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Purpose: This study provides a retrospective analysis of a large competition database describing the intensity and load demands of professional road cycling races, highlighting the differences between men's and women's races. Method: Twenty male and ten female professional cyclists participated in this study. During 4 consecutive years, heart rate (HR), rating of perceived exertion (RPE) and power output (PO) data were collected during both male (n = 3024) and female (n = 667) professional races. Intensity distribution in five HR zones was quantified. Competition load was calculated using different metrics including Training Stress Score (TSS), Training Impulse (TRIMP) and session-RPE (sRPE). Standardized effect size is reported as Cohen's d. Results: Large to very large higher values (d = 1.36 - 2.86) were observed for distance, duration, total work (kJ) and mean PO in men's races. Time spent in high intensity HR zones (i.e. zone 4 and zone 5) was largely higher in women's races (d = 1.38 - 1.55) compared to men's races. Small higher loads were observed in men's races quantified using TSS (d = 0.53) and TRIMP (d = 0.23). However, load metrics expressed per km were large to very largely higher in women's races for TSS∙km-1 (d = 1.50) and TRIMP∙km-1 (d = 2.31). Conclusions: Volume and absolute load are higher in men's races whilst intensity and time spent at high intensity zones is higher in women's races. Coaches and practitioners should consider these differences in demands in the preparation of professional road cyclists.
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“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
Note. This article will be published in a forthcoming issue of the
International Journal of Sports Physiology and Performance. The
article appears here in its accepted, peer-reviewed form, as it was
provided by the submitting author. It has not been copyedited,
proofread, or formatted by the publisher.
Section: Original Investigation
Article Title: Intensity and Load Characteristics of Professional Road Cycling: Differences
between Men’s and Women’s Races
Authors: Dajo Sanders1,2, Teun van Erp3, and Jos J. de Koning3,4
Affiliations: 1Physiology, Physiology, Exercise and Nutrition Research Group, University of
Stirling, Stirling, United Kingdom, 2Sport, Exercise and Health Research Centre, Newman
University, Birmingham, United Kingdom. 3Department of Human Movement Sciences,
Vrije Universiteit, Amsterdam, Amsterdam Movement Sciences, The Netherlands.
4Department of Exercise and Sport Science, University of Wisconsin La Crosse, La Crosse,
WI, USA.
Journal: International Journal of Sports Physiology and Performance
Acceptance Date: July 26, 2018
©2018 Human Kinetics, Inc.
DOI: https://doi.org/10.1123/ijspp.2018-0190
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
Title page
Title of the article
Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s
and Women’s Races
Submission type: Original investigation
Full names of the Authors and Institutional/Corporate Affiliations
Dajo Sanders, 1. Physiology, Exercise and Nutrition Research Group, University of Stirling,
Stirling, United Kingdom, 2. Sport, Exercise and Health Research Centre, Newman
University, Birmingham, United Kingdom
Teun van Erp, Department of Human Movement Sciences, Vrije Universiteit, Amsterdam,
Amsterdam Movement Sciences, The Netherlands
Jos J. de Koning, 1. Department of Human Movement Sciences, Vrije Universiteit,
Amsterdam, Amsterdam Movement Sciences, The Netherlands, 2. University of Wisconsin
La Crosse, Department of Exercise and Sport Science, La Crosse, USA
Contact details for the Corresponding Author.
Dajo Sanders, Physiology, Exercise and Nutrition Research Group, University of Stirling,
Stirling, United Kingdom, FK9 5NX, Stirling , United Kingdom
email: dajo.sanders@stir.ac.uk
Running head: Men’s and women’s professional cycling races
Abstract word count: 245
Text-only Word Count: 3653
Number of Figures and Tables: 2 figures, 3 tables
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
Abstract
Purpose: This study provides a retrospective analysis of a large competition database
describing the intensity and load demands of professional road cycling races, highlighting the
differences between men’s and women’s races. Method: Twenty male and ten female
professional cyclists participated in this study. During 4 consecutive years, heart rate (HR),
rating of perceived exertion (RPE) and power output (PO) data were collected during both male
(n = 3024) and female (n = 667) professional races. Intensity distribution in five HR zones was
quantified. Competition load was calculated using different metrics including Training Stress
Score (TSS), Training Impulse (TRIMP) and session-RPE (sRPE). Standardized effect size is
reported as Cohen’s d. Results: Large to very large higher values (d = 1.36 2.86) were
observed for distance, duration, total work (kJ) and mean PO in men’s races. Time spent in
high intensity HR zones (i.e. zone 4 and zone 5) was largely higher in women’s races (d = 1.38
1.55) compared to men’s races. Small higher loads were observed in men’s races quantified
using TSS (d = 0.53) and TRIMP (d = 0.23). However, load metrics expressed per km were
large to very largely higher in women’s races for TSS∙km-1 (d = 1.50) and TRIMP∙km-1 (d =
2.31). Conclusions: Volume and absolute load are higher in men’s races whilst intensity and
time spent at high intensity zones is higher in women’s races. Coaches and practitioners should
consider these differences in demands in the preparation of professional road cyclists.
Keywords: training impulse, cycling, training load, performance
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
Introduction
There are road cycling competitions all around the world across a broad spectrum that
ranges from youth and junior competitions to elite professional competitions. A male World
Tour professional cyclist will cycle around 25 000 to 35 000 kilometres in training and
competition each year including up to 100 competition days.1,2 In recent years, women’s road
cycling has been growing widely and in 2016 the Women’s World Tour was established with
more and more races running alongside the Men’s World Tour programme. Even though
published data on the training characteristics of female professional cyclists is limited, own
observations have shown that female World Tour female cyclists will typically cover around
13 000 to 18 000 kilometres in training and competition each year, including up to 65
competition days.
Due to technological advancements over recent years with mobile heart rate (HR) and
power meters, the collection of both physiological (i.e. HR) and work rate (i.e. power output
[PO]) data in the field is now widely possible to monitor the training and competition of
cyclists. As a result of this accessible data collection, both applied and more descriptive studies
on professional cycling (races) have been performed in recent decades. Most studies have
focused on describing the demands of men’s professional road cycling races1,3-6 with limited
research available describing the demands of women’s professional races.7,8 However, even
though some evidence regarding the demands of professional men and women’s races is
available, there is little evidence describing the differences between men’s and women’s races
in terms of exercise intensity and load demands. A detailed description of the demands of both
men’s and women’s races is valuable information for coaches and practitioners working with
these athletes on a daily basis. In addition, differences in intensity distribution between men’s
and women’s races may result in different training prescription and preparation for races.
