Behind enemy lines: Expressing locomotor movements of athletes in the National Rugby League Women's (NRLW) competition relative to opposition data.

We provide a novel analysis of the locomotor movements of athletes in the National Rugby League Women's (NRLW) competition by presenting the data of opposing teams expressed as a relative (%) difference and explore the association with match outcome. 117 rugby league athletes from the four NRLW clubs participated in this study. Mean speed (m·min-1), mean high-speed running (>12 km·h-1; m·min-1), and mean acceleration (m·s-2) were measured in 12 matches (370 individual match files) using the Global Navigation Satellite System (GNSS). Individual GNSS-derived data from each match-half were summed across each team and the association with total points and the points differential in each match-half was determined using linear mixed models. Greater high-speed running and lower mean acceleration were associated with more points being scored. A greater relative difference in mean high-speed running between competing teams was associated with a higher points differential. That is, if a team completed 10% more high-speed running than their opposition, they were likely to score an average of 3.2 points more during a given match-half. This unique analysis of GNSS-derived data may assist coaches and performance support staff to interpret the locomotor movements of female rugby league players with the appropriate considerations for the opposition team.

Using Small-Sided Games in Field Hockey: Can They Be Used to Reach Match Intensity?

ABSTRACT: Duthie, GM, Thomas, EJ, Bahnisch, J, Thornton, HR, and Ball, K. Using small-sided games in field hockey: Can they be used to reach match intensity? J Strength Cond Res 36(2): 498-502, 2022-Small-sided games (SSGs) are commonly used in field hockey to replicate or overload physical and tactical competition demands; however, little evidence is available regarding if specific SSG formats achieve this. This research investigated how speed and acceleration differed between 5-minute SSG formats (2v2, 3v3, and 4v4) and also compared with competition. Elite male field hockey athletes (n = 10) participated in the SSGs with standard rules, on pitches of 30 × 20, 35 × 25, and 40 × 30 m, respectively (∼150 m2 per athlete excluding goal keepers). Global Positioning System devices measured speed (m·min-1) and acceleration (m·s-2). Differences between mean speed and acceleration during SSGs and 5-minute maximal mean values from competition (calculated using moving averages) were quantified using linear mixed models and described using standardized effect sizes (ES) and 90% confidence intervals. Between SSG formats, there were nonsubstantial differences for mean speed and acceleration (ES range -0.4 to 0.8). Compared with competition, mean speed was substantially lower for all SSG formats (ES range -1.4 to -1.8), whereas mean acceleration was higher (ES range 3.9-4.8). The SSG formats examined had a lower mean speed and higher mean acceleration than the maximal mean observed in competition. Therefore, these SSGs are an effective training drill for the development and overload of acceleration. However, manipulating SSG constraints to expose athletes to the maximal mean competition speed is required.

Quantifying the Movement Characteristics of Australian Football League Women's Competition.

ABSTRACT: Thornton, HR, Armstrong, CR, Gamble, T, Rigby, A, Johnston, RD, and Duthie, GM. Quantifying the movement characteristics of Australian Football League Women's competition. J Strength Cond Res 36(12): 3415-3421, 2022-The purpose is to provide an overview of the externally measured movement characteristics of Australian Football League Women's (AFLW) competition, and the variability in this between matches. A range of movement variables were measured from 28 athletes who wore 10-Hz global positioning system devices during games and were summarized according to positional groups. The variance in each athlete's match loads for each round were expressed using standardized scores ( z -scores), and the change compared with the first game played was calculated and expressed as a standard deviation. Furthermore, using the raw export, moving means (1-10 minutes) of speed (m·min -1 ) and acceleration (m·s -2 ) were calculated. Following log transformation of the maximal means, intercept and slopes were calculated. Linear mixed models identified differences between positional groups for match loads, and intercept and slopes. Effects were described using standardized effect sizes (ESs) and magnitude-based decisions. There were no substantial and unclear differences between positional groups for match loads (ES range; ±confidence limits = 0.10-0.80; ±0.30-4.30) and for intercept and slopes (ES range; 0.04-0.44; ±0.52-2.11). Large within-athlete variation in match demands between rounds was observed ( z -score up to -1.8 SD for distance), and the maximal means for speed and acceleration demonstrate the extensive physical demands of AFLW competition. These data describe the intense and variable physical demands of AFLW competition, and further provide novel information regarding the maximal mean intensities and intercept and slopes, which should assist practitioners in planning and prescribing training in preparation for competition.

