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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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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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Adam Jones, Richard Page, Chris Brogden, Ben Langley and Matt Greig

surfaces, 1 with the task chosen to reflect the common mechanism of injury in soccer. The influence of playing surface on injury risk might, therefore, be specific to injury site and type, in part explaining the equivocal nature of the epidemiology literature. Contemporary developments in GPS

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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

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Tannath J. Scott, Heidi R. Thornton, Macfarlane T.U. Scott, Ben J. Dascombe and Grant M. Duthie

Advancements in technology have led to the extensive implementation of global positioning systems (GPS) and microtechnology in team sports to quantify movement demands. The ability to more reliably quantify and interpret these demands has led to a greater understanding of the external loads

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

sessions and matches were quantified using GPS units at a sampling rate of 5 Hz, interpolated to 15 Hz (SPI HPU, GPSports, Canberra, Australia). These were placed in a custom-made pouch in a vest positioned between the scapulae of the upper back. These units are deemed valid and reliable for quantifying

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Darcy M. Brown, Dan B. Dwyer, Samuel J. Robertson and Paul B. Gastin

The purpose of this study was to assess the validity of a global positioning system (GPS) tracking system to estimate energy expenditure (EE) during exercise and field-sport locomotor movements. Twenty-seven participants each completed a 90-min exercise session on an outdoor synthetic futsal pitch. During the exercise session, they wore a 5-Hz GPS unit interpolated to 15 Hz and a portable gas analyzer that acted as the criterion measure of EE. The exercise session was composed of alternating 5-minute exercise bouts of randomized walking, jogging, running, or a field-sport circuit (×3) followed by 10 min of recovery. One-way analysis of variance showed significant (P < .01) and very large underestimations between GPS metabolic power– derived EE and oxygen-consumption (VO2) -derived EE for all field-sport circuits (% difference ≈ –44%). No differences in EE were observed for the jog (7.8%) and run (4.8%), whereas very large overestimations were found for the walk (43.0%). The GPS metabolic power EE over the entire 90-min session was significantly lower (P < .01) than the VO2 EE, resulting in a moderate underestimation overall (–19%). The results of this study suggest that a GPS tracking system using the metabolic power model of EE does not accurately estimate EE in field-sport movements or over an exercise session consisting of mixed locomotor activities interspersed with recovery periods; however, is it able to provide a reasonably accurate estimation of EE during continuous jogging and running.