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
Accordingly, this study aims to provide an analysis of a large competition database
describing the intensity and load demands of professional road cycling races, highlighting the
differences between men’s and women’s races.
Methods
Participants
Twenty male (mean ± SD: age: 27.5 ± 4.0 yrs, height: 184.8 ± 6.2 cm, bodyweight:
73.2 ± 7.1 kg) and ten female (age: 24.5 ± 4.5 yrs, height: 169.6 ± 6.7 cm, bodyweight: 60.5 ±
4.3 kg) highly trained professional cyclists, part of a current World Tour professional cycling
team, participated in this study. During the four-year monitoring period, the men’s team were
active on the Pro-Continental level for the first year and part of the World Tour for the last
three years. The women’s team finished every year within the top-10 of the Union Cycliste
Internationale (UCI) elite women team ranking over the course of the study period. Institutional
ethics approval was granted and, in agreement with the Helsinki Declaration, written informed
consent was obtained from the participants.
Research design
During 4 consecutive years, rating of perceived exertion (RPE), HR and PO data was
collected during both single-day and multi-day (stage) races for the males and females within
the team. Only UCI classified races were included for analysis. Depending on how long the
cyclist was involved in riding for the team, the data set of an individual cyclist contains data
ranging from 1 to 4 years. If a cyclist was not able to ride for a period of 3 months or more,
because of illness or an injury, the data set of this particular year was excluded. All data sets
were visually checked for erroneous data and incomplete data files due to technological issues
(e.g. flat battery of power meter or monitor) were excluded. If one of the three main variables
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
(i.e. RPE, HR or PO) was missing for a given race, and no erroneous data was present within
the given file, this dataset was still analysed using the available data.
Race characteristics
Intensity distribution was quantified based on the time spent in different HR zones. A
five-zone model was used to quantify the time spent in each intensity zone. HR zones were
based on percentages of maximal HR (HRmax) (zone 1: 50-59% HRmax, zone 2: 60-69% HRmax,
zone 3: 70-79% HRmax, zone 4: 80-89% HRmax, zone 5: 90-100%).9 HRmax was defined as the
highest HR achieved by the cyclist during training or competition of the analysed season and
adjusted every season (if needed). The determination of intensity zones is ideally approached
using the integration of physiological measures and anchored around physiological thresholds
(i.e. lactate or ventilatory thresholds)10, however, as no structured laboratory exercise testing
was incorporated over the course of this study, this was not feasible in this study. In addition,
the percentage of total race time spent at different power bands was compared between men’s
and women’s races.7 The power bands were constructed in steps of 0.75 Wkg-1 ranges from <
0.75 to > 7.50 Wkg-1.
Exercise load was calculated using different methods based on either HR, PO or RPE:
Edwards’ TRIMP (TRIMP)9, Training Stress Score (TSS)11 and session-RPE (sRPE).12
Edwards’ TRIMP was calculated based on the time spent in the five pre-defined HR zones
described above and multiplied by a zone-specific arbitrary weighting factor (zone 1: weighting
factor = 1, zone 2: weighting factor = 2, zone 3: weighting factor = 3, zone 4: weighting factor
= 4, zone 5: weighting factor = 5) and then summated to provide a total TRIMP score.9 TSS
was calculated based on power data collected with portable power meters (SRM, Jülich,
Welldorf, Germany and Pioneer, Kawasaki, Japan). TSS was calculated according to Coggan11,
using the following formula:
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
TSS = [ (t x NP x IF) / (FTP x 3600) ] x 100
where t is the duration of the exercise bout in seconds, NP™ is Normalized Power of the
exercise bout11, and IF™ is an intensity factor which is the ratio between the NP of the exercise
bout and the individual’s Functional Threshold power (FTP).11 FTP was determined as 95% of
the highest 20 min mean maximal PO, either achieved during a specific 20 min time trial in
training or adjusted when the mean maximal 20 min power output was higher during a race.
All riders were informed about the importance of the zero-calibration of the power meter and
were instructed to do the zero-calibration before every ride. Both Edwards’ TRIMP and TSS
have previously been shown to have a strong dose-response relationships with changes in
fitness in competitive road cyclists.13 As a subjective measure of internal load, sRPE was
calculated using the participants’ RPE (6-20 scale) and session duration. Riders were
familiarised with the RPE scale prior to the start of this study and were instructed on the use of
the scale. The RPE was obtained after the race, using an online self-filled in logbook, based on
the question: “How hard was your workout?. Even though the general recommendation is to
obtain a RPE score within 30 min of each competition, the time between the end of the race
and the cyclist filling in the RPE score could have been longer in this study (~1 5 hours).
However, previous studies have shown that athletes are able to recall RPE accurately between
24 - 48h after the end of the training or competition.14,15 Exercise load for the session was then
quantified by multiplying the RPE by the duration of the session (minutes).12 In addition,
similar to previous research5, load metrics (TRIMP, TSS and sRPE) and total work performed
(kJ) were also expressed relatively per kilometre (i.e. TRIMP∙km-1, TSS∙km-1, sRPE∙km-1 and
kJ∙km-1).
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
Statistical Analysis
Prior to analysis the assumption of normality was verified by using Shapiro-Wilk W
test and by visual inspection of QQ plots. Intensity and load variables were compared to each
other using a multilevel random intercept model using Tukey’s method for 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
participant. Level of significance was established at P < 0.05. In addition, magnitude based
inferences was used to further evaluate and describe the magnitude of the effects observed.16
Standardised effect size is reported as Cohen’s d, using the pooled standard deviation as the
denominator. Qualitative interpretation of d was based on the guidelines provided by Hopkins
et al.16: 0 - 0.19 trivial; 0.20 0.59 small; 0.6 1.19 moderate; 1.20 1.99 large; ≥ 2.00 very
large.
