Profiling Professional Rugby Union Activity After Peak Match Periods.

The aim of this investigation was to quantify professional rugby union player activity profiles after the most intense (peak) passages of matches. Movement data were collected from 30 elite and 30 subelite professional rugby union athletes across respective competitive seasons. Accelerometer-derived PlayerLoad and global navigation satellite system-derived measures of mean speed and metabolic power were analyzed using a rolling-average method to identify the most intense 5- to 600-second passages (ie, worst-case scenarios) within matches. Player activity profiles immediately post their peak 5- to 600-second match intensity were identified using 5 epoch duration-matched intervals. Mean speed, metabolic power, and PlayerLoad declined sharply (∼29%-86%) after the most intense 5 to 600 seconds of matches. Following the most intense periods of rugby matches, exercise intensity declined below the average match-half intensity 81% of the time and seldom returned to or exceeded it, likely due to a host of individual physical and physiological characteristics, transient and/or accumulative fatigue, contextual factors, and pacing strategies. Typically, player exercise intensities after the most intense passages of matches were similar between match halves, positional groups, and levels of rugby competition. Accurate identification of the peak exercise intensities of matches and movement thereafter using novel methodologies has improved the limited understanding of professional rugby union player activity profiles following the worst-case scenarios of matches. Findings of the present study may inform match-representative training prescription, monitoring, and tactical match decisions (eg, substitutions and positional changes).

Applying common filtering processes to Global Navigation Satellite System-derived acceleration during team sport locomotion.

This study aimed to observe whether there were substantial differences in acceleration during team-sport locomotion between GNSS manufacturers. Speed and acceleration were obtained from 7 professional rugby league athletes via 2 GNSS manufacturers (GPSports EVO, 10 Hz and STATSports Apex, 10 Hz) worn together during the same training sessions (n = 13). Raw GNSS data were exported from respective proprietary software and a 1 Hz, 4th-order Butterworth filter applied, with differences in speed and acceleration calculated between manufacturers. To determine the difference in acceleration and speed, a root mean square deviation (RMSD) was used. Linear mixed models were used and no substantial differences were found between manufacturers in raw and filtered speed variables. RMSD for average acceleration (m · s-2) decreased from raw (RMSD: 1.77 ± 0.37 m · s-2) to those seen at the filtered (RMSD: 0.27 ± 0.23 m · s-2) and twice filtered (0.24 ± 0.23 m · s-2) variables. Raw average acceleration (m · s-2) was substantially higher in Apex compared to EVO (Difference (Diff); CI: -0.82; -0.84 to -0.80). Following application of the common filter there was no substantial difference between GNSS models for average acceleration (Diff; CI: -0.04; -0.04 to -0.04). Acceleration variables derived from each manufacturer's proprietary software were substantially different.

Modeling Professional Rugby Union Peak Intensity-Duration Relationships Using a Power Law.

PURPOSE: Can power law models accurately predict the peak intensities of rugby competition as a function of time? METHODS: Match movement data were collected from 30 elite and 30 subelite rugby union athletes across competitive seasons, using wearable Global Navigation Satellite Systems and accelerometers. Each athlete's peak rolling mean value of each measure (mean speed, metabolic power, and PlayerLoad™) for 8 durations between 5 seconds and 10 minutes was predicted by the duration with 4 power law (log-log) models, one for forwards and backs in each half of a typical match. RESULTS: The log of peak exercise intensity and exercise duration (5-600 s) displayed strong linear relationships (R2 = .967-.993) across all 3 measures. Rugby backs had greater predicted intensities for shorter durations than forwards, but their intensities declined at a steeper rate as duration increased. Random prediction errors for mean speed, metabolic power, and PlayerLoad were 5% to 6%, 7% to 9%, and 8% to 10% (moderate to large), respectively, for elite players. Systematic prediction errors across the range of durations were trivial to small for elite players, underestimating intensities for shorter (5-10 s) and longer (300-600 s) durations by 2% to 4% and overestimating 20- to 120-second intensities by 2% to 3%. Random and systematic errors were slightly greater for subelites compared to elites, with ranges of 4% to 12% and 2% to 5%, respectively. CONCLUSIONS: Peak intensities of professional rugby union matches can be predicted with adequate precision (trivial to small errors) for prescribing training drills of a given duration, irrespective of playing position, match half, level of competition, or measure of exercise intensity. However, practitioners should be aware of the substantial (moderate to large) prediction errors at the level of the individual player.

