RELATIONSHIPS BETWEEN SESSION-RPE, GPS MOVEMENT CHARACTERISTICS,
AND HEART RATE DURING TRAINING AMONG ELITE YOUTH SOCCER PLAYERS
1
Lamb
1,2
Doncaster
Kevin
& Gregory
1Department of Sport and Exercise Sciences, University of Chester, UK, & 2Stoke City FC, UK
Results
Introduction
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.
Figure 1. Modified Borg
CR-10 scale
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.
Total
Players
Distance
(m)
5946.2 ±
Total
1753.1
5781.3 ±
Defenders
1735.2
6140.1 ±
Midfielders
1718.9
5894.0 ±
Attackers
1788.0
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
months during 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.
HSR
(%)
6.9 ±
5.5
6.5 ±
5.5
6.8 ±
5.1
7.2 ±
5.6
Relative
Distance
(m/min)
66.4 ±
17.9
63.6 ±
19.9
68.4 ±
15.9
67.1 ±
19.9
> 85%
HRmax
(min)
16.52 ±
12:07
17:22 ±
11:43
14:28 ±
11:15
17:59 ±
12:35
Session
Session S-RPE TL
Duration
-RPE Load (au)
(min)
90.0 ±
4.2 ±
387 ± 204
15.7
1.8
91.0 ±
3.7 ±
354 ± 198
15.0
1.7
89.9 ±
4.5 ±
423 ± 215
15.6
1.9
89.2 ±
4.2 ±
384 ± 198
16.3
1.7
• 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.
Table 1: Descriptive statistics (mean ± SD) for GPS and S-RPE variables measured over 2 months
Figure 2. Catapult GPS unit
Methods
Participants and Design
Player
HSR Sprint
Load
(m)
(m)
(au)
458.5 ± 7.7 ± 658 ±
459.9
23.2
185
425.9 ± 8.8 ± 619 ±
461.8
26.4
176
457.6 ± 6.9 ± 707 ±
407.1
24.8
186
469.0 ± 7.2 ± 648 ±
471.7
19.1 185.0
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 Ztransformations.
 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.
Total
Distance
HSR
Total
.58*a
.59*a
.33*
.64*a
.57*a
.19*
.46*
Defenders
.58*
.66*
.49*
.65*
.67*a
.22
.58*
Midfielders
.70*a
.75*a
.33*
.74*a
.67*a
.32*
.59*
Attackers
.48*a
.47*a
.18
.52*a
.44*a
.07
.32*
Players
Player
Relative
Sprint
%HSR
Load
Distance
>85%
HRmax
 Correlations with 4 GPS variables were significantly larger (p< .01)
than the HR variable.
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 Physiol Perf, 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 Physiol Perf, 8, 195-202.
Contact: k.lamb@chester.ac.uk or Greg Doncaster 0810282@chester.ac.uk