Results
In total, 616 women’s races and 3024 men’s races were collected and analysed. In total,
3640 races with power data (women’s races; n = 616, men’s races; n = 3024 ), 2346 races with
HR data (women’s races; n = 424, men’s races; n = 1730) and 1621 races with RPE (women’s
races; n = 533, men’s races; n = 1088) data were analysed. The main part of the dataset included
multi-day stage races for both men and women (78% of men’s races, 60% of women’s races).
Within the dataset, there were a total of 57 wins (1.9% of total files) and 289 top-10 finishes
(9.6% of total files) for the men’s team and 7 wins (1.1% of total files) and 121 top-10 finishes
(19.6% of total files) for the women’s team.
Table 1 presents the descriptive values for both the men’s and women’s races. Large
to very large higher values (d = 1.36 2.86) were observed for distance, duration and mean
PO in men’s races. However, Intensity Factor™, mean HR and mean HR as %HRmax were
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
largely higher (d = 1.36 1.80) in women’s races. Figure 1 graphically displays the differences
in the percentage time spent in different HR zones for men’s versus women’s professional
cycling races. Time spent in high intensity HR zones (i.e. zone 4 and zone 5) was largely higher
in women’s races (d = 1.38 1.55) compared to men’s races (42 ± 11% and 21 ± 16% versus
24 ± 12% and 6 ± 6%). Table 2 presents the absolute load and load expressed relative to
distance and duration for the men’s and women’s races. Total work (absolute and expressed
per km) was large to very largely (d = 1.48 2.73) higher in men’s races. Small higher absolute
loads were observed in men’s races quantified using TSS (d = 0.53) and TRIMP (d = 0.23).
However, load expressed per km was large to very largely higher in women’s races for
TSS∙km-1 (d = 1.50) and TRIMP∙km-1 (d = 2.31). Similar results were observed when load
metrics were expressed per minute with TSS∙min-1 (1.15 ± 0.19 AU vs 0.89 ± 0.18 AU) and
TRIMPmin-1 (2.80 ± 0.44 AU vs 3.68 ± 0.41 AU) being large to very largely (d = 1.34 2.04)
higher in women’s races.
Figure 2 presents the percentage of competition time spent at different relative PO
(W∙kg-1) bands. Time spent at the lower end of the power bands (0.76 3.00 W∙kg-1) was
moderately higher for women’s races (d = 0.65 1.16). Time spent at the higher end of the
power bands (4.51 6.75 W∙kg-1) was moderately higher for men’s races (d = 0.60 0.72).
Table 3 presents the differences in intensity and load metrics between men’s and
women’s races for both single-day and multi-day stage races. Mean HR, mean HR as a
percentage of HRmax and TRIMPkm-1 were moderately higher in single-day compared to multi-
day races for both men and women (d = 0.66 0.96). Mean PO (Wkg-1), RPE, Intensity Factor
and TSSkm-1 were also higher in single-day races for both men and women with these
differences being small (d = 0.26 0.59).
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
Discussion
This study provides a retrospective analysis of a large competition database (~ 3700
professional road cycling races) describing the intensity and load demands of professional road
cycling races, highlighting the differences between men’s and women’s races. This study
reports the substantial differences in intensity and load characteristics of men’s versus women’s
races. Within expectations, men’s cycling races are higher in duration, distance, total work,
absolute PO and load. However, women spent a substantially bigger proportion of time at
higher intensity zones compared to men’s races. In addition, load expressed relative to distance
or duration is large to very largely higher in women’s races compared to men’s races. These
descriptive results contribute to a better understanding of the demands of professional cycling
races and the specific differences between men’s and women’s races.
Because of the differences in race format and regulations in men’s versus women’s
races, the substantial higher duration, distance and total work (kJ) are not surprising. Following
the regulations of the international cycling federation the UCI, one day (professional) races for
women are limited to a maximum of 160 km on the highest level (“World Tour”) whilst the
longest one-day races for men can be around 260 up till 300 km. Obviously, these regulations
largely contribute to the observed differences within this study, especially relating to the
‘volume’ based metrics. However, metrics expressed relatively (i.e. % of total race time, load
per km) where substantially higher in women’s races. This is nicely illustrated by Figure 1
showing a substantially higher proportion of time spent at the highest HR zones (i.e. zone 4
and zone 5) in women’s races compared to men’s races. In addition, the mean HR relative to
their maximal HR is 10% higher (79 vs 69%) in women’s races compared to men’s races.
Hence, it seems that women compensate the shorter duration of their races with a higher
intensity and different riding style. To the best of the authors’ knowledge, this is the first study
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
to specifically highlight the substantial differences in intensity demands comparing men’s to
women’s professional cycling races. Due to the substantial differences in the proportion of total
competition time spent at high intensity, training strategies to prepare for these demands (e.g.
high intensity interval training formats) may not be used interchangeably for male and female
professional cyclists.
It is important to note that, despite of the substantial differences in objective intensity
metrics based on HR and PO between men’s and women’s races, perceived intensity (i.e. RPE)
was not different when comparing men’s and women’s races. Hence, differences in physical
demands, objective intensity and load characteristics may still result in similar perceived
intensity suggesting that subjective and objective metrics have the ability to reflect different
constructs within the training process. This is in line with previous research in cyclists
describing the differences between subjective and objective measurements of intensity (and
load) in evaluating training characteristics and how the combination of subjective and objective
metrics can be used to detect states of excessive fatigue or adaptation.17-19
Mean PO was largely higher in men’s races compared to women’s races which is
suggested to be largely determined, among other factors, by inherent physiological differences
between men and women, specifically relating to maximal oxygen uptake and body
composition (i.e. higher lean mass in males).20 This results in the typically higher aerobic
capacity observed in male professional cyclists21 compared to female cyclists22. When
controlled for bodyweight, the differences between men’s and women’s races in terms of mean
PO is decreased; from a large difference (d = 1.81) for absolute PO to a small difference (d =
0.44) in relative PO (W∙kg-1). The substantial lower bodyweight (60.5 ± 4.3 kg vs 73.2 ± 7.1
kg) for the female cyclists in this study most likely contributes to the smaller difference. When
comparing to previous literature, the observed mean PO in this study during women’s races
(2.8 ± 0.4 W∙kg-1) is lower compared to the 3.0 3.4 W∙kg-1 previously reported mean PO’s
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
for women’s world cup races7,8. The main reason proposed for this difference is that the
previously reported values only evaluated world cup races whilst the competition database in
this study also incorporated non-world cup (i.e. lower level) races in the analysis. In terms of
men’s races, Ebert et al.3 showed a mean PO of 2.7 W∙kg-1 for flat and 2.9 W∙kg-1 for hilly
professional male races3, whilst we observed a mean PO of 3.0 ± 0.5 W∙kg-1 in this study.