The impact of matches and travel on rugby players' sleep, wellness and training.

Matches and travel, which are common in professional team sports, may have a negative impact on players. The aim of this study was to quantify the impact on sleep, wellness and training of Super Rugby players. Sleep of 122 players from four teams was monitored using activity monitors for up to three nights before and after matches played at home and overseas. Wellness and internal training load (questionnaires) and external training load (GPS/accelerometer) were also recorded. Separate analyses were performed for each team using a general linear mixed model to estimate the mean effects of travel (translocation overseas and return to the home country) on sleep, wellness and training. The mean effects of matches on sleep and wellness on the nights before, of and after matches. were also estimated. Teams generally experienced small to large reductions in sleep and wellness when overseas; on return, sleep and wellness recovered somewhat. The impact of matches on sleep and wellness differed in magnitude and direction (large reductions to small increases) between teams. External load overseas and upon return was reduced for three of the four teams, whilst internal load was reduced for the three teams that measured it. The changes in sleep, wellness and training can be explained by a combination of travel- and match-related stressors that differed between teams. Teams should consider remediation strategies to mitigate the effects of travel.

Prediction of 2000-m on-water rowing performance with measures derived from instrumented boats.

PURPOSE: Rowing instrumentation systems provide measures of stroke power, stroke rate, and boat velocity during rowing races, but how well these measures predict race performance has not been reported previously. METHODS: Data were collected per stroke from 45 2000-m races using Peach PowerLine and OptimEye S5 GPS units. The boat classes assessed were nine male singles, eight female singles, three male pairs, and six female pairs. Random effects and residuals from general linear mixed modeling of stroke velocity adjusted for stroke power, stroke rate, and mean headwind provided measures interpreted as technical efficiency, race conditions, and stroke-velocity variability. These measures, along with mean race power, mean stroke rate, and mean headwind were then included in multiple linear regressions to predict race velocity from official race times. Effects were assessed for 2 SD changes in predictors and interpreted using interval hypothesis tests. RESULTS: Effects of mean race power, mean stroke rate, and mean headwind on race velocity ranged from small to extremely large and were mostly decisively substantial. Effects of technical efficiency and race conditions ranged from trivial to extremely large but were generally unclear, while stroke-velocity variability had trivial-small and mostly unclear effects. Prediction error was small to moderate and decisively substantial. Men's pairs lacked sufficient data for analysis. CONCLUSION: On-water rowing race performance can be predicted with mean race values of power, stroke rate, and headwind. Estimates from stroke data are potentially useful predictors but require impractical numbers of boats and races to reduce their uncertainty.

Seasonal Change in Body Composition and Physique of Team Sport Athletes.

ABSTRACT: Walker, EJ, Aughey, RJ, McLaughlin, P, and McAinch, AJ. Seasonal change in body composition and physique of team sport athletes. J Strength Cond Res 36(2): 565-572, 2022-Body composition of team sport athletes was measured at 3 points across the preseason and competitive season. This repeated-measures study was conducted in 46 professional Australian football (AF) (age 23.8 ± 3.8 years), 26 soccer (age 22.7 ± 4.7 years), and 33 rugby union players (age 28.1 ± 4.2 years). A mixed-design analysis of variance was used to determine change across the season, and Pearson's correlation was used to determine the relationship between different measures. Anthropometry, dual-energy x-ray absorptiometry (DXA), and 3-dimensional (3D) scan technology were used in AF and soccer, whereas only DXA was used in rugby. Body mass remained unchanged for both AF and soccer with gains in lean mass (p < 0.01), from preseason to early in the competitive season. Skinfold measures declined in AF (p < 0.001) and soccer (p < 0.05) across the season, whereas DXA-measured fat mass only declined in soccer (p < 0.01). Rugby backs (p < 0.01) and forwards (p < 0.001) reduced body fat and gained lean mass from preseason to in-season with forwards having greater relative and absolute changes as measured by DXA. 3D technology did not show change across the season. Dual-energy x-ray absorptiometry body fat percent and the sum of skinfold correlation were large (r = 0.74 [p < 0.001, CI 0.67-0.81]). The greatest change in body composition occurs from the beginning of preseason to the start of competition, with changes returning to baseline levels toward the end of season. Dual-energy x-ray absorptiometry and skinfold measures were moderately correlated, providing a good alternative to track change in subcutaneous fat in AF and soccer athletes.

