How to monitor training load and mode using sRPE

Abstract

Strength and conditioning involves the application of optimal bouts of physical training and therefore needs to balance stimulus with recovery. This is important, as training must be challenging enough to overload the athlete and thus stimulate adaptation, yet provide opportunity for recovery, as this is where supercompensation occurs. Miscalculations in training load can result in injury,14
illness,21 overtraining,19 or simply reductions in both competition and training performance.10 Critical to providing optimal training is the capacity to monitor training load, including being reactive and proactive to its data. Although many sophisticated systems have been – and are continually being – introduced as means by which this can be monitored, these are often inaccessible to coaches without access to large budgets. This paper will look at a method whereby coaches can use ‘session ratings of perceived exertions’ (sRPE) to provide a cost-effective method of monitoring this load.

Full text

15
PROFESSIONAL STRENGTH & CONDITIONING / WWW.UKSCA.ORG.UK
ISSUE 39 /DECEMBER 2015 MONITORING TRAINING LOAD
How to monitor training
load and mode using
sRPE
INTRODUCTION
Strength and conditioning involves the application of optimal bouts of physical
training and therefore needs to balance stimulus with recovery. This is
important, as training must be challenging enough to overload the athlete and
thus stimulate adaptation, yet provide opportunity for recovery, as this is where
supercompensation occurs. Miscalculations in training load can result in injury,14
illness,21 overtraining,19 or simply reductions in both competition and training
performance.10 Critical to providing optimal training is the capacity to monitor
training load, including being reactive and proactive to its data. Although many
sophisticated systems have been – and are continually being – introduced as
means by which this can be monitored, these are often inaccessible to coaches
without access to large budgets. This paper will look at a method whereby coaches
can use ‘session ratings of perceived exertions’ (sRPE) to provide a cost-effective
method of monitoring this load.
By Anthony Turner, MSC, PGCE, ASCC, CSCS*D, Chris Bishop, MSC, ASCC, and Geoff Marshall, MSC, ASCC,
London Sports Institute, Middlesex University, Paul Read, MSC, ASCC, CSCS, St Mary’s University
The challenge of measuring training
load
Training load (TL) is affected by volume
and intensity and therefore both of
these must be measured as part of the
monitoring process. Traditionally, this
has been achieved via measuring heart
rate – eg, TRIMP2 – and using modified
versions using HR zones9 and lactate
deflection points,16 and – more recently
– global positioning system analysis.23
Even disregarding cost, neither can
be used across all modes of training
regularly undertaken by today’s athletes.
For example, they do not function well
when describing (highly anaerobic)
conditioning sessions consisting of in-
place exercises (eg, bikes and ropes) or
frequent and rapid changes in direction,7,8,17
and they cannot be used for gym and
plyometric sessions. This therefore leaves
the strength and conditioning (S&C) coach
with a variety of units (eg, kg, m/s, km, W, N)
used to express TL, which somehow must
be combined together to describe the day’s
physical effort.
Fortunately, a simple, time-efficient and
cost-effective method of assessing TL can
be obtained by multiplying total exercise
duration (in minutes) by its rating of
perceived exertion (using an adapted Borg
Category Ratio; CR-10). This is referred to
as the session rating of perceived exertion
(sRPE) and was devised by Foster.11,12
This method also brings further potential
benefits as, by virtue of collecting TL data,