Furthermore, the mean PO observed in this study is similar to what has previously been
observed in professional cyclists during a multistage cycling race (3.1 ± 0.2 W∙kg-1)4 and the
mean PO during the competitive season of 4 professional cyclists (3.1 W∙kg-1).1 Even though
there are some discrepancies between studies, based on the current evidence, female
professional cycling races will vary on average around 2.8 W∙kg-1 with world cup races > 3.0
W∙kg-1. On average, male professional cycling races will vary around 3.0 3.1 W∙kg-1 whilst
this may be higher or lower depending on the level of competition, ‘race profile’ (e.g. elevation
gain23,24) and race tactics.
Intensity and load demands of professional men’s cycling races has been evaluated in
a number of previous studies1,6,23,24, however, studies evaluating the characteristics of women’s
professional cycling races remains limited. Recently, Menaspa et al.7 evaluated the demands
of world cup competitions in professional women road cycling races. Even though the reporting
of their results doesn’t allow an exact comparisons, percentage of competition time spent at
different power bands seems to be similar in this study compared to the results by Menaspa et
al.7. The biggest proportion of competition time is spent at PO < 0.75 W∙kg-1 due to non-
pedalling activity. Besides that, similar to the results by Menaspa et al.7, a big proportion of
time is spent at 1.51 4.50 W∙kg-1 in women’s races. A slight shift to the right can be seen in
terms of the proportion of competition spent at the different power bands for men’s races with
a big proportion of time spent at 2.26 5.25 W∙kg-1. This right shift in the power bands is caused
by the higher relative and absolute PO of men’s races compared to women’s races (Table 1).
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
Even though this provides valuable insight into the (mean) demands of professional cycling
races, it should be acknowledged that the level of competition (i.e. World Tour vs no World
Tour races), level of athlete7, race profile24 and race tactics7 can have a large effect on the
quantified demands of the race. However, as the main aim of this study was to examine the
differences in intensity and load of men’s versus women’s professional cycling as a whole
and not the differences between the demands of different levels of races, it was chosen to adopt
an approach where all the data was analysed and compared in order to maximise the sample
size. Furthermore, the level hierarchy of professional men’s races is more extensive and
complicated compared to women’s cycling making such direct comparisons difficult to
interpret.
In line with previous research25, small to moderate higher intensity and load per
kilometre were observed for single-day races compared to multi-day stage races for both men’s
and women’s races. However, irrespective of the race format (i.e. single or multi-day race)
intensity was higher in women’s races for both single and multi-day races. For example, during
single-day and multi-day races mean HR was at 74% and 69% of HRmax for men’s races whilst
it was at 81% and 77% of HRmax for women’s races, respectively.
There are some limitations that need to be taken in to account when interpreting the
results of the study. The main causes for limitations occurring with this analysis comes from
the fact that this was a retrospective analysis of race data. For example, the HR zones used in
this study are based on ranges of a percentage of maximal HR whilst it must be acknowledged
that there can be day-to-day variations in maximal HR (e.g. due to fatigue18,26) that can
influence the data analysis. Ideally, HR zones would be anchored around physiological
thresholds such as the first and second lactate or ventilatory thresholds.10,27,28 However, during
the time of the analysis, no regular and controlled laboratory exercise testing was implemented
within the team, making such approaches (retrospectively) not feasible. Furthermore, for this
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
same reason, more individualized approaches to load quantification previously used in
cycling13 such as individualized TRIMP29 or Lucia’s TRIMP30 were not feasible in our study.
However, it must be noted that both Edwards’ TRIMP and TSS showed strong dose-response
validity with changes in aerobic fitness in competitive road cyclists.13 In addition, FTP which
was determined using the year’s best 20 min mean maximal PO achieved in training or racing.
Hence, during certain time periods FTP can be either under- or overestimated which would
lead to variability and inaccuracies with regards to the determination of TSS. Whilst
acknowledging these limitations caused by the retrospective analysis, this approach has made
it possible to collect and analyse a large competition database in elite athletes (~3700 races),
which has currently not been published before. Thereby, despite of the mentioned limitations,
this study highlights important differences in competition intensity and load demands between
men’s and women’s races.
Practical Application
These descriptive results contribute to a better understanding of the demands of
professional cycling races and the specific differences between men’s and women’s races.
Within expectations, men’s cycling races are higher in duration, distance, total work (kJ),
absolute PO and load. However, the intensity of women’s races is substantially higher
compared to men’s races highlighted by the time spent in high intensity zones and the higher
relative intensity metrics (e.g. %HRmax) in women’s races. Coaches and practitioners should
consider these differences in demands in the preparation of professional cyclists. These results
may indicate that preparation strategies between men’s and women’s races cannot be used
interchangeably. Particularly, the substantial differences in the time spent at high intensity (HR
zones) in women’s races may suggest that preparation strategies for these demands (e.g. high
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
intensity interval training formats/protocols) may require a different approach compared to
men’s races.
Conclusions
To conclude, even though overall volume and absolute load are higher in men’s races,
relative intensity and time spent at high intensity zones is higher in women’s races, despite a
similar RPE. Coaches and practitioners should consider these differences in demands in the
preparation of professional road cyclists. These results may indicate that preparation strategies
between men’s and women’s races cannot be used interchangeably.
Acknowledgments
No sources of funding were used to compose this article. The authors have no conflicts of
interest that are related to the described content of this manuscript.
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
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International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
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International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
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International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
Figure 1. Intensity distribution as percentage time spent in different heart rate zones in men’s
versus women’s professional cycling races
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
Figure 2. Power output distribution as % time spent in different power bands. *presents a
moderate difference (d ≥ 0.60).