Concurrent Validity of Power From Three On-Water Rowing Instrumentation Systems and a Concept2 Ergometer.

Purpose: Instrumentation systems are increasingly used in rowing to measure training intensity and performance but have not been validated for measures of power. In this study, the concurrent validity of Peach PowerLine (six units), Nielsen-Kellerman EmPower (five units), Weba OarPowerMeter (three units), Concept2 model D ergometer (one unit), and a custom-built reference instrumentation system (Reference System; one unit) were investigated. Methods: Eight female and seven male rowers [age, 21 ± 2.5 years; rowing experience, 7.1 ± 2.6 years, mean ± standard deviation (SD)] performed a 30-s maximal test and a 7 × 4-min incremental test once per week for 5 weeks. Power per stroke was extracted concurrently from the Reference System (via chain force and velocity), the Concept2 itself, Weba (oar shaft-based), and either Peach or EmPower (oarlock-based). Differences from the Reference System in the mean (representing potential error) and the stroke-to-stroke variability (represented by its SD) of power per stroke for each stage and device, and between-unit differences, were estimated using general linear mixed modeling and interpreted using rejection of non-substantial and substantial hypotheses. Results: Potential error in mean power was decisively substantial for all devices (Concept2, -11 to -15%; Peach, -7.9 to -17%; EmPower, -32 to -48%; and Weba, -7.9 to -16%). Between-unit differences (as SD) in mean power lacked statistical precision but were substantial and consistent across stages (Peach, ∼5%; EmPower, ∼7%; and Weba, ∼2%). Most differences from the Reference System in stroke-to-stroke variability of power were possibly or likely trivial or small for Peach (-3.0 to -16%), and likely or decisively substantial for EmPower (9.7-57%), and mostly decisively substantial for Weba (61-139%) and the Concept2 (-28 to 177%). Conclusion: Potential negative error in mean power was evident for all devices and units, particularly EmPower. Stroke-to-stroke variation in power showed a lack of measurement sensitivity (apparent smoothing) that was minor for Peach but larger for the Concept2, whereas EmPower and Weba added random error. Peach is therefore recommended for measurement of mean and stroke power.

Relationships between measures of boat acceleration and performance in rowing, with and without controlling for stroke rate and power output.

PURPOSE: Boat acceleration profiles provide a valuable feedback tool by reflecting both rower technique and force application. Relationships between measures of boat acceleration and velocity to inform interpretation of boat acceleration profiles in rowing were investigated here. METHODS: Thirteen male singles, nine female singles, eight male pairs, and seven female pairs participated (national and international level, age 18-27 y). Data from each stroke for 74 2000-m races were collected using Peach PowerLine and OptimEye S5 GPS units. General linear mixed modelling established modifying effects on velocity of two within-crew SD of boat acceleration variables for each boat class, without and with adjustment for stroke rate and power, to identify potential performance-enhancement strategies for a given stroke rate and power. Measures of acceleration magnitude at six peaks or dips, and six measures of the rate of change (jerk) between these peaks and dips were analyzed. Results were interpreted using rejection of non-substantial and substantial hypotheses with a smallest substantial change in velocity of 0.3%. RESULTS: Several boat acceleration measures had decisively substantial effects (-2.4-2.5%) before adjustment for stroke rate and power. Most effect magnitudes reduced after adjustment for stroke rate and power, although maximum negative drive acceleration, peak drive acceleration, jerk during the mid-drive phase, and jerk in the late recovery remained decisively substantial (-1.8-1.9%) in some boat classes. CONCLUSION: Greater absolute values of maximum negative drive acceleration and jerk in the late recovery are related to improved performance, likely reflecting delayed rower centre-of-mass negative acceleration in preparation for the catch. Greater absolute values of peak drive acceleration, first peak acceleration, and jerk in the early and mid-drive are also associated with improved performance, likely reflecting propulsive force during the drive. These proposed mechanisms provide potential strategies for performance enhancement additional to increases in stroke rate and power output.

