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European Journal of Sport Science
ISSN: 1746-1391 (Print) 1536-7290 (Online) Journal homepage: http://www.tandfonline.com/loi/tejs20
Physical demands and power profile of different
stage types within a cycling grand tour
Dajo Sanders & Mathieu Heijboer
To cite this article: Dajo Sanders & Mathieu Heijboer (2018): Physical demands and power profile
of different stage types within a cycling grand tour, European Journal of Sport Science
To link to this article: https://doi.org/10.1080/17461391.2018.1554706
Published online: 27 Dec 2018.
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ORIGINAL ARTICLE
Physical demands and power profile of different stage types within a
cycling grand tour
DAJO SANDERS
1,2
& MATHIEU HEIJBOER
3
1
Physiology, Exercise and Nutrition Research Group, University of Stirling, Stirling, UK;
2
Sport, Exercise and Health Research
Centre, Newman University, Birmingham, UK &
3
Team LottoNL-Jumbo Professional Cycling Team, Amsterdam,
Netherlands
Abstract
This study aims to describe the intensity and load demands of different stage types within a cycling Grand Tour. Nine
professional cyclists, whom are all part of the same World-Tour professional cycling team, participated in this
investigation. Competition data were collected during the 2016 Giro d’Italia. Stages within the Grand Tour were classified
into four categories: flat stages (FLAT), semi-mountainous stages (SMT), mountain stages (MT) and individual time
trials (TT). Exercise intensity, measured with different heart rate and power output based variables, was highest in the TT
compared to other stage types. During TT’s the main proportion of time was spent at the high-intensity zone, whilst the
main proportion of time was spent at low intensity for the mass start stage types (FLAT, SMT, MT). Exercise load,
quantified using Training Stress Score and Training Impulse, was highest in the mass start stage types with exercise load
being highest in MT (329, 359 AU) followed by SMT (280, 311 AU) and FLAT (217, 298 AU). Substantial between-
stage type differences were observed in maximal mean power outputs over different durations. FLAT and SMT were
characterised by higher short-duration maximal power outputs (5–30 s for FLAT, 30 s–2 min for SMT) whilst TT and
MT are characterised by high longer duration maximal power outputs (>10 min). The results of this study contribute to
the growing body of evidence on the physical demands of stage types within a cycling Grand Tour.
Keywords: training, performance, cycling, power output, heart rate
Highlights
.A professional cycling Grand Tour consists of varying stage types such as time trials, flat stages and (semi-)mountain stages.
.Substantial differences in intensity and exercise load demands, quantified using heart rate and power output based metrics,
are observed between different stage types.
.The detailed description of such demands, and the identified differences between different stage types, can inform training
strategies in preparation for these races.
Introduction
Three-week cycling Grand Tours are one of the most
physically demanding events in competitive sport
worldwide. A big proportion of professional road
cyclists will participate in at least one, if not more,
of the three week Grand Tours: the Giro d’Italia,
Tour de France and Vuelta a España (Lucia, Hoyos,
& Chicharro, 2001). Over recent years we have
obtained more and more information on the physio-
logical characteristics of professional cyclists specia-
lising in different competition elements that are
present within Grand Tours (Lucia et al., 2001;
Padilla, Mujika, Cuesta, & Goiriena, 1999; Vogt,
Schumacher, Blum, et al., 2007). Furthermore,
case studies are available on the physiological profiles
of a multiple Tour de France winning cyclist (Bell,
Furber, Van Somren, Anton-Solanas, & Swart,
2017) and a multiple top-10 Grand Tour finisher
(Pinot & Grappe, 2015). Descriptive studies evaluat-
ing the exercise intensity and load characteristics of
Grand Tours have shown the extreme physiological
demands of these races (Lucia, Hoyos, Santalla,
Earnest, & Chicharro, 2003; Padilla et al., 2001;
Padilla, Mujika, Orbananos, & Angulo, 2000;
© 2018 European College of Sport Science
Correspondence: Dajo Sanders, Physiology, Exercise and Nutrition Research Group, University of Stirling, FK9 4LA Stirling, UK. Email:
dajosanders@gmail.com
European Journal of Sport Science, 2018
https://doi.org/10.1080/17461391.2018.1554706
Padilla, Mujika, Santisteban, Impellizzeri, & Goir-
iena, 2008). Upon recently, the main variable to
monitor these athletes was heart rate, and intensity
and load were based on data collected using heart
rate monitors. For example, Padilla et al. (2000,
2001,2008), in a series of studies, evaluated the exer-
cise intensity and load during cycling competitions by
describing the time spent in different heart rate zones
and exercise load using the heart rate-based Training
Impulse (TRIMP) metric. The studies described
have shown that quantification of intensity distri-
bution and exercise load, using heart rate-based
metrics, can reflect the physiological demand of
different competition settings in professional
cycling. Even though these studies have also provided
(some) power output demands, power output in
these studies was estimated based on the individual’s
heart rate –power output relationship from linear
regression equations based on laboratory incremental
test results (Padilla et al., 2001). However, due to
technological advancements over recent years with
mobile power meters, the collection of both physio-
logical (i.e. heart rate) and work rate (i.e. power
output) data in the field is now widely possible to
monitor the training and competition of (elite)
cyclists. Indeed, a number of studies have reported
that power meters can be used as an accurate moni-
toring tool for coaches, athletes or sport scientists
(Bouillod, Pinot, Soto-Romero, Bertucci, &
Grappe, 2017; Gardner et al., 2004).