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
Table 1. Volume and intensity characteristics of women’s and men’s professional cycling
races.
Women’s races
Men’s races
Mean ± SD
Mean ± SD
Distance (km)
116 ± 17*
183 ± 32
Duration (min)
194 ± 30*
285 ± 56
Mean PO (W)
167 ± 21*
216 ± 34
Mean PO (W∙kg-1)
2.8 ± 0.4*
3.0 ± 0.5
Intensity Factor™
0.83 ± 0.07*
0.73 ± 0.08
Mean HR (beats∙min-1)
152 ± 13*
133 ± 12
Mean HR (%HRmax)
79 ± 10*
69 ± 6
HRmax (beats∙min-1)
185 ± 10
180 ± 12
Mean RPE (AU)
(6-20 scale)
15.4 ± 1.5
15.4 ± 2.1
Abbreviations: PO, power output; HR, heart rate; HRmax, maximal heart rate; RPE, rating of perceived exertion. Qualitative
interpretation of d was based on the guidelines provided by Hopkins et al.16
*Significant difference (P < 0.05)
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
Table 2. Absolute load in competition and load metrics expressed relative to distance in men’s
versus women’s professional cycling races.
Women’s
races
Men’s races
Differences men’s vs women’s races
Cohen’s d
Total work (kJ)
1958 ± 384*
3734 ± 918
2.73 Very large
TSS (AU)
224 ± 49*
255 ± 68
0.53 Small
TRIMP (AU)
700 ± 141*
739 ± 203
0.23 Small
sRPE (AU)
2982 ± 585*
4370 ± 1144
1.61 - Large
kJkm-1
16.8 ± 2.5*
20.4 ± 3.9
1.48 Large
TSSkm-1 (AU)
1.92 ± 0.35*
1.40 ± 0.31
1.50 Large
TRIMPkm-1 (AU)
6.02 ± 0.84*
4.08 ± 0.94
2.31 Very large
sRPEkm-1 (AU)
25.6 ± 4.0*
24.0 ± 4.3
0.42 Small
Abbreviations: TSS, Training Stress Score; TRIMP, Edwards’ training impulse; sRPE, session rating of perceived
exertion. Qualitative interpretation of d was based on the guidelines provided by Hopkins et al.16
*Significant difference (P < 0.05)
International Journal of Sports Physiology and Performance
“Intensity and Load Characteristics of Professional Road Cycling: Differences between Men’s and Women’s Races
by Sanders D, van Erp T, de Koning JJ
International Journal of Sports Physiology and Performance
© 2018 Human Kinetics, Inc.
Table 3. Differences in intensity and load metrics between women’s and men’s races for single-day and multi-day races
Single day
Multi stage
Women’s races
Men’s races
Cohen’s d
Women’s races
Men’s races
Cohen’s d
Mean PO (Wkg-1)
2.84 ± 0.30*
3.17 ± 0.41
0.94 Moderate
2.68 ± 0.34*
2.99 ± 0.43
0.83 Moderate
Mean HR (beats∙min-1)
157 ± 10*
140 ± 10
1.57 Large
149 ± 12*
130 ± 10
1.66 Large
Mean RPE (AU)
15.2 ± 1.6*
16.1 ± 1.9
0.51 Small
15.5 ± 1.5
15.6 ± 2.0
0.04 Trivial
Intensity Factor™
0.86 ± 0.05*
0.76 ± 0.07
1.40 Large
0.82 ± 0.08*
0.73 ± 0.07
1.18 Moderate
Mean HR (%HRmax)
81 ± 4*
74 ± 5
1.77 Large
77 ± 4*
69 ± 5
1.80 Large
TSS (AU)
236 ± 48*
286 ± 80
0.78 Moderate
217 ± 52*
254 ± 63
0.64 - Moderate
TRIMP (AU)
737 ± 151*
868 ± 207
0.73 - Moderate
670 ± 124*
702 ± 186
0.20 Small
TSSkm-1 (AU)
2.01 ± 0.30*
1.49 ± 0.27
1.80 Large
1.88 ± 0.37*
1.41 ± 0.30
1.41 Large
TRIMPkm-1 (AU)
6.33 ± 0.72*
4.63 ± 0.72
2.34 Very large
5.80 ± 0.85*
4.04 ± 0.90
2.01 Very large
Abbreviations: PO, power output; HR, heart rate; RPE, rating of perceived exertion; TSS, Training Stress Score; TRIMP, Edwards’ training impulse; Qualitative interpretation of d was
based on the guidelines provided by Hopkins et al.16
*Significant difference (P < 0.05)
International Journal of Sports Physiology and Performance
... 5 However, this trend has changed in the last few years, as a growing number of papers have been published on women's cycling. [6][7][8][9][10][11][12][13][14][15] Several studies analyzed training 7 and competition demands 6,8 reporting data on elite cyclists' internal and external loads, such as distance, duration, power output, heart rate, or work. In addition to this, some other studies have focused on women cyclists' adaptation to altitude 16,17 and strength training, 9,18 among other topics, revealing that women cyclists improved their performance by following the "Live High-Train Low" training method, with an increase in both hemoglobin and VO 2 max levels. ...
... 5 However, this trend has changed in the last few years, as a growing number of papers have been published on women's cycling. [6][7][8][9][10][11][12][13][14][15] Several studies analyzed training 7 and competition demands 6,8 reporting data on elite cyclists' internal and external loads, such as distance, duration, power output, heart rate, or work. In addition to this, some other studies have focused on women cyclists' adaptation to altitude 16,17 and strength training, 9,18 among other topics, revealing that women cyclists improved their performance by following the "Live High-Train Low" training method, with an increase in both hemoglobin and VO 2 max levels. ...
... However, women cyclists spent more time at highintensity heart rate zones than men and pedaled at a higher relative power output. 6,7 When comparing women cyclists of different competitive levels, Top 10 and Top 5 World Cup cyclists had higher mean maximal power output, spent more time at higher intensities, and performed a significantly higher number of short high-intensity efforts than the rest of the participants. 8,15 Single-day races also had higher volume, load, and intensity than multiday races. ...