The Quantification of Acceleration Events in Elite Team Sport: a Systematic Review.

BACKGROUND: Wearable tracking devices are commonly utilised to quantify the external acceleration load of team sport athletes during training and competition. The ability to accelerate is an important attribute for athletes in many team sports. However, there are many different acceleration metrics that exist in team sport research. This review aimed to provide researchers and practitioners with a clear reporting framework on acceleration variables by outlining the different metrics and calculation processes that have been adopted to quantify acceleration loads in team sport research. METHODS: A systematic review of three electronic databases (CINAHL, MEDLINE, SPORTDiscus), was performed to identify peer-reviewed studies that published external acceleration load in elite team sports during training and/or competition. Articles published between January 2010 and April 2020 were identified using Boolean search phrases in relation to team sports (population), acceleration/deceleration (comparators), and competition and/or training (outcome). The included studies were required to present external acceleration and/or deceleration load (of any magnitude) from able-bodied athletes (mean age ≥ 18 years) via wearable technologies. RESULTS: A total of 124 research articles qualified for inclusion. In total, 113/124 studies utilised GPS/GNSS technology to outline the external acceleration load of athletes. Count-based metrics of acceleration were predominant of all metrics in this review (72%). There was a lack of information surrounding the calculation process of acceleration with 13% of studies specifying the filter used in the processing of athlete data, whilst 32% outlined the minimum effort duration (MED). Markers of GPS/GNSS data quality, including horizontal dilution of precision (HDOP) and the average number of satellites connected, were outlined in 24% and 27% of studies respectively. CONCLUSIONS: Team sport research has predominantly quantified external acceleration load in training and competition with count-based metrics. Despite the influence of data filtering processes and MEDs upon acceleration, this information is largely omitted from team sport research. Future research that outlines acceleration load should present filtering processes, MEDs, HDOP, and the number of connected satellites. For GPS/GNSS systems, satellite planning tools should document evidence of available satellites for data collection to analyse tracking device performance. The development of a consistent acceleration filtering method should be established to promote consistency in the research of external athlete acceleration loads.

Corrigendum: Technical Determinants of On-Water Rowing Performance.

[This corrects the article DOI: 10.3389/fspor.2020.589013.].

The road goes ever on and on-a socio-physiological analysis of travel-related issues in Super Rugby.

Air travel is a key factor in Super Rugby and can have a negative influence on players' performance and well-being. The aim of this study was to identify the current practice to reduce the effects of air travel and to understand the rationale behind these interventions. "Travel managers" from eight Super Rugby teams were interviewed and answered a questionnaire. A qualitative description was performed to identify common themes and differences between participants' answers. To protect the privacy and identity of the participants, all data have been de-identified and represented as two fictionalised amalgams (Bob and Peter). The rationale behind each intervention appeared to be based on a mix of anecdotal, practice and, occasionally, literature, confirming that scientific findings are not always easily translatable to applied settings. Two different approaches, clinical (Bob) and holistic (Peter), were identified. Even if both characters acknowledge that travel variables are too many to control, it appears that team culture and practices are perceived as important as biological interventions in controlling the negative effects of travel on players' performance and well-being.

A League-Wide Evaluation of Factors Influencing Match Activity Profile in Elite Australian Football.