Since power output is now so widely used in (pro-
fessional) cycling to guide training sessions or
analyse performance, studies are now available that
describe the power output demands of professional
cycling as well, with a particular interest for the
demands of different competition elements
(Abbiss, Menaspa, Villerius, & Martin, 2013;
Menaspa, Quod, Martin, Peiffer, & Abbiss, 2015;
Padilla et al., 1999; Padilla et al., 2000; Padilla
et al., 2001; Padilla et al., 2008; Vogt et al., 2006).
Vogt, Schumacher, Roecker et al. (2007) described
the power output demands of different stages (flat
(FLAT), semi-mountainous (SMT) and mountain
(MT) stages) within the Tour de France in fifteen
professional cyclists. They showed, for example,
that mean power output was highest in MT (234 ±
13 W [3.3 ± 0.2 W/kg]), followed by SMT (228 ±
22 and [3.3 ± 0.3]) and FLAT stages (218 ± 18 W
[3.1 ± 0.3 W/kg]). In addition, studies have quanti-
fied the maximal mean power outputs over different
durations (15–1800 s) achieved during the varying
stage types (Vogt, Schumacher, Roecker et al.,
2007; Vogt, Schumacher, Blum, et al., 2007). The
quantification of such “record power outputs”
(Pinot & Grappe, 2011)or“Power Profile”(Allen
& Coggan, 2010) provides valuable evidence on
the differences in power output demands between
a variety of stage types.
The highlighted previous studies have contributed
to a greater understanding of intensity and load
demands of professional cycling races and potential
differences between a variety of competition
elements. However, previous studies evaluating
intensity and load demands of professional cycling
Grand Tours have been conducted more than 10
years ago, warranting an update. In addition,
besides the study by Vogt, Schumacher, Roecker
et al. (2007) and another case-study describing the
power output produced during flat and mountain
stages in the Giro d’Italia (Vogt, Schumacher,
Blum, et al., 2007), additional evidence on the
power output demands of different competition
elements within a Grand Tour is needed. Lastly, the
load demands of competition elements within a
Grand Tour have mainly been quantified using
heart rate based (i.e. TRIMP) measures (Padilla
et al., 2000; Padilla et al., 2001; Padilla et al., 2008),
whilst the description of external load measures (e.g.
Training Stress Score [TSS]) commonly used in
cycling, can provide valuable additional insight.
Accordingly, the purpose of this study was to
expand and update the current evidence base using
an in-depth analysis of the physical demands of a pro-
fessional cycling Grand Tour race and different stage
types within a Grand Tour.
Methods
Participants
Nine professional cyclists, whom are all part of the
same World-Tour professional cycling team, agreed
to participate in this investigation. Participants were
Table 1. Subject characteristics and laboratory measurements
(n = 9) obtained during incremental tests.
Variables Mean ± SD Range
Age (yr) 30 ± 5 25–39
Height (cm) 182 ± 6 174–193
Body mass (kg) 72.7 ± 5.6 64.5–82.0
PO at LT
1
(W) 301 ± 33 248–360
HR at LT
1
(beats min
−1
) 154 ± 12 137–168
PO at LT
2
(W) 360 ± 27 332–410
HR at LT
2
(beats min
−1
) 170 ± 12 151–185
W
max
(W) 420 ± 28 385–478
W
max
(W kg
−1
) 5.8 ± 0.3 5.4–6.2
HR
max
(beats min
−1
) 185 ± 11 168–201
VO
2max
(ml min
−1
kg
−1
)74±6 66–85
Abbreviations: PO: power output; LT
1
: first lactate threshold; HR:
heart rate; LT
2
: second lactate threshold; W
max
: maximal power
output achieved during the test; HR
max
: maximal heart rate;
VO
2max
: maximal oxygen uptake.
2D. Sanders & M. Heijboer
informed of the purpose and procedures of the
investigation. Written consent was obtained and
institutional ethics approval was granted and in
agreement with the Helsinki Declaration. Physical
characteristics of the participating cyclists are pre-
sented in Table 1. The participants roles within the
analysed race consisted of one general classification
contender, one sprinter and seven domestiques. In
addition, four of the seven domestiques were
considered good time trialists, having finished in the
top 20 of Grand Tour individual time trials either
within the analysed race or in previous races
Testing
Prior to the study (January), each participant per-
formed a laboratory incremental test. The test
started at a workload of 2.50 W kg
−1
and increased
with 0.50 W kg
−1
every 3 min until exhaustion.
Each cyclist performed the test on their own
bicycle, which was placed on an ergometer
(Cyclus2 ergometer, RBM Electronics, Leipzig,
Germany). Gas exchange was measured continu-
ously using a breath-by-breath gas analysis system
(Metalyzer 3B, Cortex, Leipzig, Germany) and
lactate measures were taken at the end of every
3 min stage and analysed directly using a portable
lactate analyser (Lactate Pro, Arkray KDK, Japan).
Three individual heart rate and power output zones
were established around a first (LT
1
) and second
lactate threshold (LT
2
) with LT
1
defined at
0.4 mmol L
−1
rises above baseline (Bourdon, 2013)
and LT
2
defined using the modified D
max
method
(Bishop, Jenkins, & Mackinnon, 1998). Three
zones were proposed using previously established
protocols (Sanders, Myers, & Akubat, 2017; Seiler
& Kjerland, 2006): zone 1, ≤LT
1
; zone 2, >LT
1
and < LT
2
; zone 3 ≥LT
2
. Peak heart rate obtained
during the incremental test was used as a measure
of maximal heart rate (HR
max
). The last completed
stage was used as the measure of maximal aerobic
power output (W
max
). If the stage was not completed
W
max
was calculated based on the fraction of the
completed stage where volitional exhaustion
occurred (Kuipers, Verstappen, Keizer, Geurten, &
van Kranenburg, 1985). The test was performed
until complete exhaustion to estimate V
̇
O
2max
. After
the test, breath-by-breath values were visually
inspected and V
̇
O
2max
was defined as the highest
30 s mean obtained during the test.
Physical demands and power profile
Competition data was collected during the 2016 Giro
d’Italia. Stages were classified into four categories:
flat stages (FLAT), semi-mountainous stages
(SMT), mountain stages (MT) and individual time
trials (TT). Stages were classified based on similar,
albeit slightly adapted, criteria previously described
(Padilla et al., 2001; Vogt, Schumacher, Blum,
et al., 2007): FLAT total distance riding uphill was
shorter than 13 km, uphill sections are scattered
along the stage with a maximum total elevation gain
of 2200 m, but never at the end of it; SMT, with a
total uphill distance of approximately 13–35 km,
total elevation gain of minimum 2500 m or less
when the climbs were in the last part of the stage;
MT, in which the total uphill distance was longer
than 35 km with minimum total elevation gain of
3000 m or the stage finished uphill with a climb of
at least 10 km. The first, ninth and fifteenth stage of
the 2016 Giro d’Italia included individual TT’s.
Elevation gain as well as heart rate and power
output were continuously measured (1 Hz) during
every stage (Pioneer Power Meter, Kawasaki, Kana-
gawa, Japan). Relative power output (W kg
−1
) was
calculated using the athlete’s pre-race bodyweight.
As part of a previous study, the concurrent validity
of the Pioneer power meter was evaluated by compar-
ing it to a Cyclus2 ergometer showing a standard
error of estimate of 6 W (Sanders, Taylor, Myers, &
Akubat, 2017). Riders were instructed to perform
zero-offset procedures prior to each stage according
to manufacturers’instructions. The distribution of
exercise time during the stages was analysed in
relation to the above-mentioned zones around LT
1
and LT
2
. Intensity distribution around these zones
was calculated to provide an descriptive of the inten-
sity characteristics of the different stage types within
the Grand Tour. Also, after every stage, rating of per-
ceived exertion (RPE) was measured using the CR-
10 scale proposed by Borg, Hassmen, and Lager-
strom (1987) based on the question: “How hard
was today’s stage?”
As a measure of external load the Training Stress
Score™(TSS) proposed by Coggan (2003) was
measured using the following formula:
TSS =
t×NPTM ×IFTM
FTP ×3600 ×100
where tis the duration of the exercise bout, NP™is
normalised power of the exercise bout (Coggan,
2003), IF™is intensity factor which is the ratio
between the NP and the individual’s FTP (Coggan,
2003). FTP is the individual’s functional threshold
power. In this study, FTP was estimated using the
laboratory incremental test data using the modified
D
max
. method (Bishop et al., 1998). As a heart rate-
based internal load measure the TRIMP method
Physical demands and power profile of different stage types within a cycling grand tour 3
proposed by Lucia et al. (2003) was used. TRIMP
was calculated based on the time spent in three pre-
defined heart rate zones. Zones were defined as
zone 1 below LT
1
, zone 2 between LT
1
and LT
2
and zone 3 above LT
2
, a different approach com-
pared to the original Lucia’s TRIMP that used venti-
latory thresholds to identify the zones (Lucia et al.,
2003). Each zone is given a coefficient of 1, 2 and
3, respectively. Time spent in each zone is multiplied
by the coefficient and then summated to provide a
total TRIMP score (Lucia et al., 2003). Both this par-
ticular TRIMP method and TSS have previously
been shown to have a strong dose–response relation-
ship with changes in aerobic fitness in competitive
road cyclists (Sanders, Abt, Hesselink, Myers, &
Akubat, 2017).
Statistical analysis
Race characteristics (volume, intensity, load) variables
were compared between stage types using a multilevel
random intercept model using Tukey’smethodfor
pairwise comparisons in R (R: A Language and
environment for statistical computing, Vienna,
Austria). Random effect variability was modelled
using a random intercept for each individual partici-
pant. Level of significance was established at P<.05.
Magnitude-based inferences were used to describe
the magnitude of the differences (Hopkins, Marshall,
Batterham, & Hanin, 2009). Standardised effect size
is reported as Cohen’sd, using the pooled standard
deviation as the denominator. Qualitative interpret-
ation of dwas based on the guidelines provided by
Hopkins et al. (2009)0–0.19 trivial; 0.20–0.59 small;
0.6–1.19 moderate; 1.20–1.99 large; ≥2.00 very large.
Results
A total of 165 stages were analysed (FLAT = 45,
SMT = 44, MT = 55, TT = 21). Race characteristics
are presented in Table 2. Early retirement in the
race due to crashes or illness and/or technical issues
with the mobile power meter resulted in incomplete
datasets for some participants for some stages.
Stages with incomplete datasets were excluded from
the overall analysis. SMT and MT stages were moder-
ate to largely longer in duration (d= 0.78–1.21) com-
pared to FLAT stages. However, MT was moderate to
largely shorter (d= 0.92–1.68) in terms of distance
compared to FLAT and SMT.
Intensity and load demands of the different stage
types are presented in Table 2. All the intensity
measures were highest in the TT compared to the
other (mass start) stage types. Mean heart rate and
mean power output were very largely higher (d=
3.54–5.48) in TT compared to the other stage
types. Peak heart rate was moderately higher in TT
compared to MT and FLAT (d=0.61–0.63) and
largely higher compared to SMT (d= 1.38). Mean
heart rate and power output was large to very largely
higher during MT compared to FLAT (d=1.68–
2.42) and SMT (d= 1.85–1.87). During TT’s, the
main proportion of time was spent at high intensity
(zone 3) for both heart rate (83.3 ± 11.8%) and
power output (64.1 ± 24.6%) (Figure 1). For
FLAT, SMT and MT the main proportion of time
Table 2. Race characteristics, intensity and load demands of the different stage types within the Grand Tour.
FLAT (n= 45) SMT (n= 44) MT (n= 55) TT (n= 21)
Duration (min) 277 ± 21 311 ± 35
a
311 ± 66
a
38 ± 24
a,b,c
Distance (km) 189 ± 15 214 ± 23
a
167 ± 33
a,b
21 ± 15
a,b,c
Speed (km h
−1
) 40.5 ± 1.26 40.6 ± 1.9 32.1 ± 3.4
a,b
36.5 ± 12.9
a,b,c
Elevation gain (m) 849 ± 684 1772 ± 784
a
3814 ± 996
a,b
377 ± 388
a,b,c
RPE 5.8 ± 1.9 6.5 ± 1.3 7.8 ± 1.5
a,b
6.8 ± 2.1
a,b
HR (beats min
−1
) 125 ± 9 128 ± 4 141 ± 10
a,b
177 ± 10
a,b,c
%HR
max
67 ± 5 67 ± 2 76 ± 5 97 ± 2
HR
peak
(beats·min
−1
) 177 ± 10 173 ± 4 177 ± 11 184 ± 12
PO (W) 196 ± 29 217 ± 20
a
254 ± 19
a,b,c
371 ± 47
a,b,c
PO (W kg
−1
) 2.68 ± 0.32 2.99 ± 0.27
a
3.50 ± 0.31
a,b
5.14 ± 0.79
a,b,c
TSS km
−1
1.14 ± 0.19 1.32 ± 0.20 1.97 ± 0.31
a,b
3.39 ± 1.39
a,b,c
TRIMP km
−1
1.55 ± 0.13 1.52 ± 0.14 2.10 ± 0.15
a,b
3.39 ± 0.17
a,b,c
TSS (AU) 217 ± 46 280 ± 40
a
329 ± 83
a,b
62 ± 32
a,b,c
TRIMP (AU) 298 ± 33 311 ± 53 359 ± 80
a
33 ± 32
a,b,c
Abbreviations: RPE: rating of perceived exertion; HR: heart rate; HR
max
: maximal heart rate; HR
peak
: peak heart rate achieved during the
stage; PO: power output; TSS: Training Stress Score; TRIMP: Training Impulse; sRPE: session rating of perceived exertion; FLAT: flat
stage; SMT: semi-mountainous stage; MT: mountains stage; TT: time trial.
a
Significantly different from FLAT.
b
Significantly different compared to SMT.
c
Significantly different compared to MS.
4D. Sanders & M. Heijboer
was spent at low intensity (zone 1) for both heart rate
(93.7 ± 5.4%, 96.2 ± 5.9%, 86.9 ± 13.1%, respect-
ively) and power output (79.5 ± 5.5%, 75.8 ± 5.7%,
68.6 ± 9.3%, respectively). Time spent at moderate
intensity (zone 2) was highest for TT followed by
MT for both heart rate (12.5 ± 5.9 and 11.3 ±
11.0%, respectively) and power output (20.2 ±
21.0% and 12.7 ± 2.9%, respectively).
Load quantified using TRIMP and TSS was very
largely (d= 3.92–8.15) higher in the mass start stage
types (FLAT, SMT, MT) compared to the individual
TT. Exercise load quantified using TSS and TRIMP
were moderately higher in MT compared to SMT (d
= 0.72–0.80) and moderate to largely higher compared
to FLAT (d= 1.08–1.73). Relative load quantified as
TSS km
−1
was very largely higher in MT compared
to FLAT and SMT (d= 2.55–3.32). Similarly,
TRIMP km
−1
was also very largely higher in MT
compared to FLAT and SMT (d= 3.93–4.00).
However, both TSS km
−1
and TRIMP km
−1
were
highest in TT with the difference being large to very
large (d= 1.67–12.3) compared to other stage types.
Figure 1: Proportion of total race time spent at three intensity zones
quantified using heart rate (A) and power output (B) for the differ-
ent stage types. FLAT: flat stage; SMT: semi-mountainous stage;
MT: mountain stage; TT: time trial.
Table 3. Maximal mean power outputs over different durations per stage type.