The Distribution of Match Activities Relative to the Maximal Mean Intensities in Professional Rugby League and Australian Football.

ABSTRACT: Johnston, RD, Thornton, HR, Wade, JA, Devlin, P, and Duthie, GM. The distribution of match activities relative to the maximal mean intensities in professional rugby league and Australian football. J Strength Cond Res 36(5): 1360-1366, 2022-This study determined the distribution of distance, impulse, and accelerometer load accumulated at intensities relative to the maximal mean 1-minute peak intensity within professional rugby league and Australian football. Within 26 rugby league (n = 24 athletes) and 18 Australian football (n = 38 athletes) games, athletes wore global navigation satellite system devices (n = 608 match files). One-minute maximal mean values were calculated for each athlete per game for speed (m·minP-1P), accelerometer load (AU·minP-1P), and acceleration (m·sP-2P). Volumes for each parameter were calculated by multiplying by time, specifying total distance, accelerometer load, and impulse. The distribution of intensity of which these variables were performed relative to the maximal mean was calculated, with percentages ranging from 0-110%, separated into 10% thresholds. Linear mixed models determined whether the distribution of activities within each threshold varied, and positional differences. Effects were described using standardized effect sizes (ESs), and magnitude-based decisions. Across both sports, the distribution of activity (%) largely reduced the closer to the maximal mean 1-minute peak and was highest at ∼60% of the maximal mean peak. When compared with Australian football, a higher percentage of total distance was accumulated at higher intensities (70-80% and 100-110%) for rugby league (ES range = 0.82-0.87), with similar, yet larger differences for accelerometer load >80% (0.78-1.07) and impulse >60% (1.00-2.26). These findings provide information of the volume of activities performed relative to the mean maximal 1-minute peak period, which may assist in the prescription of training.

Relationship Between Physical Performance Testing Results and Peak Running Intensity During Professional Rugby League Match Play.

Duthie, GM, Thornton, HR, Delaney, JA, McMahon, JT, and Benton, DT. Relationship between physical performance testing results and peak running intensity during professional rugby league match play. J Strength Cond Res 34(12): 3506-3513, 2020-The purpose of this study was to examine the relationship between individual athletes' physical characteristics and both the peak running intensities and the decline in peak running intensities during competition. Twenty-two professional rugby league athletes (age; 24.1 ± 4.0 years, body mass; 101.4 ± 9.5 kg) underwent a series of physical testing procedures. Peak running intensity was determined using a moving average technique, applied to the speed (m·min), acceleration/deceleration (m·s), and metabolic power (W·kg) during competition, across 10 different durations. The power law relationship was then established, yielding an intercept and slope for the movement variables. Mixed linear models were then used to determine the relationship between physical characteristics and intercept and slope values. There were large, positive relationships between a player's maximal speed and both peak running speeds (effect size = 0.56, 90% confidence interval: 0.20-0.78) and metabolic power (0.57, 0.21-0.79) during competition. By contrast, there were large, negative associations between maximal speed and the rate of decline in running speed (-0.60, -0.81 to -0.27) and metabolic power (-0.65, -0.83 to -0.32) during competition. Similarly, there were negative associations between relative squat strength and the rate of decline in running speed (moderate: -0.41, -0.69 to -0.04) and metabolic power (large: -0.53, -0.77 to -0.17) during competition. The findings of this study demonstrate that a players running intensity during competition is underpinned by the individual athletes physiological qualities. Athletes demonstrating higher maximal speeds in testing were able to maintain higher running intensities over short durations but had a greater decrease in running intensity as duration increased.

The Validity of a Global Navigation Satellite System for Quantifying Small-Area Team-Sport Movements.

Delaney, JA, Wileman, TM, Perry, NJ, Thornton, HR, Moresi, MP, and Duthie, GM. The validity of a global navigation satellite system for quantifying small-area team-sport movements. J Strength Cond Res 33(6): 1463-1466, 2019-The recent development of global navigation satellite systems (GNSS) has improved the availability and signal strength of surrounding satellites compared with traditional global positioning systems, although their ability to quantify rapid changes in speed may still be limited. This study aimed to evaluate the validity of GNSS to quantify the mean speed (m·s) and acceleration (m·s) of movements typical to team sports. One participant completed 9 periods of 4 minutes of activity, separated by 2-minute rest periods, which involved walking, jogging, and running in a variety of directions and patterns, aimed to simulate a team-sport movement profile. Speed and acceleration were quantified from a 10-Hz GNSS unit and compared with a 10-camera, 3-dimensional motion capture system (VICON), from which the movement of both the participant's center of mass (COM) and the location of the GNSS unit (e.g., C7 vertebrae) were calculated. Practical estimates of speed were associated with small differences from both the criterion COM (effect size; ±90% confidence limits = 0.19-0.25; ± ∼0.21) and criterion C7 (0.14-0.22; ± ∼0.13). The corresponding estimates of acceleration derived from raw data were classified as small (0.16-0.22; ± ∼0.15) and small to moderate (0.25-0.35; ± ∼0.24) for the COM and C7, respectively. Software-exported acceleration values exhibited very large mean bias compared with both criterion measures (-3.81 to -3.77; ± ∼0.24). This study demonstrates that 10-Hz GNSS possess acceptable validity for assessing the average demands of movements typical of team-sports training and competition, although caution is recommended when using software-exported measures of acceleration.

Impact of short- compared to long-haul international travel on the sleep and wellbeing of national wheelchair basketball athletes.

Currently, very little is known about the impact of short- or long-haul air travel on the sleep and wellbeing of wheelchair basketball athletes. Eleven national wheelchair basketball athletes wore actigraphy monitors prior, during, and after air travel to the United Kingdom. Upon arrival, participants rated their subjective jet-lag, fatigue, and vigor. Individuals traveled to the United Kingdom from different locations in Australia, the United States, and Europe and were categorised according to travel length [LONG (up to 30.2 h) or SHORT (up to 6.5 h)]. Linear mixed models determined effects of travel length on sleep and subjective ratings of jet-lag, fatigue, and vigor. During competition, subjective fatigue and jet-lag were substantially higher (ES = 0.73; ±0.77) and (ES = 0.57; ±0.60), subjective vigor was lower (ES = 1.94; ±0.72), and get-up time was earlier (ES = 0.57; ±0.60) for LONG when compared to SHORT. Travelling greater distances by airplane had a larger effect on subjective ratings of jet-lag, fatigue and vigor, rather than sleep. Irrespective of travel group, sleep and subjective responses were compromised, reflecting the travel requirements, competition-mediated influences, and/or due to a change in environment.

Does self-perceived sleep reflect sleep estimated via activity monitors in professional rugby league athletes?

This study examined agreement between self-perceived sleep and sleep estimated via activity monitors in professional rugby league athletes. 63 athletes, from three separate teams wore actigraphy monitors for 10.3 ± 3.9 days. During the monitoring period, ratings of perceived sleep quality (on a 1-5 and 1-10 Likert scale), and an estimate of sleep duration were recorded daily. Agreement between sleep estimated via activity monitors and self-perceived sleep was examined using mean bias, Pearson correlation (r) and typical error of the estimate (TEE). 641 nights of sleep were recorded, with a very large, positive correlation observed between sleep duration estimated via activity monitors and subjective sleep duration (r = 0.85), and a TEE of 48 minutes. Mean bias revealed subjective sleep duration overestimated sleep by an average of 19.8 minutes. The relationship between sleep efficiency estimated via activity monitors and self-perceived sleep quality on a 1-5 (r = 0.22) and 1-10 Likert scale (r = 0.28) was limited. The outcomes of this investigation support the use of subjective measures to monitor sleep duration in rugby league athletes when objective means are unavailable. However, practitioners should be aware of the tendency of athletes to overestimate sleep duration.

Importance, Reliability, and Usefulness of Acceleration Measures in Team Sports.

Delaney, JA, Cummins, CJ, Thornton, HR, and Duthie, GM. Importance, reliability and usefulness of acceleration measures in team sports. J Strength Cond Res 32(12): 3494-3502, 2018-The ability to accelerate, decelerate, and change direction efficiently is imperative to successful team sports performance. Traditional intensity-based thresholds for acceleration and deceleration may be inappropriate for time-series data and have been shown to exhibit poor reliability, suggesting other techniques may be preferable. This study assessed movement data from one professional rugby league team throughout 2 full seasons and 1 preseason period. Using both 5 and 10 Hz global positioning systems (GPS) units, a range of acceleration-based variables were evaluated for their interunit reliability, ability to discriminate between positions, and associations with perceived muscle soreness. The reliability of 5 Hz global positioning systems for measuring acceleration and deceleration ranged from good to poor (CV = 3.7-27.1%), with the exception of high-intensity deceleration efforts (CV = 11.1-11.8%), the 10 Hz units exhibited moderate-to-good interunit reliability (CV = 1.2-6.9%). Reliability of average metrics (average acceleration/deceleration, average acceleration, and average deceleration) ranged from good to moderate (CV = 1.2-6.5%). Substantial differences were detected between positions using time spent accelerating and decelerating for all magnitudes, but these differences were less clear when considering the count or distance above acceleration/deceleration thresholds. All average metrics detected substantial differences between positions. All measures were similarly related to perceived muscle soreness, with the exception of high-intensity acceleration and deceleration counts. This study has proposed that averaging the acceleration/deceleration demands over an activity may be a more appropriate method compared with threshold-based methods, because a greater reliability between units, while not sacrificing sensitivity to within-subject and between-subject changes.

Running Intensities in Elite Youth Soccer by Age and Position.

Duthie, GM, Thornton, HR, Delaney, JA, Connolly, DR, and Serpiello, FR. Running intensities in elite youth soccer by age and position. J Strength Cond Res 32(10): 2918-2924, 2018-The purpose of this investigation was to examine differences between the peak running speed, acceleration, and metabolic power of elite youth soccer across a range of age levels by position. Ninety-six elite junior soccer players were assessed between 2015 and 2017. Ninety-six elite junior soccer players (at time of match: age, 15.8 ± 0.9 years; body mass, 69.1 ± 8.0 kg) were assessed during 61 games within the 2015, 2016, and 2017 season, for a total of 441 individual match observations (4.8 ± 3.3 matches per player, range 1-13). Participants were classified by age group: under 15 (U15, n = 121, 14.7 ± 0.3 years), under 16 (U16, n = 176, 15.8 ± 0.3 years), or under 17 (U17, n = 144, 16.7 ± 0.4 years), and according to their playing position: Attacker (ATT), Defender (DEF), Mid-Fielder (MID), or Wide (WIDE). Participants wore global positioning system units during each match, where speed (m·min), acceleration/deceleration (m·s), and metabolic power (Pmet) were established. A 1- to 10-minute moving average was applied to establish the intercept (c) and slope (n) of running intensity variables as a power law y = cx relationship. Linear mixed models were used to examine differences in the intercept and slope between age group and player position. There were no substantial differences in peak (intercept) or decline (slope) in running intensity between playing levels. Several differences were observed in the peak running speeds (m·min), particularly peak running speeds of ATT and DEF being substantially lower than the MID. Despite variability between positions, we suggest that the magnitude of these differences would not warrant the prescription of different running intensities across positions at the elite junior level. These findings describe the peak running intensities of elite junior soccer, useful in the monitoring and prescription of training to ensure that players are prepared for the most demanding periods of competition.

The introduction of the six-again rule has increased acceleration intensity across all positions in the National Rugby League competition.

The impact of the six-again rule change on the movement of National Rugby League (NRL) athletes was examined. Player Global Navigation Satellite System (GNSS) data (10 Hz) was collected from 42 athletes who competed in 56 matches across the 2019 to 2021 NRL seasons. Maximal mean speed (m·min-1) and acceleration (m·s-2) were established across a 10 s to 10-min duration via raw GNSS files, with subsequent intercept (mean estimates) and slope values determined via power law analysis. The distributions of match distance (m) and impulse (kN·s-1) were established during ball-in-play time. To determine the significance between positions and seasons under different rules, linear mixed models were used. Effects were described using standardised effect sizes (ES) with 90% confidence limits (CL). Acceleration intercepts (power law-derived) across all positions were substantially greater (>0.6 SD) following the introduction of the six-again rule in the 2020 (mean ± SD; 1.02 ± 0.10 m·s-2) and 2021 seasons (1.05 ± 0.08 m·s-2) compared to the 2019 season (0.91 ± 0.07 m·s-2). Mean acceleration during ball-in-play time was greater in 2020 (ES; 90% CL = 0.75; ± 0.32) compared to 2019. The acceleration requirements of rugby league increased across all positional groups following the modification in NRL competition rules. Practitioners should tailor training programs for athletes to reflect the increased acceleration intensity found under the revised competition format.

Sleep Hygiene and Light Exposure Can Improve Performance Following Long-Haul Air Travel.

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

DXA-derived estimates of energy balance and its relationship with changes in body composition across a season in team sport athletes.