Introduction: Accurate interpretation of activity profile data requires an understanding of the variables influencing player movement during matches. Methods: Over 65,000 stints (player rotations) from all 207 matches of the 2018 Australian Football League (AFL) season were evaluated. The relative activity profile including total distance per minute (TD), high-speed running distance per minute (HSR) and Player LoadTM per minute (PL) was determined for each stint and analysed against a range of match-related, player-related and environment-related predictor variables using multivariate linear mixed modelling. Effect size statistics along with the uncertainty in the estimates (95% confidence interval) were used to interpret the findings. Results: The smallest important effects on TD, HSR, and PL were calculated as 1.5%, 5.5%, and 2.4%, respectively. Stint duration had small to moderate negative effects on TD (-6%), PL (-7.7%), and HSR (-13%), while recovery duration between stints had a small positive effect on HSR (+7%). There were moderate reductions in TD (-8%), HSR (-23%), and PL (-9.6%) in the last quarter compared to the first quarter of matches, while similar reductions existed in subsequent stints compared to the first stint in each quarter. Moderate to large differences of up to 9% in TD, 48% in HSR and 12% in PL existed between positions. The TD of less experienced players was slightly higher than their more experienced counterparts (2-3%). A 5% increase in body mass was associated with a small reduction in HSR (-5.5%). There were small reductions in TD (-2%), HSR (-10%), and PL (-3%) during the Finals Series compared to the Premiership Season. Moderate levels of rainfall during matches and higher apparent temperatures had small negative effects on TD (-2%) and HSR (-6 and -9%). The number of days break between matches, score margin, match outcome, ground hardness, ground size, and traveling for the current or the previous match had trivial effects on the activity profile. Conclusion: Player position and stage of the match (quarter) had the largest effects on match activity profile while stint duration, recovery duration, stint timing, professional experience, body mass, stage of the season, and weather conditions also had substantial effects.

Technical Determinants of On-Water Rowing Performance.

Purpose: Research establishing relationships between measures of rowing technique and velocity is limited. In this study, measures of technique and their effect on rowing velocity were investigated. Methods: Ten male singles, eight female singles, three male pairs, and six female pairs participated. Data from each stroke for forty-seven 2,000 m races were collected using Peach PowerLine and OptimEye S5 GPS units. General linear mixed modeling established modifying effects on velocity of two within-crew SD of predictor variables for each boat class, with subsequent adjustment for power, and for power and stroke rate in separate analyses. Twenty-two predictor variables were analyzed, including measures of boat velocity, gate force, and gate angle. Results were interpreted using superiority and inferiority testing with a smallest important change in velocity of 0.3%. Results: Substantial relationships with velocity were found between most variables assessed before adjustment for power, and for power and stroke rate. Effect magnitudes were reduced for most variables after adjustment for power and further reduced after adjustment for stroke rate and power, with precision becoming inadequate in many effects. The greatest modifying effects were found for stroke rate, mean and peak force, and power output before adjustment, and for catch angle after adjustment for stroke rate and power. Substantial between-crew differences in effects were evident for most predictors in some boat classes before adjustment and in some predictors and some boat classes after adjustment for stroke rate and power. Conclusion: The results presented reveal variables associated with improvements in rowing performance and can be used to guide technical analysis and feedback by practitioners. Higher stroke rates and greater catch angles should be targeted to improve rowing performance, and rower force development for the improvement of power output. Relationships between rowing technique and velocity can be crew-dependent and are best assessed on an individual basis for some variables.

Sensitivity, reliability and construct validity of GPS and accelerometers for quantifying peak periods of rugby competition.

Training prescription and monitoring of team-sport athletes rely on accurate quantification of player movement. Our aim was to determine the sensitivity, reliability and construct validity of measures derived from a wearable device incorporating Global Positioning System (GPS) and accelerometer technology to quantify the peak periods of rugby competition. Match movement data were collected from 30 elite and 30 sub-elite rugby union players across respective competitive seasons. Accelerometer and GPS measures were analysed using a rolling average to identify peak movement for epochs ranging from 5 to 600 seconds. General linear mixed modelling was used to quantify the effects of playing position and match-half on the peak movement and variabilities within and between players represented reliability of each measure. Mean positional differences and match-half changes were assessed via standardisation and magnitude-based decisions. Sensitivity of measures was quantified via evaluation of ("signal") and typical error of measurement ("noise"). GPS and accelerometer measures had poor sensitivity for quantifying peak movement across all epochs and both levels of rugby union competition (noise 4× to 5× the signal). All measures displayed correspondingly low reliability across most epochs and both levels of competition (ICC<0.50). Construct validity was evident in mean differences between playing positions and match halves that were consistent with expected activity profiles in rugby union. However, it was clear from the pattern of differences across epoch durations and levels of competition that GPS and accelerometer measures provided different information about player movement. The poor sensitivity and low reliability of GPS and accelerometer measures of peak movement imply that rugby union players need to be monitored across many matches to obtain adequate precision for assessing individuals. Although all measures displayed construct validity, accelerometers provided meaningful information additional to that of GPS. We recommend using accelerometers alongside GPS to monitor and prescribe match respresentative training.