Stage type 5 s 10 s 30 s 60 s 120 s 5 min 10 min 20 min 30 min
FLAT PO 982 ± 124 836 ± 131 604 ± 121 498 ± 74 436 ± 49 382 ± 39 351 ± 41 322 ± 42 298 ± 44
PO (W kg
−1
) 13.42 ± 1.31 11.43 ± 1.50 8.24 ± 1.31 6.81 ± 0.81 5.97 ± 0.56 5.22 ± 0.43 4.80 ± 0.47 4.40 ± 0.50 4.08 ± 0.50
SMT PO 965 ± 121 812 ± 110 605 ± 69 523 ± 49
a
467 ± 33
a
423 ± 29
a
381 ± 28
a
338 ± 27
a
315 ± 30
a
PO (W kg
−1
) 13.26 ± 1.45 11.20 ± 1.54 8.35 ± 1.07 7.22 ± 0.75
a
6.44 ± 0.55
a
5.83 ± 0.45
a
5.25 ± 0.47
a
4.67 ± 0.45
a
4.34 ± 0.45
a
MT PO 922 ± 132
a
787 ± 110
a
567 ± 67
a,b
489 ± 58
b
443 ± 31
b
409 ± 27
a,b
391 ± 29
a
374 ± 30
a,b
360 ± 30
a,b
PO (W kg
−1
) 12.63 ± 1.54
a
10.78 ± 1.33
a
7.79 ± 0.99
a,b
6.72 ± 0.83
b
6.09 ± 0.56
b
5.62 ± 0.44
a,b
5.37 ± 0.42
a
5.13 ± 0.42
a,b
4.95 ± 0.44
a,b
TT PO 770 ± 135
a,b,c
694 ± 117
a,b,c
572 ± 96 510 ± 52 457 ± 42
a
420 ± 31
a
406 ± 27
a,b,c
375 ± 26
a,b
352 ± 26
a,b
PO (W kg
−1
) 10.64 ± 1.72
a,b,c
9.58 ± 1.47
a,b,c
7.92 ± 1.36 7.07 ± 0.81 6.35 ± 0.72
a
5.83 ± 0.51
a
5.62 ± 0.44
a,b,c
5.11 ± 0.40
a,b
4.76 ± 0.43
a,b
Abbreviations: PO: power output; FLAT: flat stage; SMT: semi-mountainous stage; MT: mountains stage; TT: time trial.
a
Significantly different from FLAT
b
Significantly different compared to SMT.
c
Significantly different compared to MS.
Physical demands and power profile of different stage types within a cycling grand tour 5
Maximal mean power outputs for various dur-
ations are presented in Table 3. Short (sprint) peak
power outputs (5–10 s) were moderate to largely
higher in FLAT and SMT type stages compared to
TT (d= 1.04–1.63). Differences between stage
types for 30 and 60 s maximal mean power outputs
were trivial to small. Maximal mean power output
over a duration of 2 min was moderately higher in
SMT compared to MT and FLAT (d= 0.75–0.76).
Maximal mean power outputs during a ‘moderate’
duration (5–10 min) were moderate to largely higher in
SMT, MT and TT compared to FLAT (d= 0.81–
1.62). Longer duration maximal mean power
outputs (20–30 min) were largely higher for MT
and TT compared to SMT and FLAT (d= 1.26–
1.68).
Discussion
The purpose of this study was to describe the inten-
sity and load demands of different stage types
within a professional cycling Grand Tour race, quan-
tified using both heart rate and power output based
metrics. The results of this study show the substantial
differences intensity and load demands as well as the
differences in power profile during different stage
types within a Grand Tour. The reported physical
demands and power profiles of different stage types
within a Grand Tour contribute to the growing
body of evidence on the physical demands of pro-
fessional cycling races. The detailed description of
these demands may allow coaches and practitioners
to design training strategies to optimally prepare for
these demands.
Substantial differences in intensity and load
demands were observed between different stage
types. In line with previous results, the intensity of
TT’s is substantially higher compared to mass start
stages (Padilla et al., 2000; Padilla et al., 2001;
Padilla et al., 2008). During the TT’s the main pro-
portion of time was spent at the higher intensity
zone (i.e. zone 3) for both heart rate and power
output. In addition, a TT was spent at an average
of 97% of HR
max
compared to 67–76% for the
mass start stage types. This is higher compared to
previously reported intensity during professional
time trials varying between 80% and 89% of HR
max
for prologue, short and long TT’s (Padilla et al.,
2000). Two out of the three analysed TT’s in this
study was relatively short with 9.8 and 10.8 km
respectively, potentially allowing a higher intensity
to be maintained compared to previous research. It
has previously been shown that the lower the distance
of the TT, the higher the % of HR
max
that can be
maintained (Padilla et al., 2000). Furthermore,
tactical strategies (i.e. all-out or conservative
approach) will influence the analysed intensity for
that cyclist (Padilla et al., 2000). However, in line
with previous research, TT’s are one of the most
demanding events in professional road cycling in
terms of exercise intensity. This is also shown by
the higher relative loads (i.e. TSS km
−1
and TRIMP
km
−1
)ofTT’s compared to mass start stages.
However, due to the lower exercise duration (and dis-
tance) of TT’s, overall exercise load is substantially
lower in TT’s, which is in line with previous results
(Padilla et al., 2000; Padilla et al., 2001; Padilla
et al., 2008). Given the substantial difference in the
demand of a TT, it is not surprising that cyclists
adopt specific training strategies to prepare for these
demands. Furthermore, previous research has indi-
cated that anthropometrics and physiological vari-
ables of cyclists specialising in TT’s can be different
compared to other cycling specialities (Lucia et al.,
2001; Lucia, Hoyos, & Chicharro, 2000; Mujika &
Padilla, 2001; Padilla et al., 1999).
For the mass start stage types, highest intensity and
total exercise load were found for MT followed by
SMT and FLAT. Even though no difference in dur-
ation was observed between MT and SMT, a moder-
ately higher load was observed during MT. This is
line with previous research showing that exercise
load is highest during MT (Padilla et al., 2001).
Mean power output was also higher during MT
(3.50 W kg
−1
), followed by SMT (2.99 W kg
−1
) and
FLAT (2.68 W kg
−1
). A recent study observed a
mean power output of 3.0 W kg
−1
in a large sample
of male professional cycling races (Sanders, van
Erp, & de Koning, 2018). In the current study,
power output during MT was higher than the
observed mean value in Sanders, van Erp, et al.
(2018), SMT was similar and mean power output
during FLAT was lower. Sanders, van Erp, et al.
(2018) didn’t differentiate between different type of
races or competition elements, making further com-
parisons not possible. Vogt, Schumacher, Roecker
et al. (2007) showed a relative mean power output
of 3.1 ± 0.3 W kg
−1
for FLAT stages, 3.3 ±
0.3 W kg
−1
for SMT and 3.3 ± 0.2 W kg
-1
for MT
in the Tour de France. Even though mean power
output was higher for MT, we observed a lower
mean power output during FLAT and SMT stages.
As total elevation gain for each stage type was not
reported, it is hard to directly compare these
results. However, even though some discrepancies
in overall results between studies can be observed,
this study confirms previous studies showing that
total elevation gain is a major contributor to overall
exercise load during cycling Grand Tours with a
greater total elevation resulting in greater exercise
load. In addition, during MT, a greater proportion
6D. Sanders & M. Heijboer
of time is spent at “moderate”(i.e. zone 2) and
“high”(i.e. zone 3) intensity, quantified with both
heart rate and power output, compared to FLAT
and MT. This is line with previous research
showing that time spent at an HR at and above the
lactate threshold is higher in MT followed by SMT
and FLAT (Padilla et al., 2001). These differences
in demands should be considered when planning
strategies in preparation for different competition
elements.
Differences were observed in maximal mean power
outputs over different durations comparing the differ-
ent stage types. Short-duration power outputs (5–
30 s) were higher in FLAT and SMT compared to
MT and TT. Pacing strategies contribute to the
lower maximal mean power outputs over 5–30 s in
TT compared to mass start stages as a more continu-
ous pacing strategy, without explosive ‘bursts’,is
typically adopted (and more favourable) in TT’sof
a duration longer than 10 min (Atkinson, Peacock,
Gibson, & & Tucker, 2007). Furthermore, given
the fact that seven stages with low elevation gain
(i.e. FLAT and some SMT) in the 2016 Giro
d’Italia ended in mass sprint finishes, this most
likely contributes to the higher 5–30 s peak power
outputs observed in FLAT and SMT compared to
MT (Menaspa et al., 2015). These results are in
line with Vogt, Schumacher, Roecker et al. (2007)
who observed higher maximal mean powers over a
duration of 15–60 s during FLAT and SMT com-
pared to MT in data from the Tour de France.
However, actual power outputs during the mass
start stages (FLAT, SMT, MT) were lower for
most of the durations compared to Vogt, Schuma-
cher, Roecker et al. (2007). When comparing mass
start stages, highest ‘intermediate’durations (2–
5 min) maximal mean power outputs were found
for the SMT, most likely due to the increased
amount of (relatively) shorter hills of a duration of
2–5 min in SMT stages. This is also in line with pre-
vious research showing the highest maximal mean
power outputs over durations of 3–5 min in SMT
compared to FLAT and MT (Vogt, Schumacher,
Roecker et al., 2007). We further observed higher
maximal mean power outputs over a longer duration
(i.e. 20 and 30 min) during MT and TT compared to
SMT and FLAT. Vogt, Schumacher, Blum, et al.
(2007) compared FLAT and MT within the Giro
d’Italia and also observed higher maximal mean
power outputs over longer durations (5 and 30 min)
in MT compared to FLAT (Vogt, Schumacher,
Blum, et al., 2007). In addition, substantially higher
maximal mean power outputs over 30 min were
observed in the Tour de France for MT compared
to SMT and FLAT stages (Vogt, Schumacher,
Roecker et al., 2007). The results of this study
provide further evidence for the notion that race
profile substantially contribute to the maximal mean
power output characteristics of stages within a
Grand Tour (Lucia et al., 2001; Padilla et al.,
2001). For example, shorter uphill sections (i.e.
SMT) will result in highest maximal mean power
outputs over a moderate duration (2–5min) whilst
with increasing total elevation gain due to long
uphill sections (i.e. MT stages) the long duration
maximal mean power outputs (i.e. 20–30 min)
become increasingly important. This study identifies
power outputs at specific durations that increase in
importance depending on the stage type. This
should be considered valuable information for
coaches/practitioners as a better understanding of
the demands of different competition elements can
directly inform training strategies in preparation for
these races (i.e. training could be prescribed/
adapted to match race demands). For example, opti-
mally preparing for key moments in an MT would
most likely favour training targeted at long duration
efforts (i.e. 20–30 min) whilst this differs for SMT
and FLAT stages where key moments in the race
require the ability to produce high power outputs
over shorter durations.
One limitation of this study is that the testing was
conducted at a single Grand Tour with a single
cycling team. Hence, one should be cautious in gen-
eralising these results to a wider population of pro-
fessional cycling. However, most of the results
reported in this study are in line with previous
studies investing the intensity and load demands of
professional cycling races. Therefore, these results
of this study contribute to the growing body of evi-
dence with regards to the intensity and load
demands of different stage types within a Grand
Tour. In addition, FTP is typically defined as the
maximal power output that can be sustained over
45–60 min and is typically assessed using field-
based time trials (Coggan, 2003). It must be
acknowledged that a specific field-based assessment
of FTP was not included in this study, but estimated
using the laboratory test, which increases the poten-
tial of measurement errors with regards to TSS
(Sanders, Taylor, et al., 2017). In addition, a limiting
factor of the current study design is that the testing
was conducted before the start of the competitive
season. There might be changes in physiological
capacity between the laboratory testing and the
testing of the race which will influence intensity and
load calculations. Nevertheless, since the margin of
improvement is smaller in these highly trained ath-
letes this is somewhat mitigated.
To summarize, this study provides valuable evi-
dence on the demands and power profile of different
competition elements within Grand Tour. It has been
Physical demands and power profile of different stage types within a cycling grand tour 7
shown that TT’s are one of the most demanding
events in professional road cycling in terms of exer-
cise intensity. This is shown by the higher relative
loads and proportion of time spent at high intensity
of TT’s compared to mass start stages. However,
due to the lower exercise duration (and distance) of
TT’s, overall exercise load is substantially lower in
TT’s compared to mass start stages. Comparing
mass-start stages, MT is the most demanding for
both intensity and overall load followed by SMT
and FLAT. In terms of maximal mean power
outputs, FLAT and SMT stage types are character-
ised by higher short-duration maximal power
outputs (5–30 s for FLAT, 30 s–2 min for SMT)
whilst TT and MT are characterised by higher
longer duration maximal power outputs (>10 min).
The results of this study contribute to the growing
body of evidence on the physical demands of different
competition elements within a cycling Grand Tour.
The detailed description of such demands, and the
identified differences between different stage types
or competition elements, may allow coaches and
practitioners to design training strategies to optimally
prepare for these demands.
Acknowledgements
We would like to thank the cyclists for their partici-
pation in this investigation.
Disclosure statement
No potential conflict of interest was reported by the authors.
References
Abbiss, C. R., Menaspa, P., Villerius, V., & Martin, D. T. (2013).
Distribution of power output when establishing a breakaway in
cycling. International Journal of Sports Physiology and
Performance,8(4), 452–455.
Allen, H., & Coggan, A. R. (2010). Training and racing with a power
meter (2nd ed.). Boulder, CO: Velopress.
Atkinson, G., Peacock, O., St Clair Gibson, A., & Tucker,
R. (2007). Distribution of power output during cycling:
Impact and mechanisms. Sports Medicine,37(8), 647-667
Bell, P. G., Furber, M. J., Van Somren K. A., Anton-Solanas, A.,
& Swart, J. (2017). The physiological profile of a multiple Tour
de France winning cyclist. Medicine & Science in Sports &
Exercise,49(1), 115-123. doi:10.1249/MSS.0000000000001
068
Bishop, D., Jenkins, D. G., & Mackinnon, L. T. (1998). The
relationship between plasma lactate parameters, Wpeak and 1-
h cycling performance in women. Medicine& Science in Sports
& Exercise,30(8), 1270–1275.
Borg, G., Hassmen, P., & Lagerstrom, M. (1987). Perceived exer-
tion related to heart rate and blood lactate during arm and leg
exercise. European Journal of Applied Physiology and
Occupational Physiology,56(6), 679–685.
Bouillod, A., Pinot, J., Soto-Romero, G., Bertucci, W., & Grappe,
F. (2017). Validity, sensitivity, reproducibility and robustness of
the powertap, stages and Garmin vector power meters in com-
parison with the SRM Device. International Journal of Sports
Physiology and Performance,12(8), 1023–1030. doi:10.1123/
ijspp.2016-0436
Bourdon, P. (2013). Blood lactate thresholds: Concepts and
applications. In R. Tanner & C. J. Gore (Eds.), Physiological
tests for elite athletes (pp. 77–102). Champaign, IL: Human
Kinetics.
Coggan, A. R. (2003). Training and racing using a power meter: An
introduction Level II Coaching Manual (pp. 123-145). Colorado
Springs, CO: USA Cycling.
Gardner, A. S., Stephens, S., Martin, D. T., Lawton, E.,
Hamilton, L., & Jenkins, D. (2004). Accuracy of SRM and
power tap power monitoring systems for bicycling. Medicine &
Science in Sports & Exercise,36(7), 1252–1258.
Hopkins, W. G., Marshall, S. W., Batterham, A. M., & Hanin, J.
(2009). Progressive statistics for studies in sports medicine
and exercise science. Medicine & Science in Sports & Exercise,
41(1), 3–13. doi:10.1249/MSS.0b013e31818cb278
Kuipers, H., Verstappen, F. T., Keizer, H. A., Geurten, P., & van
Kranenburg, G. (1985). Variability of aerobic performance in
the laboratory and its physiologic correlates. International
Journal of Sports Medicine,6(4), 197–201. doi:10.1055/s-2008-
1025839
Lucia, A., Hoyos, J., & Chicharro, J. L. (2000). Physiological
response to professional road cycling: Climbers vs. time trialists.
International Journal of Sports Medicine,21, 505–512.
Lucia, A., Hoyos, J., & Chicharro, J. L. (2001). Physiology of pro-
fessional road cycling. Sports Medicine,31(5), 325–337.
Lucia, A., Hoyos, J., Santalla, A., Earnest, C., & Chicharro, J. L.
(2003). Tour de France versus Vuelta a Espa??A: Which Is
Harder? Medicine & Science in Sports & Exercise,35(5), 872–
878. doi:10.1249/01.MSS.0000064999.82036.B4
Menaspa, P., Quod, M., Martin, D. T., Peiffer, J. J., & Abbiss, C.
R. (2015). Physical demands of Sprinting in professional road
cycling. International Journal of Sports Medicine,36(13), 1058–
1062. doi:10.1055/s-0035-1554697
Mujika, I., & Padilla, S. (2001). Physiological and performance
characteristics of male professional road cyclists. Sports
Medicine,31(7), 479–487.
Padilla, S., Mujika, I., Cuesta, G., & Goiriena, J. J. (1999). Level
ground and uphill cycling ability in professional road cycling.
Medicine & Science in Sports & Exercise,31(6), 878–885.
Padilla, S., Mujika, I., Orbananos, J., & Angulo, F. (2000).
Exercise intensity during competition time trials in professional
road cycling. Medicine & Science in Sports & Exercise,32(4),
850–856.
Padilla, S., Mujika, I., Orbananos, J., Santisteban, J., Angulo, F., &
Jose Goiriena, J. (2001). Exercise intensity and load during
mass-start stage races in professional road cycling. Medicine
and Science in Sports and Exercise,33(5), 796–802.
Padilla, S., Mujika, I., Santisteban, J., Impellizzeri, F. M., &
Goiriena, J. J. (2008). Exercise intensity and load during
uphill cycling in professional 3-week races. European Journal of
Applied Physiology,102(4), 431–438. doi:10.1007/s00421-007-
0602-9
Pinot, J., & Grappe, F. (2011). The record power profile to assess
performance in elite cyclists. International Journal of Sports
Medicine,32(11), 839–844. doi:10.1055/s-0031-1279773
Pinot, J., & Grappe, F. (2015). A six-year monitoring case study of
a top-10 cycling Grand Tour finisher. Journal of Sports Sciences,
33(9), 907–914. doi:10.1080/02640414.2014.969296
Sanders, D., Abt, G., Hesselink, M. K., Myers, T., & Akubat, I.
(2017). Methods of monitoring training load and their
Relationships to changes in fitness and performance in
8D. Sanders & M. Heijboer
competitive road cyclists. International Journal of Sports
Physiology and Performance,12(5), 668–675. doi:10.1123/ijspp.
2016-0454
Sanders, D., Myers, T., & Akubat, I. (2017). Training-Intensity
distribution in road cyclists: Objective versus Subjective
measures. International Journal of Sports Physiology and
Performance,12(9), 1232–1237. doi:10.1123/ijspp.2016-0523
Sanders, D., Taylor, R. J., Myers, T., & Akubat, I. (2017). A field-
based cycling test to assess predictors of endurance performance
and establishing training zones. Journal of Strength and
Conditioning Research.https://journals.lww.com/nsca-jscr/
Abstract/publishahead/A_field_based_cycling_test_to_assess_
predictors_of.96054.aspx
Sanders, D., van Erp, T., & de Koning, J. J. (2018). Intensity and
load characteristics of professional road cycling: Differences
between Men’s and Women’s races. International Journal of
Sports Physiology and Performance,1–23. doi:10.1123/ijspp.
2018-0190
Seiler, S., & Kjerland, G. O. (2006). Quantifying training intensity
distribution in elite endurance athletes: Is there evidence for an
"optimal" distribution? Scandinavian Journal of Medicine and
Science in Sports,16(1), 49–56. doi:10.1111/j.1600-0838.2004.
00418.x
Vogt, S., Heinrich, L., Schumacher, Y. O., Blum, A., Roecker, K.,
Dickhuth, H. H., & Schmid, A. (2006). Power output during
stage racing in professional road cycling. Medicine & Science in
Sports & Exercise,38(1), 147–151.
Vogt, S., Schumacher, Y. O., Blum, A., Roecker, K., Dickhuth, H.
H., Schmid, A., & Heinrich, L. (2007). Cycling power output
produced during flat and mountain stages in the Giro d’Italia:
A case study. Journal of Sports Sciences,25(12), 1299–1305.
doi:10.1080/02640410601001632
Vogt, S., Schumacher, Y. O., Roecker, K., Dickhuth, H. H.,
Schoberer, U., Schmid, A., & Heinrich, L. (2007). Power
output during the Tour de France. International Journal
of Sports Medicine,28(9), 756–761. doi:10.1055/s-2007-964982
Physical demands and power profile of different stage types within a cycling grand tour 9