Article
Purpose: To identify the main training characteristics and competitive demands in women's road cycling. Methods: A systematic search was conducted on 5 databases according to PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines. The articles had to be primary studies, written after 1990 with a sample of competitive women between the ages of 15 and 50. The Quality Assessment Tool for Quantitative Studies and the Oxford Levels of Evidence scales were used. Results: The search yielded 1713 articles, of which 20 were included. Studies on training and competitive demands (n = 5) found that both external and internal loads are higher in women than in men. Studies on strength and endurance training (n = 5) showed that both velocity-based and heavy-load strength training programs performed at least 2 days per week and including 3 to 4 lower-body exercises improved performance. Altitude-training studies (n = 3) found that "Live High-Train Low" was effective to increase performance during the first 9 days after the training camp. The 7 remaining studies focused on a range of topics. The methodological quality was strong for 12 studies and moderate for 8. In contrast, the level of evidence was high in 7 and low in the other 13. Conclusions: Endurance training and competitive demands in women's road cycling are higher than those of men. Strength training is effective in women when the frequency, intensity, and number of exercises are appropriate, while altitude training should be completed a few days before competing. Further studies are warranted to better define the participants' competitive level, using a methodological design with a higher level of evidence.
... Likewise, the impact of intensified training on the ability to perform repeated sprinting when separated by periods of moderate intensity is also of interest, especially for road cycling given the varied power and long exercise duration in competition. 10 Yeo et al. 11 reported that interval training improved performance in a 60-min time-trial that was preceded by 60 min of submaximal exercise (preload), underpinning that high-intensity interval training (HIT) has the potential to improve long-duration performance. Inclusion of other modalities of intense training such as resistance training has also been shown to improve 5-min cycling performance following a 3-h preload in female duathletes, 12 collectively suggesting that the addition of intense training can enhance the durability of cyclists (i.e., higher fatigue resistance in the final part of a competition). ...
... Such a change is considered highly relevant given the varied nature of road cycling races with periods of frequent power bursts followed by periods with moderate intensity. 10 In turn, when averaged over the entire preload, sprint performance was increased in LOW in contrast to the study hypothesis. The mechanisms underpinning this long-term repeated sprint performance improvement are not clear from the present study. ...
Article
Full-text available
Introduction: Male elite cyclists (average VO2 -max: 71 ml/min/kg, n=18) completed seven weeks of high-intensity interval training (HIT) (3x/week; 4-min and 30-s intervals) during the competitive part of the season. The influence of a maintained or lowered total training volume combined with HIT was evaluated in a two-group design. Weekly moderate intensity training was lowered by ~33% (~5 hours) (LOW, n=8) or maintained at normal volume (NOR, n=10). Endurance performance and fatigue resistance was evaluated via 400 kcal time-trials (~20 min) commenced either with or without prior completion of a 120 min preload (including repeated 20-s sprints to simulate physiologic demands during road-races). Results: Time-trial performance without preload was improved after the intervention (P=0.006) with a 3% increase in LOW (P=0.04) and a 2% increase in NOR (P=0.07). Preloaded time-trial was not significantly improved (P=0.19). In the preload, average power during repeated sprinting increased by 6% in LOW (P<0.01) and fatigue resistance in sprinting (start vs end of preload) was improved (P<0.05) in both groups. Blood lactate during the preload was lowered (P<0.001) solely in NOR. Measures of oxidative enzyme activity remained unchanged, whereas the glycolytic enzyme PFK increased by 22% for LOW (P=0.02). Conclusion: The present study proves that elite cyclists can benefit from intensified training during the competitive season both with maintained and lowered training volume at moderate intensity. In addition to benchmarking effects of such training in ecological elite settings, the results also indicate how some performance and physiological parameters may interact with training volume.
... Created with biorender.com Elite endurance athletes possess extremely high maximal oxygen uptake (V O2max) (Saltin and Astrand, 1967), allowing high, sustained rates of metabolic activity through carbohydrate (CHO) and fatty acid metabolism (Romijn et al., 1993;van Loon et al., 2001) permitting higher sustained workloads over long distances (Sanders, van Erp and de Koning, 2019) and durations (Lucia et al., 1998;Lucia et al., 2002), all of which, critical factors in endurance sport competitive success. At the skeletal muscle level, a key hallmark of endurance training adaptation is an increase in the number and capacity of mitochondria (Holloszy, 1967;Holloszy et al., 1970Holloszy et al., , 1977Oscai and Holloszy, 1971;Holloszy and Coyle, 1984), which is highly correlated to whole-body V O2max, a proxy for metabolic function and endurance capacity (van der Zwaard, Brocherie and Jaspers, 2021). ...
Thesis
Endurance athletes have traditionally been advised to consume high carbohydrate intake before, during and after exercise to support high training loads and facilitate recovery. Accumulating evidence suggests periodically training with low carbohydrate availability, termed “train-low”, augments skeletal oxidative adaptations. Comparably, to account for increased carbohydrate utilisation during exercise in hot environmental conditions, nutritional guidelines advocate high carbohydrate intake. Recent evidence suggests heat stress induces oxidative adaptation in skeletal muscle, augmenting mitochondrial adaptation during endurance training. This thesis aimed to assess the efficacy of training with reduced carbohydrate and the impact of elevated ambient temperatures on performance and metabolism. Chapter 4 demonstrated 3 weeks of Sleep Low-Train Low (SL-TL) improves performance when prescribed and completed remotely. Chapter 5 implemented SL-TL in hot and temperate conditions, confirming SL-TL improves performance and substrate metabolism, whilst additional heat stress failed to enhance performance in hot and temperate conditions following the intervention. Chapters 6 and 7 optimised and implemented a novel in vitro skeletal muscle exercise model combining electrical pulse stimulation and heat stress. Metabolomics analysis revealed an ‘exercise-induced metabolic response, with no direct metabolomic impact of heat stress. Chapter 8 characterised the systemic metabolomic response to acute exercise in the heat following SL-TL and heat stress intervention revealing distinct metabolic signatures associated with exercise under heat stress. In summary, this thesis provides data supporting the application of the SL-TL strategy during endurance training to augment adaptation. Data also highlights the impact of exercise, environmental temperature and substrate availability on skeletal muscle metabolism and the systemic metabolome. Together, these data provide practical support for the efficacy of the SL-TL strategy to improve performance and adaptation whilst casting doubt on the utility of this approach in hot environments in endurance-trained athletes.