Muscle oxygenation maintained during repeated-sprints despite inspiratory muscle loading.

A high work of breathing can compromise limb oxygen delivery during sustained high-intensity exercise. However, it is unclear if the same is true for intermittent sprint exercise. This project examined the effect of adding an inspiratory load on locomotor muscle tissue reoxygenation during repeated-sprint exercise. Ten healthy males completed three experiment sessions of ten 10-s sprints, separated by 30-s of passive rest on a cycle ergometer. The first two sessions were "all-out' efforts performed without (CTRL) or with inspiratory loading (INSP) in a randomised and counterbalanced order. The third experiment session (MATCH) consisted of ten 10-s work-matched intervals. Tissue saturation index (TSI) and deoxy-haemoglobin (HHb) of the vastus lateralis and sixth intercostal space was monitored with near-infrared spectroscopy. Vastus lateralis reoxygenation (ΔReoxy) was calculated as the difference from peak HHb (sprint) to nadir HHb (recovery). Total mechanical work completed was similar between INSP and CTRL (effect size: -0.18, 90% confidence limit ±0.43), and differences in vastus lateralis TSI during the sprint (-0.01 ±0.33) and recovery (-0.08 ±0.50) phases were unclear. There was also no meaningful difference in ΔReoxy (0.21 ±0.37). Intercostal HHb was higher in the INSP session compared to CTRL (0.42 ±0.34), whilst the difference was unclear for TSI (-0.01 ±0.33). During MATCH exercise, differences in vastus lateralis TSI were unclear compared to INSP for both sprint (0.10 ±0.30) and recovery (-0.09 ±0.48) phases, and there was no meaningful difference in ΔReoxy (-0.25 ±0.55). Intercostal TSI was higher during MATCH compared to INSP (0.95 ±0.53), whereas HHb was lower (-1.09 ±0.33). The lack of difference in ΔReoxy between INSP and CTRL suggests that for intermittent sprint exercise, the metabolic O2 demands of both the respiratory and locomotor muscles can be met. Additionally, the similarity of the MATCH suggests that ΔReoxy was maximal in all exercise conditions.

The longest journeys in Super Rugby: 11 years of travel and performance indicators.

Regular air travel is common in sport. The aim of this study was to understand the extent to which travel has affected Super Rugby teams' performance from 2006, the first season with available Key Performance Indicators (KPIs), to 2016. Data were analysed with mixed linear models for the effects of number of time-zones crossed (east or west), travel duration, the away-match disadvantage, difference in ranking, a set of amendments to the laws of Rugby Union in 2008, a change in competition format (introduction of a conference system) in 2011, and a secular trend. In 2006, the predicted combined effects of travelling 24 h across 12 time-zones and playing away were trivial or small and negative but generally unclear for most of the KPIs in both directions of travel. In 2016 more effects were clear, small and negative for westward travel, while most effects for eastward travel were clear, small to moderate and negative. Most KPIs showed small to moderate increases over the 11 years, while difference in ranking, the introduction of new rules and game format led to mostly small changes. Changes in the physical demands of the game, and inadequate recovery time for long-haul travel can explain these effects.

Out of your zone? 21 years of travel and performance in Super Rugby.

The extent to which travel has affected Super Rugby teams' performances was analysed using outcomes of all matches played from the beginning of the competition in 1996 to the end of the 2016 season. Points difference and matches won or lost were predicted with general and generalized mixed linear models. The predictors were the linear effects of number of time zones crossed and travel duration based on the teams' locations for each match and their locations in the previous week. The away-match disadvantage was also estimated, along with trends in all these effects. In 1996 the predicted combined effect of eastward travel across 12 time zones was a reduction of 5.8 points scored per match, resulting in 4.1 more matches lost every 10 matches. Corresponding effects for westward travel were 6.4 points and 3.1 matches. In 2016 effects travelling eastward were 3.7 points and 2.3 matches, whereas travelling westward the effects were 3.7 points and 1.5 matches. These travel effects were due mainly to the away-match disadvantage: 5.7 points and 3.2 matches in 1996; 5.2 points and 2.3 matches in 2016. Teams in Super Rugby are dealing successfully with long-haul travel and should now focus on reducing the away-match disadvantage.

Respiratory muscle oxygenation is not impacted by hypoxia during repeated-sprint exercise.

This study aimed to investigate whether exercise hyperpnoea contributes to an impairment of locomotor muscle oxygenation and performance during repeated-sprint exercise in normoxia and hypoxia. Subjects performed ten 10-s sprints, separated by 30 s of passive rest while breathing either a normoxic (21% O2) or hypoxic (15% O2) gas mixture. Muscle oxygenation of the vastus lateralis and intercostal muscles was examined with near-infrared spectroscopy. Sprint and recovery vastus lateralis deoxyhaemoglobin was elevated in hypoxia by 9.2% (90% confidence interval 0.2 to 18.0) and 14.1% (90% CL 4.9 to 23.3%) compared to normoxia, respectively. There were no clear differences in respiratory muscle deoxyhaemoglobin (-0.1%, 90% CL -2.9 to 0.9%) or oxyhaemoglobin (0.9%, 90% CL -0.8 to 2.6%) between conditions. Maintenance of respiratory muscle oxygenation may contribute to the rise of vastus lateralis deoxyhaemoglobin in hypoxia during intermittent sprint cycling. This manuscript presents data which extends the fact that oxygen competition could be a limiting factor of exercise capacity.

The Individual and Combined Effects of Multiple Factors on the Risk of Soft Tissue Non-contact Injuries in Elite Team Sport Athletes.

Aim: Relationships between athlete monitoring-derived variables and injury risk have been investigated predominantly in isolation. The aim of this study was to evaluate the individual and combined effects of multiple factors on the risk of soft-tissue non-contact injuries in elite team sport athletes. Methods: Fifty-five elite Australian footballers were prospectively monitored over two consecutive seasons. Internal and external training load was quantified using the session rating of perceived exertion and GPS/accelerometry, respectively. Cumulative load and acute-to-chronic workload ratios were derived using rolling averages and exponentially weighted moving averages. History of injuries in the current and previous seasons was recorded along with professional experience, weekly musculoskeletal screening, and subjective wellness scores for individual athletes. Individual and combined effects of these variables on injury risk were evaluated with generalized linear mixed models. Results: High cumulative loads and acute-to-chronic workload ratios were associated with increased risk of injuries. The effects for measures derived using exponentially weighted moving averages were greater than those for rolling averages. History of a recent injury, long-term experience at professional level, and substantial reductions in a selection of musculoskeletal screening and subjective wellness scores were associated with increased risk. The effects of high cumulative loads were underestimated by ~20% before adjusting for previous injuries, whereas the effects of high acute-to-chronic workload ratios were overestimated by 10-15%. Injury-prone players, identified via player identity in the mixed model, were at > 5 times higher risk of injuries compared to robust players (hazard ratio 5.4, 90% confidence limits 3.6-12) despite adjusting for training load and previous injuries. Combinations of multiple risk factors were associated with extremely large increases in risk; for example, a hazard ratio of 22 (9.7-52) was observed for the combination of high acute load, recent history of a leg injury, and a substantial reduction in the adductor squeeze test score. Conclusion: On the basis of our findings with an elite team of Australian footballers, the information from athlete monitoring practices in team sports should be interpreted collectively and used as a part of the injury prevention decision-making process along with consideration of individual differences in risk.