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Table 1: Descriptive statistics (mean ± SD) for GPS and S-RPE variables measured over 2 months

RELATIONSHIPS BETWEEN SESSION-RPE, GPS MOVEMENT CHARACTERISTICS, AND HEART RATE DURING TRAINING AMONG ELITE YOUTH SOCCER PLAYERS Kevin Lamb 1 & Gregory Doncaster 1,2 1 Department of Sport and Exercise Sciences, University of Chester, UK, & 2 Stoke City FC, UK. Results.

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Table 1: Descriptive statistics (mean ± SD) for GPS and S-RPE variables measured over 2 months

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  1. RELATIONSHIPS BETWEEN SESSION-RPE, GPS MOVEMENT CHARACTERISTICS, AND HEART RATE DURING TRAINING AMONG ELITE YOUTH SOCCER PLAYERS Kevin Lamb1 & Gregory Doncaster1,2 1Department of Sport and Exercise Sciences, University of Chester, UK, & 2Stoke City FC, UK Results Session-RPE has emerged in recent years as a useful subjective method of quantifying training intensity in elite team sports. When expressed as a product of training duration (‘training load’), its validity against objective markers of volume and intensity in soccer has been advocated (e.g. Alexiou & Coutts, 2008; Impellizzeri et al., 2004). But to-date, no study has examined its validity against specific movement characteristics, including distance covered in high intensity activity, quantified via GPS technology, and its variability across positional groups. Therefore the aim of this study was to examine the relationships between session-RPE training load, GPS movement variables measures, and an objective heart rate load among elite youth soccer players. Introduction Table 1: Descriptive statistics (mean ± SD) for GPS and S-RPE variables measured over 2 months • Midfielders were distinctive in that they registered greater distances (absolute and relative), player loads, and session RPEs than the Defenders and Attackers (see Table 1), but less sprinting and time spent at >85% HRmax. • In addition, Midfielders’ S-RPE TL was approx. 10% higher than both other positions. Figure 1. Modified Borg CR-10 scale Figure 2. Catapult GPS unit • Session-RPE was positively and significantly (p< .001) correlated with GPS variables(r = 0.28-0.63) and time spent above 85% HRmax (r = 0.45). • Similar relationships were observed for S-RPE TL (see Table 2), with correlations typically highest among the Midfielders, and lowest for the Attackers. • Correlations with 4 GPS variables were significantly larger (p< .01) than the HR variable. Methods • Participants and Design • 13 elite soccer players, aged 16-18 years old (17.6 ± 0.6 y, 182.5 ± 4.9 cm, 77.2 ± 5.9 kg) from the Stoke City F.C. youth academy, England. • Players were classified as Defenders(n = 4), Midfielders(n = 4) and Attackers(n = 5). • Players provided informed consent and the study was approved by a University of Chester research ethics committee. • Repeated measures design conducted over two monthsduring the season. • All participants completed multiple, coach-led training (small-sided games) sessions (mean = 30.1, range = 23 to 36), generating ‘typical’ data. • Procedures • The players wore a 2 Hz Catapult GPS (Catapult, Melbourne, Au) device and HR monitor (VantageNV, Polar Electro, Kempele, Finland) for all sessions. • Post-training, GPS and HR data were downloaded using Logan Plus (version 4.2.3) software. The GPS variables extracted were: • (i) total distance covered (m) • (ii) high speed running (HSR) at >15 km/h (m) • (iii) sprinting >25 km/h (m) • (iv) percentage (%) of HSR per session • (v) meters per minute (m/min) • (vi) GPS-derived ‘player load’ (au),plus • (vii) minutes spent > 85% maximal heart rate • (>85%HRmax) • 30 minutes after each session, a RPE score (Figure 1) was obtained from each player and multiplied by the duration of the session to give a session-RPE training load (S-RPE TL). • Statistical Analysis • Means (+/- SD) were calculated for all dependent variables for the whole sample and by position (Table 1). • Relationships between S-RPE TL and all other variables were examined via Pearson’s product moment correlations (Table 2). • Correlations were compared using Fisher’s Z-transformations.   Conclusions • These findings provide evidence that session-RPE TL is a valid, inexpensive measure for quantifying global training load within elite youth soccer players and can distinguish between the efforts of positional groups. • The correlations observed with GPS measures of external load reinforce those recently reported among studies of professional (Scott et al., 2013) and semi-professional (Casamichana et al., 2013) adult soccer players. • The utility of session-RPE TL for monitoring training load and potentially aiding in the development of suitable training strategies (for the whole squad and specific player-positions), has been reinforced. References • Alexiou, H, Coutts, A (2008). A comparison of methods used for quantifying internal training load in women • soccer players. Int J Sports PhysiolPerf, 3, 320-30. • Casamichina, D, Castellano, J, Calleja-Gonzalez, J, San Roman, J, Castagna, C (2013). Relationship between • indicators of training load in soccer players. J Strength Cond Res, 27, 369-74. • Impellizzeri, F, Rampinini, E, Coutts, A, Sassi, A, Marcora, S (2004). Use of RPE-based training load in soccer. Med Sci Sports Exerc, 36, 1042-7. • Scott, BR, Lockie, RG, Knight, TJ, Clark, AC, Janse de Jonge, X (2013). A comparison of methods to quantify the in-season training load of professional soccer players.Int J Sports PhysiolPerf, 8, 195-202. Contact: k.lamb@chester.ac.uk or Greg Doncaster 0810282@chester.ac.uk

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