... Professional male road cyclists train between 16 and 28 h per week, and mountain cyclists between 14 and 18 h; amateur cyclists train less, but in many cases they train as much as 8-10 h per week [5]. Professional female road cyclists train approximately 12-16 h per week [6]. When conditions are adverse (excessive cold, rain and wind) cyclists use spinning bikes or cycle on rollers (balance, fluids, magnetic and direct transmission). ...
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Full-text available
COVID-19 lockdowns involved radical changes in the habits and lifestyles of many. Notably, athletes saw their training routines altered. The relationship between lockdown effects and psychological variables was analysed using a sample comprising 1032 cyclists (average age: 42.97 years, s.d. = 8.94), taking part in the first cycling competition after lockdown. The target variables included psychological variables such as frustration tolerance, subjective vitality, autonomy self-determination, and affective status, as well as sociodemographic and training habits-related variables.The results showed that the constructs under analysis are related. Pre- and post-competition psychological variables were measured, and no significant differences were detected, except concerning subjective vitality. A regression analysis model was designed to analyse the impact of frustration tolerance, autonomy self-determination, and affective status on subjective vitality. The results reveal a lineal relationship (F = 71.789, p
... (accessed on 30 September 2022)). The identification of the exercise intensity zones and the power output profiles were obtained according to previous studies [11]. The first variable was the percentage of time with respect to the overall competition duration that the cyclist spent in each intensity zone (i.e., eleven intensities from <0.75 to >7.50 W·kg −1 , with increments of 0.75 W·kg −1 between them). ...
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Various power meters are used to assess road-cycling performance in training and competition, but no previous study has analyzed their interchangeability in these conditions. Therefore, the purpose was to compare the data obtained from two different power meters (PowerTap vs. Power2Max) during cycling road races. A national-level under-23 male competitive cyclist completed six road-cycling official competitions (five road races and one individual time trial), in which power output was simultaneously registered with the two power meters. After this, the main power output variables were analyzed with the same software. The average and critical power obtained from the PowerTap power meter were slightly lower than from the Power2Max power meter (3.56 ± 0.68 and 3.62 ± 0.74 W·kg−1, 5.06 and 5.11 W·kg−1, respectively), and the correlations between both devices were very high (r ≥ 0.996 and p < 0.001). In contrast, the PowerTap power meter registered a significantly higher (p < 0.05) percentage of time at <0.75 and >7.50 W·kg−1 and power profile at 1, 5 and 10 s. In conclusion, the data obtained in competitions by the two power meters were interchangeable. Nevertheless, the Power2Max power meter underestimated the pedaling power during short and high-intensity intervals (≤10.0 s and >7.50 W·kg−1) compared to the PowerTap power meter. Therefore, the analysis of these efforts should be treated with caution.
... Professional road cycling is characterized by racing over varied topography, ranging from flat to extremely mountainous terrain. 1,2 Researchers have frequently attempted to quantify the characteristics of performance in elite cycling. 3,4 Primarily the focus has been on examining the relationships between physiological variables and race performance 5,6 and in some cases, specific tests have been developed in order to predict performance in subsequent races. ...
Article
Objectives This study aimed to investigate predictors of cycling performance in U23 cyclists by comparing traditional approaches to a novel method-the compound score. Thirty male U23 cyclists (N=30, age 20.1±1.1 yrs, body mass 69.0 ± 6.9 kg, height 182.6 ± 6.2 cm, V O 2max 73.8 ±2.5 mL.kg-1 .min-1) participated in this study. Design and Methods Power output information was derived from laboratory and field-testing during pre-season and mean maximal power outputs (MMP) from racing season. Absolute and relative 5-min MMP, 5-min MMP after 2,000 kJ (MMP 2,000KJ), allometric scaling and the compound score were compared to the race score and podium (top 3) performance during a competitive season. Positive and negative predictive values were calculated for all significant performance variables for the likelihood of a podium performance. Results The absolute 5-min MMP of the field test revealed the highest negative predictive capacity (82.4%, p=0.012) for a podium performance. The compound score of the 5-min MMP 2,000KJ demonstrated the highest positive and average predictive capacity (83.3%, 78.0%, p=0.007-respectively). The multi-linear regression analysis revealed a significant predictive capacity between performance variables and the race score (R 2 = 0.55, p=0.015). Conclusions Collectively the results of the present study reveal that the compound score, alongside absolute power, was able to predict the highest positive and average likelihood for a podium performance. These findings can help to better understand performance capacity from field data to predict future cycling success.
... Typical statements from the coaches include: Many of the investigated endurance sports include fewer and/or shorter competitions for women, which consequently influence how training sessions are designed to meet the competition-schedule and the sport-specific competition demands. For example, in cycling there are fewer and shorter races for women (14), while in biathlon and cross-country skiing competitions have so far been shorter for women (12). In addition, equipment can be relatively heavier for women such as the rifle in biathlon (16). ...
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Full-text available
This scientific short report investigated how successful male coaches perceive gender differences in training characteristics and coaching practice among medal-winning endurance athletes. Ten male Norwegian coaches with a track record of coaching both female and male endurance world-class athletes (total of 269 Olympic, World and European Championship medals) participated in semi-structured interviews. Inductive thematic analysis revealed that all coaches mainly adjusted their key training and coaching principles to the individual athlete, rather than gender. A coach-driven and athlete-centered individualization process was essential to create trust, mutual understanding, and optimal training content. Potential gender/sex differences were perceived in four main themes: sport-specific competition demands, physiological, psychological and interpersonal factors (e.g., gender of the coach). In this context, all coaches described how training and coaching of female athletes differs from that of men, thus considering male athletes as the reference group and male physiology and psychology as the norm. Furthermore, societal factors such as a male-dominant sports culture and underlying gender stereotypes were suggested as amplifiers of gender differences. Accordingly, our report highlights the need for female perspectives in elite sports and invites further in-depth investigations of the identified gender/sex differences within the respective disciplines of training science, physiology, psychology and sociology. Key Words: Coaching, Endurance Training, Gender Differences, Sex Difference, Training Science
... In the world of sports, there is a clear distinction between genders based on hormone levels, and this distinction is linked to performance (IAAF, 2018). Female cyclists compare at different distances and speeds than male cyclists (Sanders et al., 2018). Consequently, our study asked participants directly about their biological sex, based on their hormone levels 1 . ...
