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Arne Jaspers, Tim Op De Beéck, Michel S. Brink, Wouter G.P. Frencken, Filip Staes, Jesse J. Davis, and Werner F. Helsen

into high-level categories related to duration, distance, speed, acceleration and deceleration, PlayerLoad (ie, a metric based on accelerometry), 15 and repeated high-intensity effort activity (Table  1 ). The first goal was to identify the ELIs that are most predictive of the RPE. Therefore, a model

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Joseph O.C. Coyne, Sophia Nimphius, Robert U. Newton, and G. Gregory Haff

sessional ratings of perceived exertion and session duration ( t ). 16 For OS, external TL TRIMP was the product of PlayerLoad/minute derived from Catapult accelerometers and session duration ( t ). 17 PlayerLoad is an arbitrary unit derived from triaxial measures of rate of change in acceleration. 18

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Callum J. McCaskie, Warren B. Young, Brendan B. Fahrner, and Marc Sim

distance, m Total distance covered ≥0.0 m·s −1  Total run distance, m Total distance covered ≥1.7 m·s −1  Total high-speed running distance, m Total distance covered ≥5.5 m·s −1  Total sprint distance, m Total distance covered ≥7.0 m·s −1  Total PlayerLoad, au Total PlayerLoad accumulated  Total duration

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Patrick C. Maughan, Niall G. MacFarlane, and Paul A. Swinton

specific speed thresholds, are now common in professional team sports 2 – 4 as well as accelerometer-based metrics, such as PlayerLoad™ (PL; Catapult Sports, Melbourne, Australia). 3 In contrast to external measures of training load, rating of perceived exertion (RPE) has been shown to be useful as a tool

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Dan Weaving, Clive Beggs, Nicholas Dalton-Barron, Ben Jones, and Grant Abt

training days across a training period ( n ). COL indicates collisions; HMP, high metabolic power; HSD, high-speed distance; PC, principal component; PL, PlayerLoad; TD, total distance; VHSD, very high-speed distance. For example, Weaving et al 19 reported that the first PC captured 70% of the total

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Cédric Leduc, Jason Tee, Mathieu Lacome, Jonathon Weakley, Jeremy Cheradame, Carlos Ramirez, and Ben Jones

practical method of fatigue monitoring within team sports. 8 One relevant variable for fatigue monitoring that can be calculated from data obtained via commercially available MEMS units is the sum of instantaneous rate of change from the 3-axis planes (eg, PlayerLoad, force load). Such metrics are

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Nick Dobbin, Anthony Atherton, and Colin Hill

downloaded using Openfield (Catapult Sports) and analyzed for relative total and very low- (0–1 m·s −1 ), low- (1–3 m·s −1 ), moderate- (3–5 m·s −1 ), high- (5–7 m·s −1 ), and very high- (>7 m·s −1 ) intensity distance, 12 relative accelerations and decelerations (>3 m·s −1 ), total PlayerLoad ™ , distance

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Shaun J. McLaren, Jonathan M. Taylor, Tom W. Macpherson, Iain R. Spears, and Matthew Weston

locomotor metrics (eg, total and high-speed running distances) were not considered as reflective external measures. Instead, peak running speed (in km·h −1 ) and total PlayerLoad (PL, arbitrary units [AU]) 17 for each set of 7 sprints were extracted for analysis. Ten hertz MinimaxX global positioning

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

GK GPS device was used to assess external training load (GPS; Optimeye G5; firmware version 717; Catapult Sports, Melbourne, Australia). An additional variable of PlayerLoad TM was included for analysis that presents an arbitrary unit derived from the triaxial accelerometer that measures

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Thomas Mullen, Craig Twist, and Jamie Highton

high-speed running (>14 km·h −1 ), peak speed, sprint to contact speed, PlayerLoad ™ (in arbitrary units), and time at high metabolic power >20 W·kg −1 (in seconds). In a separate in-house investigation, using a sample of 20 university rugby players, the interday coefficient of variation (in