16 PROFESSIONAL STRENGTH & CONDITIONING / WWW.UKSCA.ORG.UK
ISSUE 39 / DECEMBER 2015MONITORING TRAINING LOAD
the S&C coach will have access to additional
statistics that can further describe the quality
of the training undertaken. This includes
analysing the percentage contributions of
each mode of training (eg, conditioning,
gym, technical skills and competitive
drills) that occur in the overall macrocycle
(eg, frequency of competitions, rest days,
training days and travel days).
The aim of this paper is therefore to provide
a practical guide to using the sRPE and
to show how it can be further analysed to
evaluate the distribution of training mode
and individualised athlete responses to
training.
Using the sRPE to quantify training load
Like the CR-10, the sRPE translates the
athlete’s perception of effort into a numerical
score between 0 and 10 (see Table 1),
thereby enabling its use across all modes
of training. Scores (ie, rating x session
duration) are generally obtained 30 minutes
after the completion of exercise following
the question: ‘How was your workout?’.
This time frame ensures that the score is
reflective of the entire session rather than
Table 1: The session RPE scale12
SESSION RPE
0 Rest
1 Really easy
2 Easy
3 Moderate
4 Sort of hard
5 Hard
6
7 Really hard
8
9 Really, really hard
10 Just like my hardest race
Table 2: Hypothetical training loads within fencing, calculated per session and day, and then totalled up to reveal the
week’s total load and its variability
DAY SESSION DURATION SRPE SESSION TL DAILY TL
Monday Gym 50 5 250 760
Plyometrics 10 4 40
Technical fencing 90 3 270
Conditioning 20 10 200
Tuesday Technical fencing 90 4 360 840
Footwork drills 30 4 120
Sparring (5 x 5 hits) 60 6 360
Wednesday Footwork drills 20 4 80 1130
Tactical fencing 30 5 150
Sparring (5 x 5 hits) 45 6 270
Sparring (4 x 15 hits) 90 7 630
Thursday Agility 15 6 90 570
Plyometrics 15 5 75
Footwork drills 15 3 45
Sparring (3 x 15 hits) 60 6 360
Friday Gym 50 6 300 750
Agility 10 6 60
Technical fencing 60 4 240
Tactical fencing 30 5 150
Saturday Gym 60 5 300 500
Conditioning 20 10 200
Sunday Rest and Recovery 0 0 0 0
Total TL 4550
Average daily TL 650
SD daily TL 351
TM 1.85

17
PROFESSIONAL STRENGTH & CONDITIONING / WWW.UKSCA.ORG.UK
ISSUE 39 /DECEMBER 2015 MONITORING TRAINING LOAD
just the final part. More recently, it was found
that measurements could be determined as
early as 10 minutes after exercise and be
just as accurate;22 anecdotally, doing it at the
end of the cool-down provides a good time
point. Given its validity, simplicity and cost-
effectiveness, the sRPE has been successfully
used in various team sports,1,6,14,18 as well
as taekwondo,15 swimming,24 boxing22 and
sprint kayak.4
Table 2 provides hypothetical TL data
collected within the sport of fencing. TL is
first identified specific to mode, then totalled
to describe the TL for each day. On recovery
days, a score of zero must be entered and
included in calculations of weekly TL.
In addition to TL, a score for training
monotony (TM) can also be calculated,13
which can be used to indicate the variability
(or lack of) in TL. TM is calculated as the
average daily TL across the week (or training
phase) divided by its standard deviation.
It is generally advisable that variability
(ie, the standard deviation) in training is
high, especially with more experienced
athletes. Specifically, the closer TM is to one,
the more variability within the programme.
High variability can be achieved by – for
example – alternating ‘hard’ and ‘easy’
training days. Conversely, if the same total
training load was instead equally divided
into several consecutive ‘medium’ training
days, the score for monotony would be high
and the athlete’s risk of illness, overtraining
and under-performance would increase.5,11
Training variability can be subjectively
analysed by plotting each day’s TL and
looking for appropriate undulations,
whether that be in the form of a ‘hard day,
easy day’ rota or the re-occurring pattern of
‘low, medium and hard days’. This variability
has been illustrated in Figure 1 using the
example data provided in Table 2.
Individualised training
It is important that athletes rate the session
themselves due to different perceptions of
effort required to complete the prescribed
tasks. For example, variation in fitness levels,
recovery and external stressors will impact
the internal load response. Individualisation
is of course the cornerstone of effective
training, enabling adaptations to be
optimised. Furthermore, if TL data is tracked
longitudinally and mapped to injury
incidence or illness for a particular athlete,
it may also be used to reveal thresholds of
TL that particular individuals should avoid
(see Figure 2). Alternatively, mapping data
to fitness testing results and competition
results could highlight optimal TL doses.
Quantifying training mode
Having collected TL data, and itemised
it as shown in Table 2, a quantification
can be made of the distribution of mode
relative to the week’s TL, ie, what percentage
of physical effort athletes dedicate to
particular sessions. If coaches suggest
that sparring is most important, then this
should make up the majority of training.
Alternatively, novice athletes may require
a greater emphasis on technical and
tactical aspects of fencing. Additionally,
‘variations in
fitness levels
... will impact
the internal
load response’
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
Sunday
600
800
1000
1200
400
200
0
Weeks
6500
4000
4500
5000
5500
6000
3500
2000
2500
3000
Training Load (arbituary unts)
***
Figure 1. Hypothetical data describing training load distribution per day within a
typical week for fencers
Figure 2. Hypothetical data of weekly TL for an individual athlete. Also plotted is
the threshold for training for this athlete (identified as 5500 arbitary units), above
which appears to be correlated to injury or illness (as represented by ‘*’)