Thesis
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Virtual reality allows users to experience a sense of ownership of a virtual body-a phenomenon commonly known as the body ownership illusion. Researchers and designers aim at inducing a body ownership illusion and creating embodied experiences using avatars-virtual characters that represent the user in the digital world. In accordance with the real world where humans own a body and interact via the body with the environment, avatars thereby enable users to interact with virtual worlds in a natural and intuitive fashion. Interestingly, previous work revealed that the appearance of an avatar can change the behavior, attitude, and perception of the embodying user. For example, research found that users who embodied attractive or tall avatars behaved more confidently in a virtual environment than those who embodied less attractive or smaller avatars. Alluding to the versatility of the Greek God Proteus who was said to be able to change his shape at will, this phenomenon was termed the Proteus effect. For designers and researchers of virtual reality applications, the Proteus effect is therefore an interesting and promising phenomenon to positively affect users during interaction in virtual environments. They can benefit from the limitless design space provided by virtual reality and create avatars with certain features that improve the users' interaction and performance in virtual environments. To utilize this phenomenon, it is crucial to understand how to design such avatars and their characteristics to create more effective virtual reality applications and enhanced experiences. Hence, this work explores the Proteus effect and the underlying mechanisms with the aim to learn about avatar embodiment and the design of effective avatars. This dissertation presents the results of five user studies focusing on the body ownership of avatars, and how certain characteristics can be harnessed to make users perform better in virtual environments than they would in casual embodiments. Hence, we explore methods for inducing a sensation of body ownership of avatars and learn about perceptual and physiological consequences for the real body. Furthermore, we investigate whether and how an avatar's realism and altered body structures affect the experience. This knowledge is then used to induce body ownership of avatars with features connected with high performance in physical and cognitive tasks. Hence, we aim at enhancing the users' performance in physically and cognitively demanding tasks in virtual reality. We found that muscular and athletic avatars can increase physical performance during exertion in virtual reality. We also found that an Einstein avatar can increase the cognitive performance of another user sharing the same virtual environment. This thesis concludes with design guidelines and implications for the utilization of the Proteus effect in the context of human-computer interaction and virtual reality.
... Model predictions highly agree with measured MMP 1200 but overestimate MMP 1800 , a reasonable finding given the environmental and tactical characteristics of the race that limit's the possibility to perform long-lasting maximal cycling bouts without planned, forced, or unexpected slowdowns. The present findings are restricted to male athletes; however, there is high likelihood that the model can be applied also to women's professional multistage races, where relative exercise intensities were found to be greater than for men (29). ...
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This study evaluated the changes in ratios of different intensity (rating of perceived exertion; RPE, heart rate; HR, power output; PO) and load measures (session-RPE; sRPE, individualized TRIMP; iTRIMP, Training Stress Score™; TSS) in professional cyclists. RPE, PO and HR data was collected from twelve professional cyclists (VO2max 75 ± 6 ml∙min∙kg⁻¹) during a two-week baseline training period and during two cycling Grand Tours. Subjective:objective intensity (RPE:HR, RPE:PO) and load (sRPE:iTRIMP, sRPE:TSS) ratios and external:internal intensity (PO:HR) and load (TSS:iTRIMP) ratios were calculated for every session. Moderate to large increases in the RPE:HR, RPE:PO and sRPE:TSS ratios (d = 0.79–1.79) and small increases in the PO:HR and sRPE:iTRIMP ratio (d = 0.21–0.41) were observed during Grand Tours compared to baseline training data. Differences in the TSS:iTRIMP ratio were trivial to small (d = 0.03–0.27). Small to moderate week-to-week changes (d = 0.21–0.63) in the PO:HR, RPE:PO, RPE:HR, TSS:iTRIMP, sRPE:iTRIMP and sRPE:TSS were observed during the Grand Tour. Concluding, this study shows the value of using ratios of intensity and load measures in monitoring cyclists. Increases in ratios could reflect progressive fatigue that is not readily detected by changes in solitary intensity/load measures.
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Scantlebury, S, Till, K, Sawczuk, T, Phibbs, P, and Jones, B. Validity of retrospective session rating of perceived exertion to quantify training load in youth athletes. J Strength Cond Res 32(7): 1975-1980, 2018-Youth athletes frequently participate in multiple sports or for multiple teams within the same sport. To optimize player development and minimize undesirable training outcomes (e.g., overuse injuries), practitioners must be cognizant of an athlete's training load within and outside their practice. This study aimed to establish the validity of a 24-hour (s-RPE24) and 72-hour (s-RPE72) recall of session rating of perceived exertion (s-RPE) against the criterion measure of s-RPE collected 30 minutes' post training (s-RPE30). Thirty-eight adolescent athletes provided a s-RPE30 following the first field based training session of the week. Approximately 24 hours later subjects were asked to recall the intensity and duration of the previous days training. The following week subjects once again provided an s-RPE30 measure after training before recalling the intensity and duration of the session approximately 72 hours later. A nearly perfect correlation (0.98 [0.97-0.99]) was found between s-RPE30 and s-RPE24, with a small typical error of estimate (TEE; 8.3% [6.9-10.5]) and trivial mean bias (-1.1% [-2.8 to 0.6]). Despite a large correlation between s-RPE30 and s-RPE72 (0.73 [0.59-0.82]) and a trivial mean bias (-0.2% [-6.8 to 6.8]), there was a large TEE (35.3% [29.6-43.9]). s-RPE24 provides a valid measure of retrospectively quantifying s-RPE; however, the large error associated with s-RPE72 suggests that it is not a suitable method for monitoring training load in youth athletes.
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Purpose: Describing the demand of recent World Cup (WC) races comparing Top 10 (T10) and non-Top 10 (N-T10) performances using power data. Methods: Race data were collected in 1-day World Cup races during the 2012-2015 road cycling seasons. Seven female cyclists completed 49 WC races, finishing 25 times in T10 and 24 times N-T10. