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Use of RPE-Based Training Load in Soccer
FRANCO M. IMPELLIZZERI1, ERMANNO RAMPININI1,
AARON J. COUTTS2,
ALDO SASSI1, and SAMUELE M. MARCORA3
1Human Performance Lab, S.S. MAPEI, Castellanza, Varese,
ITALY; 2School of Leisure, Sport and Tourism, University of
Technology, Sydney, AUSTRALIA; and 3School of Sport,
Health, and Exercise Sciences, University of Wales-Bangor,
UNITED KINGDOM
ABSTRACT
IMPELLIZZERI, F. M., E. RAMPININI, A. J. COUTTS, A.
SASSI, and S. M. MARCORA. Use of RPE-Based Training

Load in
Soccer.Med. Sci. Sports Exerc., Vol. 36, No. 6, pp. 1042–1047,
2004.Purpose: The ability to accurately control and monitor
internal
training load is an important aspect of effective coaching. The
aim of this study was to apply in soccer the RPE-based method
proposed
by Foster et al. to quantify internal training load (session-RPE)
and to assess its correlations with various methods used to
determine
internal training load based on the HR response to
exercise.Methods: Nineteen young soccer players (mean� SD:
age 17.6� 0.7
yr, weight 70.2� 4.7 kg, height 178.5� 4.8 cm, body fat 7.5�
2.2%, V
̇ O2max, 57.1 � 4.0 mL·kg
�1·min�1) were involved in the
study. All subjects performed an incremental treadmill test
before and after the training period during which lactate
threshold (1.5
mmol·L�1 above baseline) and OBLA (4.0 mmol·L�1) were
determined. The training loads completed during the seven
training weeks
were determined multiplying the session RPE (CR10-scale) by
session duration in minutes. These session-RPE values were
correlated
with training load measures obtained from three different HR-
based methods suggested by Edwards, Banister, and Lucia,
respectively.
Results: Individual internal loads of 479 training sessions were
collected. All individual correlations between various HR-based
training load and session-RPE were statistically significant
(from r� 0.50 to r� 0.85,P � 0.01).Conclusion: The results of
this study
show that the session-RPE can be considered a good indicator of
global internal load of soccer training. This method does not

require
particular expensive equipment and can be very useful and
practical for coaches and athletic trainer to monitor and control
internal load,
and to design periodization strategies.Key Words: PERCEIVED
EXERTION, HEART RATE, PHYSICAL TRAINING, TEAM
SPORTS
P
hysical training is the systematic repetition of physi-
cal exercises, and it can be described in terms of its
outcome (anatomical, physiological, biochemical,
and functional adaptations) or its process, that is, the train-
ing load (TL) (the product of volume and intensity of
training) (30). Although physical fitness tests are commonly
used to assess training outcome, the training process is often
described as the external load prescribed by coach (e.g., 4
� 1000 m running at 4 min·km�1 or 8 � 30-m dash at
maximum velocity). However, the stimulus for training in-
duced adaptation is the relative physiological stress imposed
on the athletes (internal TL) and not the external TL (30).
Therefore, to monitor and control the training process, it is
important to have a valid measure of internal TL (16). This
is particularly relevant in team sports where the planned
external load is often similar for each team member because
of the extensive use of group exercises such as small -sided
games in team training sessions. For example, it was re-
cently reported that soccer players with higher V˙ O2max tend
to exercise at a lower percentage of V˙ O2max during small -
game exercises (19). These previous results suggest that use
of group training exercises, such as small-sided games, may
not provide sufficient stimulus for physiological adaptation
in the fitter athletes within a team (19). In addition to fitness
level, other factors such as injury, illness, weather condi -

tions, match-scheduling problems, and athlete psychological
status can influence the internal TL. Consequently, when
combined, these factors suggest that monitoring and con-
trolling athletes’ internal TL is very important to ensure that
each athlete receives adequate training stimulus.
There have been several attempts to quantify TL in en-
durance sports (5,13–16,25). It is well known that HR dem-
onstrates an almost linear relationship with V˙ O2 over a wide
range of steady-state submaximal exercise intensities (2).
This close relationship between HR and V˙ O2 measures
makes HR monitoring suitable for quantifying exercise in-
tensity during most exercise sessions. Because HR seems to
be one of the best objective way to quantify aerobic training
intensity (1,17), many methods to quantify the internal TL
are based on HR monitoring (5,25). In sports like soccer,
HR is mainly used to determine the exercise intensity
(3,18,19). To our knowledge, there are no studies using HR
to monitor the overall internal TL of soccer sessions. How -
ever, it is common practice for some top professional soccer
teams to systematically monitor TL using HR methods.
Apart from few top level soccer teams, the routine use of
HR-based method is not always feasible due to problems
Address for correspondence: Franco M. Impellizzeri, Human
Performance
Lab, S. S. MAPEI srl, Via Don Minzoni, 34, 21053 Castellanza
(VARE-
SE), Italy; E-mail: [email protected]
Submitted for publication August 2003.
Accepted for publication February 2004.
0195-9131/04/3606-1042
MEDICINE & SCIENCE IN SPORTS & EXERCISE®
Copyright © 2004 by the American College of Sports Medicine

DOI: 10.1249/01.MSS.0000128199.23901.2F
1042
such as the required technical expertise, the time-consuming
process of collecting HR data of all team players every
training session, and the cost of numerous HR telemetric
systems. An additional problem with using HR methods for
quantification of internal TL in team sports such as soccer is
that HR transmitter belts are not permitted during official
competitive matches. This is an important limitation be-
cause the internal training load induced by a match may
represent a relative high percentage of the weekly training
load.
An alternative strategy to quantify internal TL was pro-
posed by Foster et al. (13–16). This simple method (session-
RPE) quantifies internal TL multipl ying the whole training
session rating of perceived exertion (RPE) using the cate-
gory ratio scale (CR10-scale) (6) by its duration. This prod-
uct represents in a single number the magnitude of internal
TL in arbitrary units (AU). Previous research examining the
validity of this method of measuring internal TL has shown
session-RPE to be related to the percent of HR reserve
(HRR) during 30 min of steady-state running and to the time
spent at different intensities corresponding to HR at lactate
thresholds (2.5 and 4.0 mmol·L�1) during 30 min of con-
tinuous and interval running (16). Other research has also
shown the session-RPE to be significantly correlated to
HR-based method of quantifying internal TL proposed by
Edwards (12) in endurance athletes (13). The individual
correlations between the session-RPE and Edwards’ HR
method ranged from 0.75 to 0.90 (13). Although the session-
RPE method was initially proposed for monitoring internal

TL in endurance athletes, this method has recently been
applied to basketball (9,15), where training is characterized
by both aerobic and anaerobic exercises (4).
To date, there are no published studies validating this
practical, simple, and inexpensive method to quantify inter -
nal TL in team sports. Therefore, the aim of this study was
to verify whether the Fosters’ RPE-based approach can be
considered a good indicator of internal TL in soccer players,
using various HR-based methods as criteria.
METHODS
Subjects. Nineteen young soccer players (mean � SD:
age 17.6 � 0.7 yr, weight 70.2 � 4.7 kg, height 178.5 � 4.8
cm) from the same soccer club were involved in the study.
All participants were fully informed of the aims and the
procedures of the study receiving both verbal and written
explanation. All athletes gave a written consent according to
the American College of Sports Medicine guidelines. This
study was approved by the Ethics Committee of the local
organization.
Laboratory test. Commonly used performance tests
were performed before and after 7 wk of training to eval uate
the subjects training progress. An incremental treadmill run
to exhaustion was completed using the protocol of Helgerud
et al. (18), where the treadmill running velocity was in-
creased by 1 km·h�1 every 5 min, at an inclination of 3%.
Once capillary blood lactate concentrations [La�] were el-
evated above 4 mmol·L�1, the treadmill speed was in-
creased 1 km·h�1 every 30 s until exhaustion. V
̇ O2max was
measured using a breath-by-breath automated gas analysis
system (VMAX29, SensorMedics, Yorba Linda, CA). Flow,
volume, and gas concentrations were calibrated before each