This study examined the relationship between dual-energy x-ray absorptiometry (DXA)-derived estimates of energy balance (EB) and changes in body composition across various seasonal phases in team sport athletes. Forty-five Australian rules footballers underwent six DXA scans across a 12-month period (off-season [OS, Week 0-13], early [PS1, Week 13-22] and late pre-season [PS2, Week 22-31] and early [IS1, Week 3-42] and late in-season [IS2, Week 42-51]). EB (kcal·day-1) was estimated from changes in fat free soft tissue mass (FFSTM) and fat mass (FM) between scans according to a validated formula. An EB threshold of ± 123 kcal·day-1 for >60 days demonstrated a very likely (>95% probability) change in FFSTM (>1.0 kg) and FM (>0.7 kg). There were small to almost perfect relationships between EB and changes in FM (r = 0.97, 95% CI, 0.96-0.98), FFSTM (r = -0.41, -0.92 to -0.52) and body mass (r = 0.27, 0.14-0.40). EB was lowest during PS1 compared to all other phases (range, -265 to -142 kcal·day-1), with no other changes at any time. Increases in FFSTM were higher during OS compared to PS2 (1.6 ± 0.4 kg), and higher during PS1 compared to PS2, IS1, and IS2 (range, 1.6-2.1 kg). There were no changes during in-season (-0.1-0.05 kg). FM decreased only in PS1 compared to all other seasonal phases (-1.8 to -1.0 kg). Assessments of body composition can be used as a tool to estimate EB, which practically can be used to indicate athlete's training and nutrition behaviours/practices.

Greater Association of Relative Thresholds Than Absolute Thresholds With Noncontact Lower-Body Injury in Professional Australian Rules Footballers: Implications for Sprint Monitoring.

Sprint capacity is an important attribute for team-sport athletes, yet the most appropriate method to analyze it is unclear. PURPOSE: To examine the relationship between sprint workloads using relative versus absolute thresholds and lower-body soft-tissue and bone-stress injury incidence in professional Australian rules football. METHODS: Fifty-three professional Australian rules football athletes' noncontact soft-tissue and bone-stress lower-body injuries (N = 62) were recorded, and sprint workloads were quantified over ∼18 months using the global positioning system. Sprint volume (m) and exposures (n) were determined using 2 methods: absolute (>24.9 km·h-1) and relative (≥75%, ≥80%, ≥85%, ≥90%, ≥95% of maximal velocity). Relationships between threshold methods and injury incidence were assessed using logistic generalized additive models. Incidence rate ratios and model performances' area under the curve were reported. RESULTS: Mean (SD) maximal velocity for the group was 31.5 (1.4), range 28.6 to 34.9 km·h-1. In comparing relative and absolute thresholds, 75% maximal velocity equated to ~1.5 km·h-1 below the absolute speed threshold, while 80% and 85% maximal velocity were 0.1 and 1.7 km·h-1 above the absolute speed threshold, respectively. Model area under the curve ranged from 0.48 to 0.61. Very low and very high cumulative sprint loads ≥80% across a 4-week period, when measured relatively, resulted in higher incidence rate ratios (2.54-3.29), than absolute thresholds (1.18-1.58). DISCUSSION: Monitoring sprinting volume relative to an athlete's maximal velocity should be incorporated into athlete monitoring systems. Specifically, quantifying the distance covered at >80% maximal velocity will ensure greater accuracy in determining sprint workloads and associated injury risk.

Alterations in core temperature during World Rugby Sevens Series tournaments in temperate and warm environments †.

PURPOSE: To characterize player core temperature (Tc) across two separate World Rugby Sevens Series (WRSS) tournaments in temperate and warm environments. METHODS: Tc was collected in seventeen playing members of one men's team competing at the Singapore (n = 12) and London (n = 11) WRSS tournaments. Exertional heat illness (EHI) symptoms, cooling strategy use, playing minutes and wet blub globe temperature (WBGT) were also collected. Linear mixed models and magnitude-based inferences assessed differences in Tc between all periods within-and between tournaments and were also used to assess the effect of WBGT and playing minutes on Tc. RESULTS: Several players experienced Tc in excess of 38°C during warm-ups and 39°C during games. The highest mean Tc values were observed in the final game on all days and in Singapore Day Two, there were substantial game-on-game increases in mean Tc. These Tc responses were associated with playing minutes (effect size; ±90% CL = 0.38; ±0.20), although the effect of WBGT was trivial and unclear. Further, there were no differences in Tc between the two tournaments in the different environments. Despite high individual peak Tc values (Singapore 39.9°C; London 39.6°C); no signs/symptoms of EHI were reported, voluntary post-game cooling usage was minimal, and pre- and mid-cooling strategies were not implemented. CONCLUSIONS: During WRSS matches, peak Tc values approached thresholds associated with EHI (>40°C) and exceeded those demonstrated to reduce repeated sprint performance (>39°C). Practitioners may consider the use of compatible cooling and heat acclimation strategies to minimize Tc increase and maximize player preparedness and recovery.

Limiting the Rise in Core Temperature During a Rugby Sevens Warm-Up With an Ice Vest.

PURPOSE: To determine how a cooling vest worn during a warm-up could influence selected performance (countermovement jump [CMJ]), physical (global positioning system [GPS] metrics), and psychophysiological (body temperature and perceptual) variables. METHODS: In a randomized, crossover design, 12 elite male World Rugby Sevens Series athletes completed an outdoor (wet bulb globe temperature 23-27°C) match-specific externally valid 30-min warm-up wearing a phase-change cooling vest (VEST) and without (CONTROL), on separate occasions 7 d apart. CMJ was assessed before and after the warm-up, with GPS indices and heart rate monitored during the warm-ups, while core temperature (Tc; ingestible telemetric pill; n = 6) was recorded throughout the experimental period. Measures of thermal sensation (TS) and thermal comfort (TC) was obtained pre-warm-up and post-warm-up, with rating of perceived exertion (RPE) taken post-warm-ups. RESULTS: Athletes in VEST had a lower ΔTc (mean [SD]: VEST = 1.3°C [0.1°C]; CONTROL = 2.0°C [0.2°C]) from pre-warm-up to post-warm-up (effect size; ±90% confidence limit: -1.54; ±0.62) and Tc peak (mean [SD]: VEST = 37.8°C [0.3°C]; CONTROL = 38.5°C [0.3°C]) at the end of the warm-up (-1.59; ±0.64) compared with CONTROL. Athletes in VEST demonstrated a decrease in ΔTS (-1.59; ±0.72) and ΔTC (-1.63; ±0.73) pre-warm-up to post-warm-up, with a lower RPE post-warm-up (-1.01; ±0.46) than CONTROL. Changes in CMJ and GPS indices were trivial between conditions (effect size < 0.2). CONCLUSIONS: Wearing the vest prior to and during a warm-up can elicit favorable alterations in physiological (Tc) and perceptual (TS, TC, and RPE) warm-up responses, without compromising the utilized warm-up characteristics or physical-performance measures.

Developing Athlete Monitoring Systems in Team Sports: Data Analysis and Visualization.

In professional team sports, the collection and analysis of athlete-monitoring data are common practice, with the aim of assessing fatigue and subsequent adaptation responses, examining performance potential, and minimizing the risk of injury and/or illness. Athlete-monitoring systems should be underpinned by appropriate data analysis and interpretation, to enable the rapid reporting of simple and scientifically valid feedback. Using the correct scientific and statistical approaches can improve the confidence of decisions made from athlete-monitoring data. However, little research has discussed and proposed an outline of the process involved in the planning, development, analysis, and interpretation of athlete-monitoring systems. This review discusses a range of methods often employed to analyze athlete-monitoring data to facilitate and inform decision-making processes. There is a wide range of analytical methods and tools that practitioners may employ in athlete-monitoring systems, as well as several factors that should be considered when collecting these data, methods of determining meaningful changes, and various data-visualization approaches. Underpinning a successful athlete-monitoring system is the ability of practitioners to communicate and present important information to coaches, ultimately resulting in enhanced athletic performance.

Interunit Reliability and Effect of Data-Processing Methods of Global Positioning Systems.

PURPOSE: To establish the interunit reliability of a range of global positioning system (GPS)-derived movement indicators, to determine the variation between manufacturers, and to investigate the difference between software-derived and raw data. METHODS: A range of movement variables were obtained from 27 GPS units from 3 manufacturers (GPSports EVO, 10 Hz, n = 10; STATSports Apex, 10 Hz, n = 10; and Catapult S5, 10 Hz, n = 7) that measured the same team-sport simulation session while positioned on a sled. The interunit reliability was determined using the coefficient of variation (%) and 90% confidence limits, whereas between-manufacturers comparisons and comparisons of software versus raw processed data were established using standardized effect sizes and 90% confidence limits. RESULTS: The interunit reliability for both software and raw processed data ranged from good to poor (coefficient of variation = 0.2%; ±1.5% to 78.2%; ±1.5%), with distance, speed, and maximal speed exhibiting the best reliability. There were substantial differences between manufacturers, particularly for threshold-based acceleration and deceleration variables (effect sizes; ±90% confidence limits: -2.0; ±0.1 to 1.9; ±0.1), and there were substantial differences between data-processing methods for a range of movement indicators. CONCLUSIONS: The interunit reliability of most movement indicators was deemed as good regardless of processing method, suggesting that practitioners can have confidence within systems. Standardized data-processing methods are recommended, due to the large differences between data outputs from various manufacturer-derived software.

Long-Haul Northeast Travel Disrupts Sleep and Induces Perceived Fatigue in Endurance Athletes.

Introduction: Long-haul transmeridian travel is known to cause disruptions to sleep and immune status, which may increase the risk of illness. Aim: This study aimed to determine the effects of long-haul northeast travel for competition on sleep, illness and preparedness in endurance athletes. Methods: Twelve trained (13.8 ± 3.2 training h/week) masters (age: 48 ± 14 years) triathletes were monitored for sleep (quantity via actigraphy and quality via self-report), mucosal immunity (salivary immunoglobulin-A) and stress (salivary cortisol) as well as self-reported illness, fatigue, recovery and preparedness. Baseline measures were recorded for 2 weeks prior to travel for all variables except for the saliva samples, which were collected on three separate days upon waking. Participants completed normal training during the baseline period. Measures were subsequently recorded before, during and after long-haul northeast travel from the Australian winter to the Hawaiian summer, and in the lead up to an Ironman 70.3 triathlon. Results: All comparisons are to baseline. There was a most likely decrease in sleep duration on the over-night flight (-4.8 ± 1.2 h; effect size; ±90% confidence limits = 3.06; ±1.26) and a very likely increase in sleep duration on the first night after arrival (0.7 ± 1.0 h; 1.15; ±0.92). After this time, sleep duration returned to baseline for several days until it was very likely decreased on the night prior to competition (-1.2 ± 1.0 h; 1.18; ±0.93). Nap duration was likely increased on the first day after arrival (36 ± 65 min; 3.90; ±3.70). There was also a likely increase in self-reported fatigue upon waking after the first night in the new destination (1.1 ± 1.6 AU; 0.54; ±0.41) and there were three athletes (25%) who developed symptoms of illness 3-5 days after arrival. There were no changes in sleep quality or mucosal measures across study. Discussion: Long-haul northeast travel from a cool to a hot environment had substantial influences on sleep and self-reported fatigue, but these alterations had returned to pre-departure baseline 48 h after arrival. Endurance athletes undertaking similar journeys may benefit from optimizing sleep hygiene, especially on the first 2 days after arrival, or until sleep duration and fatigue levels return to normal.

Effects of Preseason Training on the Sleep Characteristics of Professional Rugby League Players.

PURPOSE: To investigate the influence of daily and exponentially weighted moving training loads on subsequent nighttime sleep. METHODS: Sleep of 14 professional rugby league athletes competing in the National Rugby League was recorded using wristwatch actigraphy. Physical demands were quantified using GPS technology, including total distance, high-speed distance, acceleration/deceleration load (SumAccDec; AU), and session rating of perceived exertion (AU). Linear mixed models determined effects of acute (daily) and subacute (3- and 7-d) exponentially weighted moving averages (EWMA) on sleep. RESULTS: Higher daily SumAccDec was associated with increased sleep efficiency (effect-size correlation; ES = 0.15; ±0.09) and sleep duration (ES = 0.12; ±0.09). Greater 3-d EWMA SumAccDec was associated with increased sleep efficiency (ES = 0.14; ±0.09) and an earlier bedtime (ES = 0.14; ±0.09). An increase in 7-d EWMA SumAccDec was associated with heightened sleep efficiency (ES = 0.15; ±0.09) and earlier bedtimes (ES = 0.15; ±0.09). CONCLUSIONS: The direction of the associations between training loads and sleep varied, but the strongest relationships showed that higher training loads increased various measures of sleep. Practitioners should be aware of the increased requirement for sleep during intensified training periods, using this information in the planning and implementation of training and individualized recovery modalities.