respectively). The highest between-groups differences in changes in HRR were reported at 11 km/h (13 ± 4 beats/min) and 12 km/h ( 10 ± 6 beats/min). A concomitant increase in RPE at all intensities was reported only in the f-OR group (large to extremely large differences, +2.1 ± 1.5 to +0.7 ± 1.5 arbitrary units). Conclusion: These findings confirm that faster HRR does not systematically predict better physical performance. However, when interpreted in the context of the athletes' fatigue state and training phase, HRR after submaximal exercise may be more discriminant than HRR measures taken after maximal exercise for monitoring f-OR. These findings may be applied in practice by regularly assessing HRR after submaximal exercise (ie, warm-up) for monitoring endurance athletes' responses to training. [ABSTRACT FROM AUTHOR]

Purpose: To examine differences in physical and technical performance profiles using a large sample of match observations drawn from successful and less-successful professional rugby league teams. Methods: Match activity profiles were collected using global positioning satellite (GPS) technology from 29 players from a successful rugby league team during 24 games and 25 players from a less-successful team during 18 games throughout 2 separate competition seasons. Technical performance data were obtained from a commercial statistics provider. A progressive magnitude-based statistical approach was used to compare differences in physical and technical performance variables between the reference teams. Results: There were no clear differences in playing time, absolute and relative total distances, or low-speed running distances between successful and less-successful teams. The successful team possibly to very likely had lower higher-speed running demands and likely had fewer piysical collisions than the less-successful team, although they likely to most likely demonstrated more accelerations and decelerations and likely had higher average metabolic power. The successful team very likely gained more territory in attack, very likely had more possessions, and likely committed fewer errors. In contrast, the less-successful team was likely required to attempt more tackles, most likely missed more tackles, and very likely had a lower effective tackle percentage. Conclusions: In the current study, successful match performance was not contingent on higher match running outputs or more physical collisions; rather, proficiency in technical performance components better differentiated successful and less-successful teams. [ABSTRACT FROM AUTHOR]

The aim of the current study was to examine the influence of restricted visual feedback using stroboscopic eyewear on the dribbling performance of youth soccer players. Three dribble test conditions were used in a within-subjects design to measure the effect of restricted visual feedback on soccer dribbling performance in 189 youth soccer players (age: 10-18 y) classified as fast, average or slow dribblers. The results showed that limiting visual feedback increased dribble test times across all abilities. Furthermore, the largest performance decrement between stroboscopic and full vision conditions was in fast dribblers, showing that fast dribblers were most affected by reduced visual information. This may be due to a greater dependency on visual feedback at increased speeds, which may limit the ability to maintain continuous control of the ball. These findings may have important implications for the development of soccer dribbling ability. [ABSTRACT FROM AUTHOR]

Purpose: To compare development and variations in body composition of early-, mid-, and late-career professional Australian Football (AF) players over 3 successive seasons. Methods: Regional and total-body composition (body mass [BM], fat mass [FM], fat-free soft-tissue mass [FFSTM], and bone mineral content [BMC]) were assessed 4 times, at the same time of each season--start preseason (SP), end preseason (EP), midseason (MS), and end season (ES)--from 22 professional AF players using pencil-beam dual-energy X-ray absorptiometry. Nutritional intake for each player was evaluated concomitantly using 3-d food diaries. Players were classified according to their age at the beginning of the observational period as either early- (<21 y, n = 8), mid- (21 to 25 y, n = 9), or late- (>25 y, n = 5) career athletes. Results: Early-career players had lower FFSTM, BMC, and BM than mid- and late-career throughout. FM and %FM had greatest variability, particularly in the early-career players. FM reduced and FFSTM increased from SP to EP, while FM and FFSTM decreased from EP to MS. FM increased and FFSTM decreased from MS to ES, while FM and FFSTM increased during the off-season. Conclusions: Early-career players may benefit from greater emphasis on specific nutrition and resistance-training strategies aimed at increasing FFSTM, while all players should balance training and diet toward the end of season to minimize increases in FM. [ABSTRACT FROM AUTHOR]

This article discusses the relationship between sports drinks consumption, athletic ability, and high temperatures. An analysis of body mass index, fluid retention, sweat loss, and blood plasma changes is presented.