test using routine procedures. The highest HR measured
during the test was used as maximum reference value. At the
end of each step and 3 min after exhaustion, capillary blood
samples (25 �L) were collected from the ear lobe and
immediately analyzed using an electroenzymatic technique
(YSI 1500 Sport, Yellow Springs Instruments, Yellow
Springs, OH). Before each test the analyzer was calibrated
following the instructions of the manufacturer using stan-
dard lactate solutions of 0, 5, 15, and 30 mmol·L�1. The
following lactate thresholds were calculated from blood
[La�] measures taken during the incremental test:
1) Lactate threshold (LT), the intensity that elicited a 1.5
mmol·L�1 increase in [La�] above baseline values (50 –
60% of V
̇ O2max) (18).
2) Onset of blood lactate accumulation (OBLA), the
intensity corresponding to a fixed [La�] value of 4
mmol·L�1 (28).
Field data collection. Training data were collected
during the first 7 wk of the competitive season (from Sep-
tember to November). The training program was planned by
the coach of the team. The researchers did not alter the
original training program. Except for the second week of the
study, all players trained four times (Monday, Tuesday,
Wednesday, Thursday) and participated in an official match
each week (Saturday). In the second week, only three train-
ing sessions were completed. The heaviest aerobic training
was usually completed during the Monday sessions. During
the Tuesday sessions, the first 30 min of training were
generally dedicated to speed development consisting mainly
of sprint and plyometric training exercises. Running interval
training (4 � 1000 m) was completed only two times during
the 7 wk of the study. Most of the physical conditioning
training was performed using small group exercises. Small -

sided games with individual technical and tactical objectives
were also extensively performed.
HR was recorded every 5 s during each training session
using HR monitor with individually coded HR transmitters
to avoid interference (VantageNV, Polar Electro, Kempele,
Finland). The mean HR recorded during the briefing before
each training session was used as rest HR. To reduce HR
recording error during training, all athletes were regularly
asked to check that their HR monitors were functioning of
properly (at least every 10 min). The investigators were
immediately available to solve these problems such as er -
roneous HR values or technical/transmission problems. Af-
ter every training session, HR data were downloaded on a
portable PC using the specific software and subsequently
exported and analyzed using the Excel software program
(Microsoft Corporation, U.S.).
Internal training load indices determination. The
session-RPE was determined by multiply the training dura-
tion (minutes) by session RPE as described by Foster et al.
(16). Each athlete’ s session-RPE was collected about 30 min
after each training session to ensure that the perceived effort
MONITORING TRAINING LOAD IN SOCCER Medicine &
Science in Sports & Exercise� 1043
was referred to the whole session rather than the most recent
exercise intensity. In this study, the Italian translation of the
CR10-scale modified by Foster et al. (16) was used. This
scale was modified in order to better reflect the American
idiomatic English (Table 1). It is unlikely that these minor
changes affect the reliability and the validity of the original
Borg’ s CR10-scale. All athletes had been familiarized with

this scale for rating perceived exertion before the com-
mencement of the study.
Various HR-based TL were used as the criterion measure
of internal TL. The HR-based method proposed by Edwards
(12) was used by Foster et al. to validate the use of RPE-TL
to monitor endurance training (13). This HR-based method
was also used as criterion measure of TL in a study exam-
ining the session-RPE method during nonsteady state and
prolonged exercise (15). For these reasons, we calculate
Edwards’ TL from training sessions HR data recorded and
collected during the 7 wk of training. The Edwards’ method
determines internal load by measuring the product of the
accumulated training duration (minutes) of 5 HR zones by a
coefficient relative to each zone (50 –60% of HRmax � 1,
60 –70% of HRmax � 2, 70 –80% of HRmax � 3, 80 –90%
of HRmax � 4, 90 –100% of HRmax � 5) and then summat-
ing the results.
Another HR-based method of determining internal TL in
the present study was the training impulse (TRIMP), de-
scribed by Banister (5). Training impulse was determined
using the following formula:
TD�HRR�0.64�e
1.92�HRR [1]
in which TD is the effective training session duration ex-
pressed in min and HRR is determined with the following
equation:
��HRTS � HRB�/(HRmax � HRB�] [2]
where HRTS is the average training session HR and HRB is
the HR measured at rest.

Recently, Lucia et al. (21) proposed another approach to
determine internal TL in endurance athletes (Lucia’ s
TRIMP). TL is calculated using this method by multiplying
the time spent in three different HR zones (zone 1: below the
ventilatory threshold; zone 2: between the ventilatory
threshold and the respiratory compensation point; zone 3:
above the respiratory compensation point) by a coefficient
(k) relative to each zone (k � 1 for zone 1, k � 2 for zone
2, and k � 3 for zone 3) and then summating the results.
This method is similar to that of Edwards (12). The main
difference between Edward’ s and Lucia’ s method is that the
HR zones defined by Lucia et al. (21) are based on indi -
vidual parameters obtained in laboratory, whereas Edward’ s
method uses standardized predefined zones. In the present
study, LT were used instead of ventilatory thresholds. A
similar approach was used by Foster et al. (16), who re-
ported significant relationships between session-RPE and
relative time spent in three different zones defined by HR at
2.5 and 4 mmol·L�1 LT. For weeks 1–4, the LT of the first
laboratory test was used, whereas for weeks 5–7, the tests
results performed at the end of the training period investi -
gated were taken as reference.
Statistical analysis. The relationships between ses-
sion-RPE and the various HR-based TL were analyzed
using Pearson’ s product moment correlation. Mean weekly
session-RPE was analyzed using a one-way ANOVA, fol-
lowed by Scheffé’ s post hoc test. Statistical significance was
set at P � 0.05. For the statistical analysis, the software
package STATISTICA (Version 6.0, StatSoft, Tulsa, OK)
was used.
RESULTS
Maximum oxygen uptake of this group of young soccer

players was not statistically different before and after 7 wk
of training (56.8 � 3.9 mL·kg�1·min�1 vs 57.1 � 4.0
mL·kg�1·min�1). Similarly, HRmax (187.6 � 6.7
beats·min�1 vs 189.6 � 5.7 beats·min�1) and maximal
aerobic speed reached in the treadmill incremental test (16.7
� 1.1 km·h�1 vs 17.0 � 1.1 km·h�1) were unchanged after
training. The HR at LT in the first and second laboratory
tests was 162.0 � 11.9 beats·min�1 and 163 � 7.9
beats·min�1, corresponding to 85.5 � 5.3 and 86.9 � 3.8%
of HRmax, respectively. The HR at OBLA in the first and
second laboratory test was 171.5 � 8.3 beats·min�1 and
171.2 � 7.1 beats·min�1, corresponding to 90.5 � 3.4 and
91.3 � 3.4% of HRmax, respectively. These absolute and
relative HR were not significantly different between the two
testing sessions.
The various HR-based TL and session-RPE were col-
lected from 476 training sessions. Individual correlations
were determined on a minimum of 17 to a maximum of 27
training sessions data. Correlations between session-RPE
and HR-based TL were all significant (P � 0.01 to P �
0.001). Individual correlations are presented in Table 2.
Figure 1 shows that session-RPE and Edwards’ TL de-
scribed similarly the team TL during the 7 wk of training,
confirmed also by the significant correlation between team
session-RPE and team Edwards’ TL (Fig. 2).
The mean weekly internal TL (weekly periodization)
described using session-RPE is shown in Figure 3. The
mean session-RPE of Monday, Tuesday, Wednesday, and
Thursday were 634 � 116 AU, 550 � 67 AU, 453 � 83
AU, and 343 � 65 AU, respectively (N � 19). For descrip-
tive purposes and to obtain a more representative value of
match RPE (625 � 60 AU), only data of players that played
more than 80 min were used (N � 12). Peak internal TL was

TABLE 1. Borg’s CR10-scale modified by Foster et al. (16).
Rating Descriptor
0 Rest
1 Very, very easy
2 Easy
3 Moderate
4 Somewhat hard
5 Hard
6
7 Very hard
8
9
10 Maximal
1044 Official Journal of the American College of Sports
Medicine http://www.acsm-msse.org
https://www.researchgate.net/publication/10746534_Heart_rate_
monitoring_applications_and_limitations?el=1_x_8&enrichId=r
greq-56fe8ee2e53619e29c4b4822c9cd1cb5-
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TA0NTE4MDgzNjc4MjEyQDE0MDE5MzA0NjE5MDU=
reached the first day of the training week (after a day of total
recovery) (Fig. 1). Further analysis of the individual training
weeks within this study showed that there was some vari-
ability in the placement of peak internal TL sessions within
the week. For example, during week 2 and 7 peak daily
sessions were completed on the second day of training.
However, most of the sessions with higher internal TL were
completed at least 3 d before match. This was deliberately
planned by the coach to allow for adequate recovery before

competitive matches.
DISCUSSION
The present study is the first to apply the Foster’ s RPE-
based approach (16) to quantify internal TL in soccer, and
to demonstrate significant correlations between this method
and other published methods based on the HR response to
exercise. These correlations (ranging from 0.50 to 0.85)
were slightly lower than those reported by previous inves-
tigators (r � 0.75–0.90) (13). A possible explanation for the
lower correlations in the present study could be the in-
creased anaerobic contribution to energy provision during
soccer training. The increased anaerobic contribution may
account for the increased internal TL through increased
RPE. Previous research supporting this suggestion has dem-
onstrated increased subject RPE during intermittent proto-
cols in comparison with a steady-state exercise session
matched for total work, despite no differences in V
̇ O2 and
HR between the two exercise protocols (11). These inves-
tigators also suggested that the increased RPE during the
intermittent work protocol may be due to the increased
contribution of anaerobic mechanisms to energy provision
(11,27). Because soccer training can be characterized by
intermittent exercises relying on both aerobic and anaerobic
sources for energy provision (3), the different perceived
exertion with similar mean HR may explain the reduced
strength of the correlations between the session-RPE and
HR-based TL in comparison to those reported by previous
research on endurance athletes (13).
As RPE represents the athlete’ s own perception of train-
ing stress, which can include both physical and psycholog-
ical stress, the session-RPE method may provide a valuable

FIGURE 1—Pattern of RPE-based training load (session-RPE)
and
HR-based training load suggested by Edwards (12) (Edwards’
TL)
referred to the whole team (N � 19) during the 7 wk of training
(27
training days without matches); AU, arbitrary unit.
FIGURE 2—Correlation between mean team RPE-based training
load
(session-RPE) and HR-based training load suggested by
Edwards (12)
(Edwards’ TL) of the 27 training sessions (r � 0.71, P < 0.001).
FIGURE 3—Weekly periodization determined using mean
weekly
RPE-based training load (session-RPE) during the 7 wk of
soccer
training (N � 19); AU, arbitrary unit; * P < 0.05; *** P <
0.001; † P
< 0.05; ‡ P < 0.001: statistically different from Saturday
(MATCH).
TABLE 2. Individual correlations between Foster’s RPE-based
training load (session-
RPE) and various HR-based training loads; all individual
correlations were
statistically significant (P � 0.01).
Subjects
Banister’s
TRIMP
Edwards’
TL

Lucia’s
TRIMP
S1 0.52 0.61 0.63
S2 0.68 0.55 0.68
S3 0.67 0.54 0.67
S4 0.51 0.68 0.61
S5 0.50 0.62 0.67
S6 0.64 0.59 0.69
S7 0.52 0.55 0.71
S8 0.62 0.67 0.77
S9 0.56 0.60 0.69
S10 0.59 0.74 0.68
S11 0.56 0.57 0.65
S12 0.54 0.54 0.73
S13 0.60 0.67 0.67
S14 0.64 0.73 0.63
S15 0.67 0.70 0.79
S16 0.60 0.78 0.70
S17 0.58 0.62 0.68
S18 0.57 0.62 0.75
S19 0.77 0.64 0.85
Min 0.50 0.54 0.61
Max 0.77 0.78 0.85
measure of internal TL. Borg’ s CR10 is considered a global
indicators of exercise intensity including physiological (ox-
ygen uptake, HR, ventilation, beta endorphin, circulating
glucose concentration, and glycogen depletion) and psycho-
logical factors (23). As a consequence, RPE-based quanti-

fication of TL could be considered an accurate indicator of
global internal TL. Research has shown that the combina-
tion of HR and [La�] predicts RPE more accurately than
either variable taken alone (7). This previous research sug-
gests that RPE may be a more reliable measure of exercise
intensity when both anaerobic and aerobic systems are ap-
preciably activated, such as is the case during intermittent
activities like soccer training and match play (3). Hence,
these findings emphasize the usefulness of RPE to monitor
exercise intensity due to its psychobiological nature (8).
Although RPE has been shown to accurately reflect ex-
ercise intensity, it is possible that players could perceive the
same physiological stimulus differently as a consequence of
their individual psychological state (24). Researchers inves -
tigating overreaching and overtraining support this sugges-
tion, as RPE has been reported to increase during a stan-
dardized exercise test when athletes are in an increased
fatigue state (29). Furthermore, during overreaching, RPE
for a given HR was reported to increase (22), suggesting that
RPE could be more sensitive to accumulated fatigue than
HR. This characteristic of RPE may have partially deter-
mined the moderate correlations between HR-based TL and
session-RPE found in some subjects of this investigation.
Consequently, the use of RPE to monitor exercise intensity
could be considered a valuable tool to detect excessive
training-related fatigue in athletes and also potentially via-
ble in monitoring responses to training and preventing over -
training (20,29).
Quantification of internal TL is also necessary to analyze
the periodization of training (26). In team sports, appropri-
ate periodization of internal TL during the training week is
important to ensure adequate physiological stimulus is pro-
vided while allowing adequate time for recovery before
competition days. Commonly, heavy training sessions are

not imposed to players in the days immediately before or
after competition matches, in order to avoid excessive phys-
ical strain that could impair recovery and reduce perfor -
mance (10). This general approach to the weekly training
structure is common among many soccer teams and other
team sports where weekly competition is required (10,26).
The RPE-based method for quantifying internal TL is
simple and practical. However, in order to be used reliably,
it is necessary to follow correct standardized procedures
including player education and familiarization with the
CR10-scale, and standard timing of rating should be fol-
lowed (15). In the present investigation, the players were
accustomed to use the CR10-scale to classify training in-
tensity, as this method was routinely used in both their
soccer training and laboratory-based physiological testing
sessions. The use of RPE during incremental tests is a good
approach as it allows the athlete to readily associate RPE
scores through a full range of exercise intensities. However,
when laboratory tests cannot be conducted, it is possible to
familiarize players with incremental field tests. The famil -
iarity of our subjects with the use of the CR10-scale made
it simple to attain valid exertion ratings after each training
session. The timing of the rating is also important to mini -
mize influence of the last effort during training on the
player’ s RPE of the whole training session. For this reason
in this study, the last 15–20 min of each training session
were dedicated to cool-down, and RPE were asked for after
30 min from the end of the session.
In summary, based on our results and the literature re-
viewed, Foster’ s RPE-based method seems to be a good
indicator of global internal TL in soccer. This method does
not require expensive equipment such as telemetric HR
systems and may be very useful and practical for coaches to

monitor soccer players internal TL. Furthermore, the present
results suggest that the RPE-based method may assist in the
development of specific periodization strategies for individ-
uals and teams. However, the moderate correlations we
found do not support this method as a valid substitute of HR,
as only about 50% of variance in HR was explained by
session-RPE. This simple method has the potential to be-
come a valuable tool for coaches and sport scientists to
monitor internal TL, but further studies are necessary to
fully validate this TL quantification strategy.
The authors would like to thank Prof. Maurizio Fanchini and the
Pro Patria Football Club for their collaboration in this study.
We also
acknowledge the soccer players involved in this investigation.
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320

International Journal of Sports Physiology and Performance,
2008, 3, 320-330
© 2008 Human Kinetics, Inc.
A Comparison of Methods
Used for Quantifying Internal
Training Load in Women Soccer Players
Helen Alexiou and Aaron J. Coutts
Purpose: The purpose of this study was to compare the session-
RPE method for
quantifying internal training load (TL) with various HR-based
TL quantification
methods in a variety of training modes with women soccer
players. Methods: Fifteen
elite women soccer players took part in the study (age: 19.3 ±
2.0 y and VO2max: 50.8
± 2.7 mL·kg−1·min−1). Session-RPE, heart rate, and duration
were recorded for 735
individual training sessions and matches over a period of 16 wk.
Correlation analysis
was used to compare session-RPE TLs with three commonly
used HR-based methods
for assessing TL. Results: The mean correlation for session-RPE
TL with Banister’s
TRIMP, LTzone TL and Edwards’s TL were (r = 0.84, 0.83, and
0.85, all P < .01,
respectively). Correlations for session-RPE TL and three HR-
based methods sepa-
rated by session type were all significant (all P < .05). The
strongest correlations were
reported for technical (r = 0.68 to 0.82), conditioning (r = 0.60
to 0.79), and speed

sessions (r = 0.61 to 0.79). Conclusion: The session-RPE TL
showed a significant
correlation with all training types common to soccer. Higher
correlations were found
with less intermittent, aerobic-based training sessions and
suggest that HR-based TLs
relate better to session-RPE TLs in less intermittent training
activities. These results
support previous findings showing that the session-RPE TL
compares favorably with
HR-based methods for quantifying internal TL in a variety of
soccer training activi-
ties.
Keywords: session-RPE, heart rate, soccer training,
periodization
To optimize athletic performance, physical training should be
prescribed to suit
each athlete’s individual characteristics. However, in team
sports like soccer,
training sessions are often conducted in a group, which reduces
the likelihood that
players are receiving specific training based on their individual
characteristics.1
For example, Hoff et al,2 demonstrated that soccer players with
superior fitness
levels did not receive sufficient training stimulus to further
increase their fitness
when training in a team environment using small-sided games
alone. It has also
been suggested that players with inferior fitness levels may be
overstressed during
The authors are with the School of Leisure, Sport, and Tourism,
University of Technology, Sydney,

Australia.
Quantifying Training in Team Sports 321
team-based training sessions leading to increased fatigue,
injury, and a reduction
in performance.1 Collectively, these findings show that
individuals within the
same soccer team may not receive an appropriate level of
training stimulus when
a team-based training approach is undertaken. Therefore, to
overcome the limita-
tions associated with team-based training, it has been suggested
that a simple
system that quantifies an individual’s response to training (ie,
internal TL) is
developed, so that coaches can monitor and modify training
according to indi-
vidual players’ needs.
The assessment of internal TL requires quantification of the
intensity and
duration of the physiological stress imposed on the athlete.3
While the duration of
the training session is simple to measure, exercise intensity is
more difficult to
quantify. However, the most common methods used to measure
exercise intensity
in soccer are heart rate (HR) and ratings of perceived exertion
(RPE).1,4 The use
of HR to measure exercise intensity is based on the well -known
linear relationship
between HR and VO2max over a wide range of steady-state
submaximal workloads.5

However, there are several limitations associated with HR-based
methods for
quantifying internal TL. For example, a high level of technical
expertise is required
to collect and collate HR information from a whole team,
collecting and analyzing
HR data for each player can be time consuming, there is a
chance for technical
errors, and the financial cost associated with purchasing and
maintaining telemet-
ric HR systems can be high. Finally, another limitation of HR-
based methods for
quantifying internal TL in soccer is that it is a relatively poor
method of evaluating
very high intensity (and/or short duration) exercise such as
resistance training,
high intensity interval training, and plyometric training.6 For
these reasons the use
of HR-based methods for quantifying TL may not be the most
valid or practical
approach for measuring TL in the field.
Foster3 proposed an alternative method for assessing internal
TL utilizing
Borg’s Category Ratio–10 (CR-10) RPE scale as a measure of
exercise intensity.
Using this method, internal TL can be calculated by multiplying
the training dura-
tion by the rating of perceived exertion (RPE) score. While this
method was origi-
nally proposed for endurance athletes, research has recently
shown that this
method has a good level of agreement with HR-based methods
for quantifying TL
in team sports7 and in particular soccer players.6 However, a
limitation of previous

studies examining session-RPE is that the majority of them have
focused on
endurance sports or one type of training mode (ie, resistance
training).8–10 More-
over, the few studies that have focused on team sports have
established the validity
of the session-RPE during aerobic interval training using small-
sided soccer
games training. Therefore, this study will assess the validity of
the session-RPE
method across all the training types typical of a soccer training
program, therefore
including both aerobic and technical/tactical training as well as
anaerobic training
and matches.
The session-RPE method may provide valuable information in
regards to
monitoring TL throughout the season and appears to be of great
benefit for moni-
toring individual soccer players’ TL. As well as providing
valuable information in
regards to monitoring TL, the session-RPE method provides a
practical alternative
to using HR-based methods. However, the relationship between
session-RPE
derived TLs and HR-based TLs across a range of exercise types
in women soccer
322 Alexiou and Coutts
players has not been fully assessed. Therefore, the purpose of
this study is to com-
pare the session-RPE method with various HR-based methods

for quantifying
internal TL with women soccer players in a variety of training
modes.
Methods
Subjects
Fifteen elite women soccer players (age: 19.3 ± 2.0 years,
height: 169.0 ± 5.1 cm,
body mass: 64.8 ± 7.7 kg, VO2max: 50.8 ± 2.7 mL·kg−1·min−1)
were recruited for
this study. All were scholarship holders at the Football
Association (FA) National
Player Development Centre (Loughborough University,
Loughborough, UK). Ten
of the fifteen subjects were members of the England
international age-group team
at Under 17 years, Under 19 years, Under 21 years, or open age
level. Before the
commencement of this study all subjects were given an
information sheet outlin-
ing potential risks associated with involvement in this study. A
written consent
form was also obtained from each subject or their parent. Before
any testing ethi-
cal approval was granted by an Institutional Human Research
Ethics Committee.
Study Design
The data for this study was collected from 15 high performance
women soccer
players over a 16-week soccer season. All subjects completed a
maximum oxygen
uptake test (VO2max) and a lactate threshold (LT) test at the

beginning of the com-
petitive season to determine the individual HR training zones.
Heart rate and ses-
sion-RPE were monitored during each training session and
match during the
season. The relationships between the session-RPE TL and
commonly used HR-
based TL quantification methods were used to examine the
criterion validity of the
session-RPE. The strength of the relationship was reported
within each individual
player and also for each different training type completed
during the season.
Physical Training
The training program was set by the players’ coaching panel
throughout the study
period. Each player usually completed eight training sessions
per week during the
study period. The typical training week consisted of three
technical/tactical ses-
sions, two high-intensity resistance training sessions, one
aerobic conditioning
session, one core stability session, one pool “recovery” session,
and a competitive
match. The training sessions were usually conducted together
with the entire
training squad. The technical/tactical sessions usually focused
on acquisition and
refinement of soccer-specific skills. The resistance training
sessions were usually
involved 6 to 10 exercises of 6 to 12 repetitions at various
lifting speeds. Depend-
ing on the focus of training and each player’s individual needs,
from one to three

sets of each resistance training exercise were completed with 30
s / 3 min rest
between each set. The core stability sessions focused on
developing core body
strength and posture and involved resistance training exercises.
The pool sessions
were completed within 24 h following matches and were of low
intensity and
continuous in nature. The aerobic conditioning sessions
involved either
high-intensity, small-sided soccer games or high-intensity
interval running train-
ing. The competitive soccer matches were played according to
the normal Fédéra-
tion Internationale de Football Association regulations.
The TL for each session was calculated using the session-RPE
method7 for
each player during the study period. This method involved
multiplying the train-
ing duration in minutes by the mean training intensity.7 The
training intensity was
measured using a modified 10-point Rating of Perceived
Exertion Scale (CR-10:
RPE)11 shown in Table 1. To ensure the subjects reported a
mean RPE for the
entire training session, the RPE was taken 30 minutes after the
completion of the
session using previously described methods.6 The TL for each
day of the week
was summed to provide a weekly TL. All data were entered into

an online data-
base for analysis of team and individual TLs
(www.trainingload.com, Accelera-
tion Australia, Brisbane).
Training intensity for each player was also recorded
continuously throughout
each training session using Polar HR monitors (Polar Oy,
Finland). The HR data
were recorded every 5 s. To reduce HR recording error during
training, all subjects
were asked to check their HR monitors before each session and
after each set (~10
min). Following each training session, HR information was then
downloaded to a
computer using Polar Advantage Software.
Several HR-based methods for quantifying TL were used as the
criterion
measure of internal TL in this investigation. The TRIMP method
proposed by
Banister et al12 assumes each exercise bout elicits a training
impulse. The expres-
sion of TL measured in TRIMP units is determined using the
following formula:
where D = duration of training session and b = 1.67 for females
and 1.92 for
males.13
Table 1 The Borg Category Ratio-10 Rating
of Perceived Exertion Scale8
Rating Description

0 Rest
1 Very, Very Easy
2 Easy
3 Moderate
4 Somewhat Hard
5 Hard
6
7 Very Hard
8
9
10 Maximal
where HRrest = the average heart rate during rest and HRex =
the average HR
during exercise. The player’s HRrest was measured during 5
min of seated rest
every morning during the study period.
The HR-based method proposed by Edwards14 for determining

internal TL
was also used as another criterion measure of internal TL in this
study. The
Edwards14 HR-based method involved integrating the total
volume of the training
session with the total intensity of the exercise session relative
to five intensity
phases. An exercise score for each training bout was calculated
by multiplying the
accumulated duration in each HR zone by a multiplier allocated
to each zone
(50% to 60% HRmax = 1, 60% to 70% HRmax = 2, 70% to 80%
HRmax = 3, 80%
to 90% HRmax = 4, and 90% to 100% HRmax = 5) and then
summating the
results.
The final criterion measure of internal TL used in this study was
the HR-
based approach based on lactate thresholds (LTzone). This
approach has previously
been used in a similar investigation.6 This method involves
multiplying the time
spent in three heart rate zones (zone 1: below lactate threshold
(LT), zone 2:
between LT and the anaerobic threshold (AT); and zone 3:
above AT) by a coef-
ficient relative to each intensity zone (k = 1 for zone 1, k = 2
for zone 2, and k = 3
for zone 3) and then summating the results. The main difference
between the
Edwards and LTzone methods for quantifying TL are that the
HR zones determined
in Edwards’s14 investigation are based on standardized
predetermined zones,
whereas LTzone HR zones are based on individual parameters

determined in the
laboratory.
Session-RPE and HR-based TL data were collected for 735
individual train-
ing sessions and matches. For the lactate threshold heart rate
zone (LTzone) TL
method, only 623 of the total training samples and matches were
used, because LT
data were not collected from three players. For each player, a
minimum of 20 ses-
sions of RPE and HR-based TL data were used to ensure
adequate statistical
power with the correlation analysis.
Physiological Tests
All subjects completed a maximal oxygen uptake test and
twelve players com-
pleted a lactate threshold test.
Lactate threshold was measured using an incremental run on a
motorized
treadmill (RunRace, Technogym, Gambettola, Italy) in an
environmentally con-
trolled human performance laboratory. The test began at
between 8 and 9 km·h−1
dependant on individual. Treadmill speed was increased every
four minutes by 1
km·h1 until 12 km·h−1, and then by 0.5 km·h-1 for the final
four-minute stages.
Blood samples (25 µL) were taken at rest, along with two
samples collected
toward the end of each stage from the players thumb and
analyzed using a YSI
2300 STAT Plus Lactate Analyser (Fleet, Hampshire, England).

Lactate threshold
was determined using the Dmax method with the Lactate-E
macro add-in15 for
Microsoft Excel (Microsoft Corporation, USA).
To determine maximum oxygen uptake, the players completed
an uphill
incremental treadmill run to exhaustion16 on a motorized
treadmill (RunRace,
Technogym, Gambettola, Italy). The test began with a 5-minute
warm-up at 8
km·h−1. The treadmill speed was kept constant throughout the
test and the inclina-
tion was increased from an initial gradient of 3.5% by 2.5%
every 3 min. Expired
air samples were collected during the 1:45 to 2:45 minutes of
each 3-minute stage.
A final expired air sample was taken during the last minute of
the test, immedi-
ately after the player signaled that the running speed could be
maintained for one
final minute. The highest value for oxygen uptake, collected
over a 60-s period,
during this test was considered to be the VO2max of the
participant.17 Heart rate was
recorded throughout the incremental test using portable HR
monitors (Polar NV
HR monitor). Maximal oxygen uptake was measured using the
conventional
Douglas bag method. Expired gases were analyzed using
Servomex 1440 (Cow-

borough, Sussex, England), which was calibrated before each
test with reference
and calibration gases of known concentrations and a Harvard
Dry Gas Meter
(Edenbridge, Kent, UK).
Statistical Analyses
The relationship between session-RPE and previously used HR-
based methods
for monitoring TL were analyzed using Pearson’s product–
moment correlation.
Relationships were determined between each of these methods
for a) each session
completed by each individual player and b) each type of
training completed by the
players. Differences between the mean TL for each exercise
type were determined
using a one-way ANOVA with a Scheffe post hoc test. The
mean, standard devia-
tion (SD), and 95% confidence intervals (CI) were also
calculated for the group
data. Statistical significance was set at P < .05. SPSS statistical
software package
version 11.5 (SPSS Inc., Chicago, USA) was used for all
statistical calculations.
Results
Individual correlations of session-RPE and all three HR-based
TL methods are
outlined in Table 2. All correlations were statistically
significant (P < .01). There
were also significant correlations between the session-RPE and
all the HR-based
TL methods for each of the various training modalities (Table
3). The correlation

analysis for the various training modes demonstrated that
approximately half the
variance in the HR-based training methods could be accounted
for by the session-
RPE TL for the Conditioning (Banister’s TL-55%; LTzone TL-
35%; Edwards’s
TL-62%), Speed (Banister’s TL-37%; LTzone TL-
56%;Edwards’s TL-62%), and
Technical (Banister’s TL-46%; LTzone TL-48%; Edwards’s TL-
67%) training ses-
sions. However, the session-RPE TL accounted for less of the
variance in the
HR-based TLs for the Matches (Banister’s TL-24%; LTzone TL-
24%; Edwards’s
TL-41%) and Resistance (Banister’s TL-6%; LTzone TL-12%;
Edwards’s TL-27%)
training sessions.
Figure 1 shows the mean (±SD) session TL for the session-RPE
and HR-
based TL methods for each of the common training modalities
completed during
the study periods. A one-way analysis of variance demonstrated
that the TLs for
each monitoring method (ie, Banister’s TRIMP, LTzone TL, and
Edwards’s TL)
was not significantly different (F = 0.15, df = 2, P = .86).
However, within ses-
326
Table 2 Individual Correlations Between Session-RPE TL and
Three
HR-Based TL Methods

Subject N
Banister’s
TRIMP
LTzone
TL
Edwards’s
TL
1 20 0.75 0.88 0.50
2 115 0.76 0.82 0.74
3 20 0.92 0.85 0.93
4 60 0.91 0.63 0.93
5 26 0.76 —a 0.85
6 80 0.88 0.93 0.95
7 39 0.74 0.56 0.78
8 20 0.95 0.66 0.91
9 20 0.94 0.97 0.96
10 58 0.81 0.88 0.91
11 80 0.91 0.94 0.93
12 42 0.67 —a 0.72

13 39 0.87 0.90 0.90
14 44 0.89 —a 0.89
15 72 0.90 0.94 0.92
Range 0.67–0.95 0.56–0.97 0.50–0.96
Mean ± SD 0.84 ± 0.09 0.83 ± 0.14 0.85 ± 0.12
95% CI (0.80–0.89) (0.74–0.92) (0.79–0.92)
a LTzone TL was not calculated because lactate threshold
measurements were not available. All
correlations were significant (P < .01).
sion-RPE and each monitoring method highly significant
differences were detected
based on training type (P < .001). A post hoc analysis showed
that match loads
were significantly greater than resistance training, speed, and
conditioning, and
that resistance training were less than technical sessions.
Discussion
This study is the first to our knowledge to compare session-RPE
derived TLs with
various HR-based TLs in a variety of training types in elite
women soccer players.
The results showed that the session-RPE method had a
significant positive corre-
lation with three HR-based methods for quantifying TL within
each of the 15
players examined. Moreover, we also found significant positive
correlations
between session-RPE TL and the various HR-based TL methods
across various
training activities common to soccer. The present findings

support previous stud-
ies reporting the session-RPE as a practical tool for monitoring
internal TL in a
variety of training activities.6,7
327
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In agreement with previous research,6,7 we observed moderate-
to-strong rela-
tionships between session-RPE TL and HR-based TL methods (r
= 0.56 to 0.97)
within the individual players. The mean correlations between
the HR-based TL
methods and RPE within individual players in this study (0.83
to 0.85) are higher
than those reported in previous studies that examined soccer
training6 but lower
than studies that have examined steady-state exercise.18 A
possible explanation for
the lower correlations in this study compared with other similar
research that
involved more steady-state exercise could be attributed to an
increased anaerobic
contribution due to the stochastic nature of work in soccer
training.4 In support of
this, when we examined the relationships between the HR-based
TLs and the
session-RPE method for the different training types we found
the lowest correla-
tion for the resistance training sessions (r = 0.25 to 0.52), which

typically involve
short high-intensity lifting efforts. Collectively, these results
suggest that there are
stronger relationships between session-RPE TL and HR-based
TL measures taken
following endurance-based, steady-state exercise than these
measures taken with
stochastic, intermittent, or interval-based exercises.
Previous studies have supported the validity of the session-RPE
method as a
tool for quantifying internal TL for resistance training using the
percentage of
one-repetition maximum (1-RM) as the criterion measure of
training intensity.7–10
In contrast to these previous studies, we compared the session-
RPE TL method
with HR-based TL methods. Since HR is considered a relatively
poor method of
evaluating very high intensity exercises such as resistance
training, high intensity
interval training, and plyometric training it seems that using HR
as the criterion
measure of exercise intensity is a limitation. These types of
exercises depend on a
large contribution from oxygen-independent metabolism rather
than oxygen-
dependent mechanisms and therefore HR may not be an
appropriate global mea-
sure of exercise intensity. It is possible that other markers of
exercise intensity
such as blood lactate measures taken during high-intensity
exercises may better
relate to session-RPE measures than HR measures.4 In
agreement with previous
research,6 the present results suggest that the session-RPE

method is a good prac-
tical method for quantifying internal TL in team sports such as
soccer.
Table 3 Correlation Coefficients for Session-RPE TL and Three
HR-
Based TL Methods Separated by Session Type for the Combined
Group of Players
Bannister’s TRIMP LTzone TL Edwards’s TL
r N P r N P r N P
Conditioning 0.74 139 <0.001 0.60 119 <0.001 0.79 139 <0.001
Matches 0.49 65 <0.001 0.49 56 <0.001 0.64 65 <0.001
Speed 0.61 59 <0.001 0.75 48 <0.001 0.79 59 <0.001
Technical 0.68 230 <0.001 0.69 200 <0.001 0.82 230 <0.001
Resistance 0.25 242 <0.001 0.34 200 <0.001 0.52 242 <0.001
Practical Applications
The simplicity and versatility of the session-RPE method makes
it a valuable tool
for athletes, coaches, and sport scientists. Its low cost and lack
of reliance on
technical expertise or equipment make it a very user friendly
and practical tool for
monitoring TL in soccer. One of the benefits of using Borg’s

CR-10 scale19 is its
measure of both psychological and physiological factors,
therefore giving a more
holistic indication of the “global” internal (or physiological)
stress.20 This study
also supports the benefits of using the session-RPE method to
monitor each player
within a soccer team. Indeed, long-term monitoring of training
loads may assist
soccer coaches in controlling the training process and assist in
improving
performance.
Summary
The purpose of this study was to compare the session-RPE
method with various
HR-based methods for quantifying internal TL with women
soccer players in a
variety of training modes. The results demonstrated significant
correlations
between the session-RPE method and various HR-based methods
for quantifying
TL for all individual players. Notably, however, there was a
poorer correlation
with the session-RPE TL and HR-based TL during resistance
training and match
play. These lower relationships might be explained by the
intermittent nature or
the very high intensity of these activities. These results support
previous findings
that session-RPE is a practical method for assessing internal TL
for soccer players
and in particular women soccer players. Importantly, however,
these results also
demonstrate that session-RPE TL is not a valid substitute for

HR derived TLs
when monitoring exercise intensity.
Acknowledgments
Physiological test were completed at the physiology laboratory
at the School of Sport and
Exercise Science, Loughborough University, UK.
References
1. Impellizzeri FM, Rampinini E, Marcora SM. Physiological
assessment of aerobic
training in soccer J Sport Sci. 2005;23(6):583–592.
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specific aerobic endurance
training. Br J Sports Med. 2002;36(3):218–221.
3. Foster C, Hector LL, Welsh R, Schrager M, Green MA,
Snyder AC. Effects of specific
versus cross-training on running performance. Eur J Appl
Physiol Occup Physiol.
1995;70(4):367–372.
4. Coutts AJ, Rampinini E, Castagna C, Marcora S,
Impellizzeri FM. Physiological
correlates of perceived exertion during soccer-specific exercise.
J Sci Med Sport.
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5. Åstrand PO, Rodahl K. Textbook of Work Physiology. New

York: McGraw Hill;
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6. Impellizzeri FM, Rampinini E, Coutts AJ, Sassi A, Marcora
SM. Use of RPE-based
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1047.
7. Foster C, Florhaug JA, Franklin J, et al. A new approach to
monitoring exercise train-
ing. J Strength Cond Res. 2001;15(1):109–115.
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during resistance training using the session-RPE scale. J
Strength Cond Res.
2004;18(2):353–358.
9. Gearhart RE, Goss FL, Lagally KM, Jakicic JM, Gallagher J,
Robertson RJ. Stan-
dardized scaling procedures for rating perceived exertion during
resistance exercise. J
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10. Singh F, Foster C, Tod D, McGuigan MR. Monitoring
different types of resis-
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11. Borg GAV, Hassmen P, Langerstrom M. Perceived exertion
in relation to heart rate
and blood lactate during arm and leg exercise. Eur J Appl
Physiol. 1985;65:679–685.
12. Banister EW. Modeling elite athletic performance. In:

Green HJ, McDougal JD,
Wenger HA, eds. Physiological Testing of Elite Athletes.
Champaign, Illinois: Human
Kinetics; 1991:403–424.
13. Morton RH, Fitz-Clarke JR, Banister EW. Modeling human
performance in running.
J Appl Physiol. 1990;69(3):1171–1177.
14. Edwards S. High performance training and racing. In:
Edwards S, ed. The Heart Rate
Monitor Book. 8th ed. Sacramento, CA: Feet Fleet Press;
1993:113–123.
15. Newell J, Higgins D, Madden N, et al. Software for
calculating blood lactate endur-
ance markers. J Sports Sci. 2007;25(12):1403–1409.
16. Taylor HL, Buskirk E, Henschel A. Maximal oxygen intake
as an objective measure
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17. Howley ET, Bassett DR, Jr, Welch HG. Criteria for
maximal oxygen uptake: review
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18. Foster C. Monitoring training in athletes with reference to
overtraining syndrome.
Med Sci Sports Exerc. 1998;30(7):1164–1168.
19. Borg G, Ljunggren G, Ceci R. The increase of perceived
exertion, aches and pain in
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Journal of Science and Medicine in Sport (2009) 12, 79—84
ORIGINAL PAPER
Heart rate and blood lactate correlates of
perceived exertion during small-sided
soccer games
Aaron J. Coutts a,∗ , Ermanno Rampinini b, Samuele M.
Marcora c,
Carlo Castagna d, Franco M. Impellizzeri b
a School of Leisure, Sport and Tourism, University of
Technology, Sydney, Australia
b Human Performance Laboratory, Mapei Sport Research
Center, Castellanza (VA), Italy
c School of Sport, Health, and Exercise Sciences, University of
Wales-Bangor,
Bangor, United Kingdom
d School of Sport and Exercise Sciences, Faculty of Medicine
and Surgery,
University of Rome Tor Vergata, Rome, Italy
Received 13 September 2006 ; received in revised form 10
August 2007; accepted 13 August 2007

KEYWORDS
Training intensity;
Heart rate;
Blood lactate;
Rating of perceived
exertion;
Soccer
Summary The rating of perceived exertion (RPE) could be a
practical measure of
global exercise intensity in team sports. The purpose of this
study was to examine
the relationship between heart rate (%HRpeak) and blood lactate
([BLa−]) measures
of exercise intensity with each player’s RPE during soccer -
specific aerobic exercises.
Mean individual %HRpeak, [BLa−] and RPE (Borg’s CR 10-
scale) were recorded from 20
amateur soccer players from 67 soccer-specific small-sided
games training sessions
over an entire competitive season. The small-sided games were
performed in three
4 min bouts separated with 3 min recovery on various sized
pitches and involved 3-,
4-, 5-, or 6-players on each side. A stepwise linear multiple
regression was used to
determine a predictive equation to estimate global RPE for
small-sided games from
[BLa−] and %HRpeak. Partial correlation coefficients were also
calculated to assess
the relationship between RPE, [BLa−] and %HRpeak. Stepwise
multiple regression
analysis revealed that 43.1% of the adjusted variance in RPE
could be explained by
HR alone. The addition of [BLa−] data to the prediction
equation allowed for 57.8%

of the adjusted variance in RPE to be predicted (Y = −9.49 −
0.152 %HRpeak + 1.82
[BLa−], p < 0.001). These results show that the combination of
[BLa−] and %HRpeak
measures during small-sided games is better related to RPE than
either %HRpeak or
[BLa−] measures alone. These results provide further support
the use of RPE as a
measure of global exercise intensity in soccer.
© 2007 Sports Medicine Australia. Published by Elsevier Ltd.
All rights reserved.
∗ Corresponding author.
E-mail address: [email protected] (A.J. Coutts).
1440-2440/$ — see front matter © 2007 Sports Medicine
Australia. Published by Elsevier Ltd. All rights reserved.
doi:10.1016/j.jsams.2007.08.005
mailto:[email protected]
dx.doi.org/10.1016/j.jsams.2007.08.005
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Introduction
The ability to monitor exercise intensity during
soccer training can be used to provide important
feedback to the coach regarding the training stim-
ulus applied to the players. It is now common
for top level professional soccer teams to moni-
tor training intensity using technical devices such as
heart rate monitoring systems1 and player tracking
devices.2 These systems can be used to provide use-
ful information on the external (i.e. distance) and
internal (i.e. heart rate) training load experienced
by the players. Unfortunately, time constraints
associated with using these devices such as analy-
sis and interpretation of data from multiple players
can limit their usefulness in the practical setting.
We have recently shown that a player’s rating of
perceived exertion (RPE) provides an alternatively
valid and time effective method for quantifying
training intensity during an entire soccer training
session (consisting of small-sided games, techni-
cal, speed, aerobic conditioning and plyometric
training).3 However, to the authors’ knowledge, no
studies have specifically examined the validity of
RPE as an indicator of exercise intensity solely dur-
ing soccer-specific small-sided games.
Rating of perceived exertion has been suggested
to be a more appropriate measure of exercise
intensity than individual physiological variables6

and is thought to be representative of the com-
bination of many factors affecting the internal
load of exercise such as an athlete’s psycholog-
ical state,7,8 training status8,9 and the external
training load.10 Indeed, RPE has been shown to be
a simple and valid method for quantifying whole
training session intensity for both steady-state11,12
and intermittent exercise.3,12 Moreover, RPE has
been correlated with many physiological measures
of exercise intensity such as oxygen consumption
(V
̇ O2), ventilation, respiratory rate, blood lactate
concentration ([BLa−]), heart rate (HR) and elec-
tromyographic activity during a variety of exercise
protocols.13—15 Taken together, these factors sug-
gest that RPE may be a valid marker of global
training intensity in athletes who undertake high-
intensity, intermittent exercise.
We have previously demonstrated that session-
RPE be a good general indicator for evaluating
global session training intensity in soccer players on
the basis of moderate correlations (r = 0.50—0.85)
between HR and RPE measures of training inten-
sity during soccer-specific training.3 In our previous
research RPE measures were referred to the global
perception of effort for the entire training session
rather than the perception of exercise intensity
during each training session. However, we suggest
2
s
o
w

T
A.J. Coutts et al.
hat a better understanding of the validity of using
PE for monitoring exercise intensity during soc-
er training could be gained by comparing RPE
easures taken during soccer training with other
onventional markers of exercise intensity such as
BLa−]. The aim of the present study was to there-
ore examine the relationship between RPE with
oth HR and [BLa−] to further validate the use of
PE for measuring global exercise intensity during
occer-specific small-sided games.
aterials
wenty soccer players from the same team (body
ass: 73.0 ± 9.0 kg, height: 178.8 ± 5.2 cm, and
ge: 25 ± 5 years) volunteered to participate in the
tudy. In order to be included in the study, partici-
ants were required to gain medical clearance from
he team physician to ensure they were in good
ealth. Informed consent was obtained after verbal
nd written explanation of the experimental design
nd potential risks of the study, and the partici-
ants were aware that they could withdraw from
he study at any time. The study was approved by
n Independent Institutional Review Board.
The amateur soccer team trained for approxi-
ately 120 min, two to three times each week. Data
ere collected two times a week from Septem-
er to June during 67 team training sessions. For
his study, HR, [BLa−] and RPE data were collected

rom the small-sided games component of train-
ng that consisted of 3 min × 4 min soccer-specific,
mall-sided games play with 3 min of active recov-
ry. Each small-sided game session was conducted
s part of the normal training regime for the soc-
er team and all games were completed outdoors
n the same grass soccer pitch. The data collection
as suspended in the winter period (December and
anuary) to avoid the colder weather and to exclude
ossible influences of extreme environmental con-
itions on the results. The small-sided games
nvestigated were 3-, 4-, 5-, and 6-a-side, with-
ut goalkeepers, using small goals, free touches
nd with a second ball always available for prompt
eplacement when it left the playing area (for more
etail of the formats used in these games see).4
oals were considered valid only when all team
ates were in the opponents half of the pitch.
mall-sided games were performed on various sized
ectangular pitches with playing areas ranging from
2 2
40 m (12 m × 20 m) to 2208 m (46 m × 48 m). A
tandard warm up procedure consisting of 20 min
f low intensity running, striding and stretching
as completed by all players before each session.
hese small-sided soccer game formats were cho-
M
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(
onitoring soccer training intensity

en for this study as they are commonly used in
raining by soccer teams to develop both physical
nd technical-tactical qualities and also to provide
n ecologically valid range of exercise intensities
or soccer training.4,5
In order to obtain the reference each player’s
ndividual peak heart rate (HRpeak) at regular
ntervals during the study period, soccer players
ompleted both a yo-yo endurance test (level 2)
nd a yo-yo intermittent recovery test (level 1) in
eptember (beginning of the competitive season),
ebruary (mid-season) and May/June (end of the
ompetitive season). These tests were used as they
ere normal part of each players physiological and
erformance testing regime and conducted accord-
ng to previously described methods.16,17 Both the
o-yo endurance test16 and the yo-yo intermittent
ecovery test17 have been shown to elicit HRpeak
alues that are very close to actual HRmax (99 ± 1%)
etermined in a laboratory. All players were famil-
ar with the field-testing procedures being part of
heir usual fitness assessment program.
In June (prior to the play-off phase) the soccer
layers also completed an incremental tread-
ill (RunRace, Technogym, Gambettola, Italy) test
or the determination of maximal oxygen uptake
V
̇ O2 max) using previously described methods.
4
eart rate was recorded throughout the incre-
ental treadmill test using a portable recordable

R monitor (VantageNV, S710 and Xtrainer models,
olar Electro, Kempele, Finland). The highest HR
eached during the laboratory or the field tests was
aken as the HRpeak.
Heart rate was recorded every 5 s during each
mall-sided game training session using individual
olar HR monitors (VantageNV, S710 and Xtrainer
odels, Polar Electro, Kempele, Finland). Immedi-
tely after every training session, the investigators
ownloaded the HR data to a portable PC using the
pecific software (Polar AdvantageTM, Polar Elec-
ro, Kempele, Finland) and subsequently exported
nd analysed using the Excel XP software pro-
ram (Microsoft Corporation, USA). The mean HR
xpressed relative to each players HRpeak (%HRpeak)
or the entire three 4 min small-sided game section
f each training session was used for analysis.
Blood lactate samples were taken within one min
fter the completion of the third 4 min interval
f the small-sided game. Capillary blood sam-
les (5 �L) were collected from the ear lobe
nd immediately analysed using several portable
mperometric microvolume lactate analysers (Lac-
atePro, Arkray, Japan). Before each test, the
nalysers were calibrated following the manufac-
urers recommendations. To limit the influence of
iet on [BLa−], all players were asked to follow a
H
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c

f
m
81
eneric weekly nutritional plan to ensure an ade-
uate carbohydrate intake (50—60% of total energy
ntake). However, a food diary was not recorded
y the athletes. During the small-sided games and
raining sessions all players were permitted to drink
d libitum.
Rating of perceived exertion (RPE, Borg’s CR-10
cale)18 was also used as a measure of inten-
ity for the small-sided game. Each player’s RPE
as collected at the end of each soccer-specific
mall-game to ensure that the perceived effort was
eferred to the small-game training only. In this
tudy, a printed Italian translation of the CR-10
cale modified from Foster et al.11 was used to
ssist the players in making their responses. All
layers who participated in this study had been
amiliarized with this modified scale for RPE before
he commencement of this study.
tatistical analyses
ata are presented as means ± standard deviation
S.D.). Prior to parametric statistical procedures,
he assumption of normality was verified using the
olmogorov—Smirnov test and Lillefors probabil-
ties. If this assumption was violated a Box-Cox
ransformation was completed with the optimal
ambda being determined by MINITAB 14.1 (Minitab
nc., PA, USA).

A stepwise multiple regression was used to
etermine a predictive equation to estimate RPE
f small-sided soccer games training from [BLa−]
nd %HRpeak. Partial correlation coefficients were
lso calculated to assess the relationship between
PE with [BLa−] and %HRpeak. Collinearity toler-
nce statistics were calculated to determine the
orrelation between the predictor variables. The
ollinearity tolerance statistics are used to deter-
ine when a predictor is too highly correlated with
ne or more of the other predictors. If the predictor
ariables are highly correlated with each other, the
nfluence of one variable on the response variable
ould not be separated from the other predictor
ariable. Therefore any variable that had a toler-
nce level of less than 0.10 was not included in the
odel. Standard statistical methods were used for
he calculation of means, standard deviation (S.D.)
nd Pearson’s product moment correlation coeffi-
ients. Statistical significance was set at p < 0.05.
ne-way repeated measures analysis of variance
ANOVA) was used to examine for differences in
Rmax and distance covered during the yo-yo inter-
ittent recovery tests performed throughout the
ompetitive season. Where a significant F-value was
ound, post-hoc Bonferroni’s test was applied. The
ultiple regression, ANOVA and collinearity statis-

82 A.J. Coutts et al.
Table 1 Partial correlations, standardized coeffi -
cients and level of significance for predictors of rating
of perceived exertion.
%HRpeak [BLa−]
Partial correlations 0.519 0.508
Standardized coefficient (ˇ) 0.449 0.436
Significance of standardized p < 0.001 p < 0.001
Figure 1 Changes in (A) HRmax and (B) Yo-Yo intermit-
t
(
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coefficients
All correlations significant (p < 0.05).
tics and linear regression analysis were conducted
using SPSS statistical software package (SPSS Inc.
Version 12, Chicago, USA).
Results
The mean HR, [BLa−] and RPE from the 851 indi-
vidual training sessions were 87.9 ± 3.8 %HRpeak,
5.59 ± 1.78 mmol L−1 and 7.0 ± 1.3, respectively.
The RPE measures were significantly corre-
lated with [BLa−] (r = 0.63, p < 0.05) and %HRpeak
(r = 0.60, p < 0.05). The stepwise multiple regres-
sion analysis revealed that 43.1% of the adjusted
variance in RPE could be explained by exercise
intensity measured by HR alone. The addi-
tion of [BLa−] data to the prediction equation
allowed for 57.8% of the adjusted variance
(57.9% unadjusted) in RPE to be predicted
(Y = −9.49 − 0.152 %HRpeak + 1.82 [BLa−]) [Adjusted
R2 = 0.58; F2,849 = 582.01, p < 0.001]. Partial corre-
lations, standardized coefficients and the level
of significance of predictors of RPE are shown in
Table 1. The collinearity statistic for this multiple
regression was acceptable with tolerance levels at

0.820.
Fig. 1A shows that HRpeak did not change dur-
ing the season (p > 0.05). The mean HRpeak values
obtained during the laboratory and field tests were
not significantly different to each other (p > 0.05).
Additionally, the total distance covered by the soc-
cer players during the yo-yo intermittent recovery
test significantly (p < 0.01) increased between the
three test sessions (Fig. 1B). The V
̇ O2max of soccer
players measured during the incremental treadmill
test in the laboratory was 56.3 ± 4.8 ml kg−1 min−1.
Discussion
The main finding of the present study was that
the combination of %HRpeak and [BLa
−] predicts
RPE following soccer small-games training better
than %HRpeak or [BLa
−] measures alone. In addi-
t
n
s
t
ent recovery test performance during the study period
mean ± S.D.). aSignificantly different to September
p < 0.05); bsignificantly different to February (p < 0.05).
ion, the present results also demonstrated that
oth %HRpeak and [BLa
−] were moderately corre-
ated to RPE. These results therefore demonstrate

he validity of RPE as indicator of training intensity
or intermittent aerobic soccer-specific exercises.
Correlation analysis showed that %HRpeak
xplained approximately 43% of the variance in
PE following soccer-specific small-games train-
ng. These results are similar to previous studies
xamining the relationship between RPE and
R measures during intermittent exercise.13,19
or example, in a meta-analysis Chen et al.13
emonstrated that the 95% confidence interval
f validity coefficients between HR and RPE was
= 0.397—0.617 during progressive intermittent
xercise. Likewise, Green et al.19 also recently
emonstrated a moderate correlation between HR
nd RPE (r = 0.63) during 5 min × 2 min cycling inter-
als with 3 min of active recovery in 12 physically
ctive males. The present results provide confir-
ation that RPE is not a valid substitute for HR
easures during high-intensity, non-steady-state
occer-specific exercises. However, since stronger
elationships have been reported between RPE and
R measures during steady-state endurance exer-
ise (95% confidence interval: r = 0.583—0.643),13
e suggest factors other than HR contribute to
he perception of fatigue following high-intensity,
on-steady-state training. The results of this
tudy also revealed that the [BLa−] taken after
he small-sided soccer games were moderately

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onitoring soccer training intensity
orrelated with RPE taken at the same time. In
greement, Green et al.19 previously demonstrated
hat RPE taken following each bout of 5 × 2 min
nterval cycling was moderately correlated to
BLa−] (r = 0.43). Taken together, these results
rovide further support to the validity of RPE as
easure of global exercise intensity during interval
raining.
The major finding of this study was that 57.8% of
he variance in RPE during soccer-specific aerobic
raining sessions was accounted for by the combi-
ation of the %HRpeak and [BLa
−] measures. It is
nteresting that the addition of [BLa−] measures to
he %HRpeak data in the multiple regression equa-
ion resulted in an additional 14.7% of the variance
f RPE being explained. Furthermore, the addi-
ion of [BLa−] to the multiple regression equation
lso reduced the standard error of the estimate
rom 0.98 to 0.87 units on the Borg CR 10-scale.
ince the present results show 42.2% of the RPE
ould not be explained by [BLa−] and %HRpeak, it
ppears that other factors may contribute to a play-
rs’ RPE during small-sided games training. Other
esearchers have suggested psychobiological fac-
ors such as metabolic acidosis, ventilatory drive,
espiratory gases, catecholamines, �-endorphins

nd body temperature are also related to percep-
ion of effort,8 however, the relationship of these
actors to RPE during high-intensity, intermittent
xercise is yet to be determined. Although these
actors were not measured in this study, it is likely
hat these could also account for some of the addi-
ional variance in RPE not explained by HR and
BLa−] given that these variables are also signifi-
antly changed during soccer-specific exercise.20
The results of this study validate the use of
PE as a marker of training intensity during high-
ntensity intermittent exercise and further support
he use of RPE for quantifying training intensity
uring small-sided games in soccer. A limitation of
his study is that only a single [BLa−] measure was
sed as the representative measure of the blood
actate response to the entire small-sided games
ection. It is possible that the present results may
ave been altered if multiple [BLa−] measures were
aken during each bout. However, it has previously
een reported that the [BLa−] measured during
occer activities may not represent the lactate pro-
uction immediately before sampling, but rather
n accumulated/balanced response to various prior
igh-intensity activities.1
In summary, the present data extend earlier
esearch suggesting RPE as a good indicator of train-
ng intensity during soccer training. In this study, we
ound that both HR and [BLa−] independently relate
o the RPE measures during soccer-specific, small-
83
ided games. We also demonstrated that most of
he variation in RPE measures might be explained

y the combination of %HRpeak and [BLa
−], which
urther supports the validity of RPE as indicator of
ntensity during intermittent exercise. Since regu-
ar assessment of HR and [BLa−] can be logistically
ifficult and expensive, we suggest that RPE pro-
ides an alternative and valid method for coaches
o monitor soccer training intensity. Nonetheless,
e suggest that small-sided soccer game training is
est monitored through the combination of each of
hese measures.
Practical implications
• Rating of perceived exertion correlates well
with traditional markers of exercise intensity
during soccer-specific small-sided games train-
ing.
• Player’s ratings of perceived exertion may be
used within a soccer training session to mon-
itor global exercise intensity and help the
coach control the training stimulus.
eferences
1. Bangsbo J, Mohr M, Krustrup P. Physical and metabolic
demands of training and match-play in the elite football
player. J Sports Sci 2006;24(7):665—74.
2. Edgecomb SJ, Norton KI. Comparison of global positioning
and computer-based tracking systems for measuring player
movement distance during Australian football. J Sci Med
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3. Impellizzeri FM, Rampinini E, Coutts AJ, Sassi A, Marcora
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Strength Cond Res 2007;21(2):367—71.
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ods. Med Sci Sports 1973;5(2):90—3.
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methods, mediators, and applications. Exerc Sport Sci Rev
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84
12. Foster C, Florhaug JA, Franklin J, Gottschall L, Hrovatin
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sciencedirect.com
Heart rate and blood lactate correlates of perceived exertion
during small-sided soccer gamesIntroductionMaterialsStatistical
analysesResultsDiscussionPractical implicationsReferences

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