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Dean J. McNamara, Tim J. Gabbett, Geraldine Naughton, Patrick Farhart and Paul Chapman

Purpose:

This study investigated key fatigue and workload variables of cricket fast bowlers and nonfast bowlers during a 7-wk physical-preparation period and 10-d intensified competition period.

Methods:

Twenty-six elite junior cricketers (mean ± SD age 17.7 ± 1.1 y) were classified as fast bowlers (n = 9) or nonfast bowlers (n = 17). Individual workloads were measured via global positioning system technology, and neuromuscular function (countermovement jump [relative power and flight time]), endocrine (salivary testosterone and cortisol concentrations), and perceptual well-being (soreness, mood, stress, sleep quality, and fatigue) markers were recorded.

Results:

Fast bowlers performed greater competition total distance (median [interquartile range] 7049 [3962] m vs 5062 [3694] m), including greater distances at low and high speeds, and more accelerations (40 [32] vs 19 [21]) and had a higher player load (912 [481] arbitrary units vs 697 [424] arbitrary units) than nonfast bowlers. Cortisol concentrations were higher in the physical-preparation (mean ± 90% confidence intervals, % likelihood; d = –0.88 ± 0.39, 100%) and competition phases (d = –0.39 ± 0.30, 85%), and testosterone concentrations, lower (d = 0.56 ± 0.29, 98%), in the competition phase in fast bowlers. Perceptual well-being was poorer in nonfast bowlers during competition only (d = 0.36 ± 0.22, 88%). Differences in neuromuscular function between groups were unclear during physical preparation and competition.

Conclusions:

These findings demonstrate differences in the physical demands of cricket fast bowlers and nonfast bowlers and suggest that these external workloads differentially affect the neuromuscular, endocrine, and perceptual fatigue responses of these players.

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Matthias W. Hoppe, Christian Baumgart, Jutta Bornefeld, Billy Sperlich, Jürgen Freiwald and Hans-Christer Holmberg

The aims of this study were (1) to assess the running activities of adolescent tennis players during match play with respect to velocity, acceleration, and deceleration; (2) to characterize changes in these activities during the course of a match; and (3) to identify potential differences between winners and losers. Twenty well-trained adolescent male athletes (13 ± 1 y) played one simulated match each (giving a total of 10 matches), during which distances covered at different velocity categories (0 to < 1, 1 to < 2, 2 to < 3, 3 to < 4, and ≥ 4 m·s−1) and number of running activities involving high velocity (≥ 3 m·s−1), acceleration (≥ 2 m·s−2), and deceleration (≤ −2 m·s−2) were monitored using a global positioning system (10 Hz). Heart rate was also assessed. The total match time, total distance covered, peak velocity, and mean heart rate were 81.2 ± 14.6 min, 3362 ± 869 m, 4.4 ± 0.8 ms−1, and 159 ± 12 beats min−1, respectively. Running activities involving high acceleration (0.6 ± 0.2 n·min−1) or deceleration (0.6 ± 0.2 n·min−1) were three times as frequent as those involving high velocity (0.2 ± 0.1 n·min−1). No change in the pattern of running activities (P ≥ .13, d ≤ 0.39) and no differences between winners and losers (P ≥ .22, d ≤ 0.53) were evident during match play. We conclude that training of well-trained adolescent male tennis players need not focus on further development of their running abilities, since this physical component of multifactorial tennis performance does not change during the course of a match and does not differ between the winners and losers.

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Aaron T. Scanlan, Daniel M. Berkelmans, William M. Vickery and Crystal O. Kean

Cricket is a popular international team sport with various game formats ranging from long-duration multiday tests to short-duration Twenty20 game play. The role of batsmen is critical to all game formats, with differing physiological demands imposed during each format. Investigation of the physiological demands imposed during cricket batting has historically been neglected, with much of the research focusing on bowling responses and batting technique. A greater understanding of the physiological demands of the batting role in cricket is required to assist strength and conditioning professionals and coaches with the design of training plans, recovery protocols, and player-management strategies. This brief review provides an updated synthesis of the literature examining the internal (eg, metabolic demands and heart rate) and external (eg, activity work rates) physiological responses to batting in the various game formats, as well as simulated play and small-sided-games training. Although few studies have been done in this area, the summary of data provides important insight regarding physiological responses to batting and highlights that more research on this topic is required. Future research is recommended to combine internal and external measures during actual game play, as well as comparing different game formats and playing levels. In addition, understanding the relationship between batting technique and physiological responses is warranted to gain a more holistic understanding of batting in cricket, as well as to develop appropriate coaching and training strategies.

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Heidi R. Thornton, Jace A. Delaney, Grant M. Duthie and Ben J. Dascombe

Purpose:

To investigate the ability of various internal and external training-load (TL) monitoring measures to predict injury incidence among positional groups in professional rugby league athletes.

Methods:

TL and injury data were collected across 3 seasons (2013–2015) from 25 players competing in National Rugby League competition. Daily TL data were included in the analysis, including session rating of perceived exertion (sRPE-TL), total distance (TD), high-speed-running distance (>5 m/s), and high-metabolic-power distance (HPD; >20 W/kg). Rolling sums were calculated, nontraining days were removed, and athletes’ corresponding injury status was marked as “available” or “unavailable.” Linear (generalized estimating equations) and nonlinear (random forest; RF) statistical methods were adopted.

Results:

Injury risk factors varied according to positional group. For adjustables, the TL variables associated most highly with injury were 7-d TD and 7-d HPD, whereas for hit-up forwards they were sRPE-TL ratio and 14-d TD. For outside backs, 21- and 28-d sRPE-TL were identified, and for wide-running forwards, sRPE-TL ratio. The individual RF models showed that the importance of the TL variables in injury incidence varied between athletes.

Conclusions:

Differences in risk factors were recognized between positional groups and individual athletes, likely due to varied physiological capacities and physical demands. Furthermore, these results suggest that robust machine-learning techniques can appropriately monitor injury risk in professional team-sport athletes.

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Tyler L. Goodale, Tim J. Gabbett, Ming-Chang Tsai, Trent Stellingwerff and Jeremy Sheppard

Purpose:

To evaluate the effects of contextual game factors on activity and physiological profiles of international-level women’s rugby sevens players.

Methods:

Twenty international-level female rugby sevens players from the same national team participated in this study. Global positioning system and heart-rate data were collected at 5 World Rugby Women’s Sevens Series events (2013–14 season).

Results:

Total, moderate-speed (0.2–3.5 m/s), and high-speed running (3.5–5.0 m/s) distances were significantly greater in the first half (20.1% ± 4.1%, 17.6% ± 6.9%, 24.5% ± 7.8%), during losses (11.4% ± 6.1%, 6.1% ± 6.4%, 26.9% ± 9.8%), during losses of large magnitudes (≥2 tries) (12.9% ± 8.8%, 6.8% ± 10.0%, 31.2% ± 14.9%), and against top-4 opponents (12.6% ± 8.7%, 11.3% ± 8.5%, 15.5% ± 13.9%). In addition, total distance increased (5.0% ± 5.5%) significantly from day 1 to day 2 of tournaments, and very-high-speed (5.0–6.5 m/s) running distance increased significantly (26.0% ± 14.2%) during losses. Time spent between 90% and 100% of maximum heart rate (16.4% ± 14.5%) and player load (19.0% ± 5.1%) were significantly greater in the second half. No significant differences in physiological or activity profiles were observed between forwards and backs.

Conclusions:

Game half, game outcome, tournament day, opponent rank, and margin of outcome all affected activity profiles, whereas game half affected physiological profiles. No differences in activity or physiological profiles were found between playing positions. Practitioners are advised to develop high-speed running ability in women’s rugby sevens players to prepare them to tolerate the varying factors that affect activity profiles.

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Benjamin M. Jackson, Ted Polglaze, Brian Dawson, Trish King and Peter Peeling

Global positioning system (GPS) devices are commonly used in elite-level team sports as a way of tracking player movements and quantifying workloads. 1 – 3 The data collected from GPS devices are important to coaches, athletes, and scientists, as they provide details about the movement patterns

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Lee Taylor, Christopher J. Stevens, Heidi R. Thornton, Nick Poulos and Bryna C.R. Chrismas

ecologically valid setting. The experimental aims were therefore to use a phase-change cooling vest within elite WRSS players during an externally valid match-day warm-up. Specifically, the performance (countermovement jump [CMJ]), physical (global positioning system [GPS] metrics), and psychophysiological

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Pedro Figueiredo, George P. Nassis and João Brito

perceived exertion (s-RPE). Players also used 10-Hz global positioning system (GPS) pods during training sessions (Viper Pod; STATSports, Newry, Northern Ireland). External load variables included total training time, total distance covered, distance covered per minute, high-speed distance (>14.4 km

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Liam Anderson, Graeme L. Close, Ryland Morgans, Catherine Hambly, John Roger Speakman, Barry Drust and James P. Morton

contractions etc) that are not often considered when using global positioning system (GPS) data to make inferences of daily EE. Methods Overview of the Player The player is a 27-year old male professional GK (body mass 85.6 kg, height 191 cm from a headless scan, percentage body fat 11.9%, fat mass 9.8 kg

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Jeroen de Bruijn, Henk van der Worp, Mark Korte, Astrid de Vries, Rick Nijland and Michel Brink

Corporation, Annapolis, MD, US). This system consists of a chest strap, a data module, GPS-trackers, and a laptop including Zephyr ™ software. The chest strap has the ability to measure heart rate due to 2 electrocardiogram (ECG) sensors and the GPS trackers can be easily attached to the chest strap using an