Purpose: To assess the effects of mental fatigue on physical and technical performance in small-sided soccer games. Methods: Twenty soccer players (age 17.8 ± 1.0 y, height 179 ± 5 cm, body mass 72.4 ± 6.8 kg, playing experience 8.3 ± 1.4 y) from an Australian National Premier League soccer club volunteered to participate in this randomized crossover investigation. Participants played 15-min 5-vs-5 small-sided games (SSGs) without goalkeepers on 2 occasions separated by 1 wk. Before the SSG, 1 team watched a 30-min emotionally neutral documentary (control), while the other performed 30 min of a computer-based Stroop task (mental fatigue). Subjective ratings of mental and physical fatigue were recorded before and after treatment and after the SSG. Motivation was assessed before treatment and SSG; mental effort was assessed after treatment and SSG. Player activity profiles and heart rate (HR) were measured throughout the SSG, whereas ratings of perceived exertion (RPEs) were recorded before the SSG and immediately after each half. Video recordings of the SSG allowed for notational analysis of technical variables. Results: Subjective ratings of mental fatigue and effort were higher after the Stroop task, whereas motivation for the upcoming SSG was similar between conditions. HR during the SSG was possibly higher in the control condition, whereas RPE was likely higher in the mental-fatigue condition. Mental fatigue had an unclear effect on most physical-performance variables but impaired most technical-performance variables. Conclusions: Mental fatigue impairs technical but not physical performance in small-sided soccer games. [ABSTRACT FROM AUTHOR]

Purpose: To analyze the match running profile, distance traveled over successive 15 min of match play, heart rates (HRs), and index of performance efficiency (effindex) of professional soccer players with a global positioning system (GPS) and HR in official competition. Methods: Twenty-six professional players were investigated during full matches in competitive club-level matches (N = 223). Time-motion data and HR were collected using GPS and HR technology. Results: The relative total distance was 113 ± 11 m/min, with substantial differences between halves. For all playing positions, a substantial decrease in total distance and distance covered at >13.0 km/h was observed in the second half in comparison with the first. The decrease during the second half in distance covered at >13.0 km/h was substantially higher than in total distance. The average HR recorded was 86.0% maximal HR, and the relationship between external and internal load (effindex) was 1.3, with substantial differences between halves in all playing positions, except strikers for effindex. Wide midfielders reflected substantially the lowest mean HR and highest effindex, whereas center backs showed substantially the lowest effindex of all playing positions. Conclusions: The current study confirmed the decrement in a player's performance toward the end of a match in all playing positions. Wide midfielders displayed the highest and fittest levels of physical and physiological demands, respectively, whereas center backs had the lowest and least-fit levels of physical and physiological demands, respectively. The position-specific relationship between external and internal load confirms that players with more overall running performance during the full match were the best in effindex. [ABSTRACT FROM AUTHOR]

Purpose: To describe the effect of the initial perceptual experience from heat familiarization on the pacing profile during a free-paced endurance time trial (IT) compared with temperate conditions. Methods: Two groups of well-trained triathletes performed two 20-km TTs in either hot (35°C and 50% relative humidity [RH], n= 12) or temperate (21 °C and 50% RH, n = 22) conditions, after standardization of training for each group before both trials. To ensure no physiological acclimation differences between conditions, the TTs for both groups were separated by 11 ± 4 d.Results: Performance improvement in the heat (11 ±24W)from the 1st to 2nd trial appeared comparable to that in temperate conditions (8 ± 14 W, P = .67). However, the specific alteration in pacing profile in the heat was markedly different than temperate conditions, with a change from "positive" to an "even" pacing strategy. Conclusions: Altered perceptions of heat during heat familiarization, rather than physiological acclimatization per se, may mediate initial changes in pacing and TT performance in the heat. These results highlight the need for athletes without time for sufficient heat acclimatization to familiarize themselves with hot conditions to reduce the uncertainty from behavior-based outcomes that may impede performance. [ABSTRACT FROM AUTHOR]

The purpose of this study was to examine the seasonal changes in body composition, nutrition, and upper-body (UB) strength in professional Australian Football (AF) players. The prospective longitudinal study examined changes in anthropometry (body mass, fat-free soft-tissue mass [FFSTM], and fat mass) via dual-energy X-ray absorptiometry 5 times during an AF season (start preseason, midpreseason, start season, midseason, end season) in 45 professional AF players. Dietary intakes and strength (bench press and bench pull) were also assessed at these time points. Players were categorized as experienced (>4 y experience, n = 23) or inexperienced (<4 y experience, n = 22). Fat mass decreased during the preseason but was stable through the in-season for both groups. %FFSTM was increased during the preseason and remained constant thereafter. UB strength increased during the preseason and was maintained during the in-season. Changes in UB FFSTM were related to changes in UB-strength performance (r= .37-.40). Total energy and carbohydrate intakes were similar between the experienced and inexperienced players during the season, but there was a greater ratio of dietary fat intake at the start-preseason point and an increased alcohol, reduced protein, and increased total energy intake at the end of the season. The inexperienced players consumed more fat at the start of season and less total protein during the season than the experienced players. Coaches should also be aware that it can take >1 y to develop the appropriate levels of FFSTM in young players and take a long-term view when developing the physical and performance abilities of inexperienced players. [ABSTRACT FROM AUTHOR]

The authors reflect on the need for sports scientists to collaborate in research and evidence-based practice to have an impact to the sporting performance of athletes. Topics include how effective collaboration between scientists, coaches and athletes can bridge the gap from research to practice, and the sport-science impact matrix to discuss how research affect sport performance.

While the effects of sleep loss on performance have previously been reviewed, the effects of disturbed sleep on recovery after exercise are less reported. Specifically, the interaction between sleep and physiological and psychological recovery in team-sport athletes is not well understood. Accordingly, the aim of the current review was to examine the current evidence on the potential role sleep may play in postexercise recovery, with a tailored focus on professional team-sport athletes. Recent studies show that team-sport athletes are at high risk of poor sleep during and after competition. Although limited published data are available, these athletes also appear particularly susceptible to reductions in both sleep quality and sleep duration after night competition and periods of heavy training. However, studies examining the relationship between sleep and recovery in such situations are lacking. Indeed, further observational sleep studies in team-sport athletes are required to confirm these concerns. Naps, sleep extension, and sleep-hygiene practices appear advantageous to performance; however, future proof-of-concept studies are now required to determine the efficacy of these interventions on postexercise recovery. Moreover, more research is required to understand how sleep interacts with numerous recovery responses in team-sport environments. This is pertinent given the regularity with which these teams encounter challenging scenarios during the course of a season. Therefore, this review examines the factors that compromise sleep during a season and after competition and discusses strategies that may help improve sleep in team-sport athletes. [ABSTRACT FROM AUTHOR]

Purpose: To examine the impact of varying between-matches microcycles on training characteristics (ie, intensity, duration, and load) in professional rugby league players and to report on match load related to these between-matches microcycles. Methods: Training-load data were collected during a 26-wk competition period of an entire season. Training load was measured using the session rating of perceived exertion (session-RPE) method for every training session and match from 44 professional rugby league players from the same National Rugby League team. Using the category-ratio 10 RPE scale, the training intensity was divided into 3 zones (low <4 AU, moderate ≥4-≤7 AU, and high >7 AU). Three different-length between-matches recovery microcycles were used for analysis: 5-6 d, 7-8 d, and 9-10 d. Results: A total of 3848 individual sessions were recorded. During the shorter-length between-matches microcycles (5-6 d), significantly lower training load was observed. No significant differences for subsequent match load or intensity were identified between the various match recovery periods. Overall, 16% of the training sessions were completed at the low-intensity zone, 61% at the moderate-intensity zone, and 23% at the high-intensity zone. Conclusions: The findings demonstrate that rugby league players undertake higher training load as the length of between-matches microcycles is increased. The majority of in-season training of professional rugby league players was at moderate intensity, and a polarized approach to training that has been reported in elite endurance athletes does not occur in professional rugby league. [ABSTRACT FROM AUTHOR]

Purpose: To describe the physical and technical demands of rugby league 9s (RL9s) match play for positional groups. Methods: Global positioning system data were collected during 4 games from 16 players from a team competing in the Auckland RL9s tournament. Players were classified into positional groups (pivots, outside backs, and forwards). Absolute and relative physical- performance data were classified as total high-speed running (HSR; >14.4 km/h), very-high-speed running (VHSR; >19.0 km/h), and sprint (>23.0 km/h) distances. Technical-performance data were obtained from a commercial statistics provider. Activity cycles were coded by an experienced video analyst. Results: Forwards (1088 m, 264 m) most likely completed less overall and high-speed distances than pivots (1529 m, 371 m) and outside backs (1328 m, 312 m). The number of sprint efforts likely varied between positions, although differences in accelerations were unclear. There were no clear differences in relative total (115.6-121.3 m/min) and HSR (27.8-29.8 m/min) intensities, but forwards likely performed less VHSR (7.7 m/min) and sprint distance (1.3 m/min) per minute than other positions (10.2-11.8 m/min, 3.7-4.8 m/min). The average activity and recovery cycle lengths were ~50 and ~27 s, respectively. The average longest activity cycle was ~133 s, while the average minimum recovery time was ~5 s. Technical involvements including tackles missed, runs, tackles received, total collisions, errors, off-loads, line breaks, and involvements differed between positions. Conclusions: Positional differences exist for both physical and technical measures, and preparation for RL9s play should incorporate these differences. [ABSTRACT FROM AUTHOR]

This study aimed to profile the physiological characteristics of junior sprint kayak athletes (n = 21, VO2max 4.1 ± 0.7 L/min, training experience 2.7 ± 1.2 y) and to establish the relationship between physiological variables (VO2max, VO2 kinetics, muscleoxygen kinetics, paddling efficiency) and sprint kayak performance. VO2max, power at VO2max, power:weight ratio, paddling efficiency, VO2 at lactate threshold, and whole-body and muscle oxygen kinetics were determined on a kayak ergometer in the laboratory. Separately, on-water time trials (TT) were completed over 200 m and 1000 m. Large to nearly perfect (-.5 to -.9) inverse relationships were found between the physiological variables and on-water TT performance across both distances. Paddling efficiency and lactate threshold shared moderate to very large correlations (-.4 to -.7) with 200- and 1000-m performance. In addition, trivial to large correlations (-.11 to -.5) were observed between muscle-oxygenation parameters, muscle and whole-body oxygen kinetics, and performance. Multiple regression showed that 88% of the unadjusted variance for the 200-m TT performance was explained by VO2max, peripheral muscle deoxygenation, and maximal aerobic power (P < .001), whereas 85% of the unadjusted variance in 1000-m TT performance was explained by VO2max and deoxyhemoglobin (P < .001). The current findings show that well-trained junior sprint kayak athletes possess a high level of relative aerobic fitness and highlight the importance of the peripheral muscle metabolism for sprint kayak performance, particularly in 200-m races, where finalists and nonfinalists are separated by very small margins. Such data highlight the relative aerobic-fitness variables that can be used as benchmarks for talent-identification programs or monitoring longitudinal athlete development. However, such approaches need further investigation. [ABSTRACT FROM AUTHOR]

Purpose: To examine the training periodization of an elite Australian Football team during different phases of the season. Methods: Training-load data were collected during 22 wk of preseason and 23 wk of in-season training. Training load was measured using the session rating of perceived exertion (session-RPE) for all training sessions and matches from 44 professional Australian Football players from the same team. Training intensity was divided into 3 zones based on session-RPE (low, <4; moderate, >4 AU and <7 AU; and high, >7 AU). Training load and intensity were analyzed according to the type of training session completed. Results: Higher training load and session duration were undertaken for all types of training sessions during the preseason than in-season (P < .05), with the exception of "other" training (ie, re/prehahilitation training, cross-training, and recovery activities). Training load and intensity were higher during the preseason, with the exception of games, where greater load and intensity were observed during the in-season. The overall distribution of training intensity was similar between phases with the majority of training performed at moderate or high intensity. Conclusions: The current findings may allow coaches and scientists to better understand the characteristics of Australian Football periodization, which in turn may aid in developing optimal training programs. The results also indicate that a polarized training-intensity distribution that has been reported in elite endurance athletes does not occur in professional Australian Football. [ABSTRACT FROM AUTHOR]