18 PROFESSIONAL STRENGTH & CONDITIONING / WWW.UKSCA.ORG.UK
ISSUE 39 / DECEMBER 2015
athletes returning to the sport following
an injury or the off-season should show a
progressive week-on-week increase in the
amount of fencing they are doing in order to
reduce the risk of experiencing an overuse
injury.20 This data can be represented as a
pie chart (Figures 3 and 4), identifying the
total contribution of each mode within the
respective micro-, meso- and macrocycles.
Using the idea of gradual return to play,
you could produce and investigate a series
of microcycles to determine if TL has
been appropriately managed, by gradually
increasing the volume of fencing training
during successive weeks (Figure 4).
Finally, using the methods illustrated
in Figures 3 and 4 (and using Excel’s
‘COUNTIF’ function), the whole season (or
a significant portion of) can be planned
and then illustrated to show the distribution
of training days, rest days, travel days and
competition days. Although this represents
the best-case scenario, actual data
collected can be analysed retrospectively
for comparison. This allows the coach to
assess the quantity of training completed
by the athletes, highlighting days lost to
injury, illness, travel and other external
commitments (eg, study or employment).
These graphs can thus be useful in
explaining why a) progressions have
been made, or b) why some athletes have
regressed or reached a plateau.
Figure 5 (on next page) demonstrates this
register type approach (where the COUNTIF
formula is illustrated in the formula bar) and
also includes the frequency tables for the
best-case scenario allocation of training
days and training modes. A comparison
between two athletes (athlete A and B)
against the best-case scenario has also been
provided.
It is interesting to see that of the 181 days
analysed (and using the pie charts to show
percentage distribution), athlete A trained
MONITORING TRAINING LOAD
conditioning 10%
technical 13%
tactical 8%
plyometrics
3%
agility 4%
gym 17%
sparring 42%
footwork
3%
= Fencing technical = Fencing sparring = Gym = Conditioning
Figure 3. Hypothetical data
illustrating the relative
distribution of training modes
within a typical week for fencers
Figure 4. Assessing the
distribution of training over
successive weeks to ensure
athletes are progressively
introduced to the high-intensity
training and high-impact loads
that are synonymous with
fencing. The pie charts go left to
right, weeks 1 to 4
‘The whole
season can be
planned and
illustrated
to show
distribution of
training, rest,
travel and
competition
days’

19
PROFESSIONAL STRENGTH & CONDITIONING / WWW.UKSCA.ORG.UK
ISSUE 39 /DECEMBER 2015
more (39 vs 28%) including at camps
(14 vs 11 %) and also had greater rest periods (17
vs 9%). Additionally, athlete A had no outside
training commitments – unlike athlete B,
who missed 19% of training due to university
and/or work commitments; athlete A was
also injured (2 vs 3%) and ill less frequently
(1 vs 3%) than athlete B.
This type of data collection and analysis
is of great use to coaches and facilitates
discussion during athlete review meetings.
Conclusion
The sRPE provides a quick and accessible
means to calculate TL and is available to
all athletes and S&C coaches regardless of
competition level. It is also simple enough
for athletes to complete themselves and
provide the data to the S&C coach when
reporting for gym-based and conditioning
sessions.
A TL can even be computed for athletes who
also have labour-intensive professions, as
this may affect the body’s recovery processes
and ability to perform during training and
competition. If the training data is detailed
enough, and additional commitments are
recorded (eg, work, study), then the relative
distribution of training modes across
the athlete’s plan can also be evaluated.
This provides an additional opportunity
to evaluate training, either proactively or
reactively, as it identifies time spent training
and time spent resting – ie, where the athlete
has the opportunity to improve, relative to
time that could have been spent in this
capacity.
MONITORING TRAINING LOAD
Figure 5. Quantifying the distribution of training mode. This can be done across the whole season or at time periods of interest to
the coaching team. The data can also be used to compare athlete engagement relative to the ‘best-case scenario’
‘The sRPE provides a
quick and accessible
means to calculate
training load –available
to all athletes and S&C
coaches regardless of
competition level’

20 PROFESSIONAL STRENGTH & CONDITIONING / WWW.UKSCA.ORG.UK
ISSUE 39 / DECEMBER 2015MONITORING TRAINING LOAD
References
1. Alexiou, H, & Coutts, A J. A comparison of
methods used for quantifying internal training
load in women soccer players. International
Journal of Physiology and Performance, 3, 320-
330. 2008.
2. Bannister, E. Modeling athletic performance. In:
Physiological testing of the elite athlete (pp. 403–
424). J D McDougall, H A Wenger, & H J Green
(Eds.).Champaign: Human Kinetics. 1991.
3. Borg, G. Psychophysical Bases of Perceived
Exertion. Medicine and Science in Sports and
Exercise, 14 (5), 377–381. 1982.
4. Borges, T, Bullock, N, Duff, C, & Coutts, A.
Methods for quantifying training in Sprint Kayak.
Journal of Strength and Conditioning Research,
28 (2), 474-482. 2014.
5. Bruin, G, Kuipers, H, Keizer, H A, & Vander
Vusse, G J. Adaption and overtraining in horses
subjected to increasing training loads. Journal of
Applied Physiology, 76, 1908-1913. 1994.
6. Coutts, A, Reaburn, P, Murphy, A, Pine, M, &
Impellizzeri, F. Validity of the session-RPE
method for determining training load in team
sport athletes. Journal of Science and Medicine in
Sport, 6 (4), 525. 2003.
7. Drust, B, Reilly, T, & Cable, N. Physiological
responses to laboratory-based soccer-specific
intermittent and continuous exercise. Journal of
Sports Science, 18, 885–892. 2000.
8. Duffield, R, Reid, M, Baker, J, & Spratford, W.
Accuracy and reliability of GPS devices for
measurement of movement patterns in confined
spaces for court-based sports. Journal of Science
and Medicine in Sport, 13 (5), 523-525. 2010.
9. Edwards, S. High performance training and
racing. In: The Heart Rate Monitor Book (pp.
113-123). S Edwards (Ed.). Sacramento: Feet Fleet
Press. 1993.
10. Elloumi, M, Makni, E, Moalla, W, Bouaziz, T,
Tabka, Z, & Chamari, K. Monitoring Training
Load and Fatigue in Rugby Sevens Players.
Asian Journal of Sports Medicine, 3 (3), 175-184.
2012.
11. Foster, C. Monitoring Training in Athletes with
Reference to Overtraining Syndrome. Medicine
and Science in Sports and Exercise, 30 (7), 1164–
1168. 1998.
12. Foster, C, Daines, E, Hector, L, Snyder, A C, &
Welsh, R. Athletic Performance in Relation to
Training Load. Wisconsin Medical Journal, 95
(6), 370-374. 1996.
13. Foster, C, Hector, R., Welsh, M, Schrager, M,
Green, MA, & Snyder, A C. Effects of specific
versus cross-training on running performance.
European Journal of Applied Physiology, 70 (4),
367-372. 1995.
14. Gabbett, T. Influence of training and match
intensity on injuries in rugby league. Journal of
Sports Science, 222 (5), 409-417. 2004.
15. Haddad, M, Chaouachi, A, Castagna, C, Wong,
P L, Behm, D G, & Chamari, K. The construct
validity of session RPE during an intensive camp
in young male Taekwondo athletes. International
Journal of Physiology and Performance, 6, 252-
263. 2011.
16. Impellizzeri, F, Rampinini, E, Coutts, A, Sassi, A,
& Marcora, S. Use of RPE-Based Training Load
in Soccer. Medicine and Science in Sports and
Exercise, 36 (6), 1042-1047. 2004.
17. Jennings, D, Cormack, S, Coutts, A J, Boyd, L,
& Aughey, R J. The validity and reliability of
GPS units for measuring distance in team sport
specific running patterns. International Journal
of Sports Physiology and Performance, 5 (3), 328-
341. 2010.
18. Manzi, V, D’Ottavio, S, Impellizzeri, F M,
Chaouachi, A, Chamari, K, & Castagna, C. Profile
of weekly training load in elite male professional
basketball players. The Journal of Strength &
Conditioning Research, 24 (5), 399-1406. 2010.
19. Meeusen, R, Gleeson, M, Rietjens, M, & Steinacker,
G. Prevention, diagnosis and treatment of the
Overtraining Syndrome. European Journal of
Sport Science, 6 (1), 1-14. 2006.
20. Myer, G, Faigenbaum, A, Cherny, C, Heidt, R,
& Hewett, T. Did the NFL Lockout expose the
Achilles heel of competitive sports? The Journal
of Orthopaedic and Sports Physical Therapy, 41
(10), 702-705. 2011.
21. Neville, V, Gleeson, M, & Folland, J P. Salivary
IgA as a Risk Factor for Upper Respiratory
Infections in Elite Professional Athletes.
Medicine & Science in Sports & Exercise, 40 (7),
1228–1236. 2008.
22. Uchida, M, Teixeira, L, Godoi, V, Marchetti, P,
Conte, M, Coutts, A., et al. Does The Timing
of Measurement Alter Session-RPE in Boxers?
Journal of Science and Medicine in Sport, 13 (1),
59-65. 2014.
23. Varley, M, Fairweather, I, & Aughey, R. Validity and
reliability of GPS for measuring instantaneous
velocity during acceleration, deceleration, and
constant motion. Journal of sports sciences, 30
(2), 121-127. 2012.
24. Wallace, L, Slattery, K, & Coutts, A. The
ecological validity and application of the
session-RPE method for quantifying training
loads in swimming. Journal of Strength and
Conditioning Research, 23 (1), 33-38. 2009.
ANTHONY TURNER, MSC, PGCE, ASCC, CSCS*D
Anthony Turner is the director of postgraduate programmes at the London Sport Institute, Middlesex University, where he
is also the programme leader for the MSc in strength and conditioning. Anthony is head of physical preparation for British
Fencing and a consultant to Queens Park Rangers Football Club, Saracens Rugby Club and the Special Forces. Anthony
was awarded the 2015 UKSCA Strength and Conditioning Coach of the Year Award for Education and Research.
CHRIS BISHOP, MSC, ASCC
Chris is a lecturer in strength and conditioning
at the London Sport Institute, Middlesex University.
PAUL READ, MSC, ASCC, CSCS
Paul Read is a senior lecturer in strength and conditioning at St Mary’s University. He is also an accredited strength and
conditioning coach consulting with professional MMA fighters, international combat athletes in a range of disciplines,
and various professional football clubs.
AUTHORS’ BIOGRAPHIES
GEOFF MARSHALL, MSC, ASCC
Geoff is a strength and conditioning coach
at British Fencing where he works primarily
with the men’s foil team in preparation for
the Rio Olympics in 2016.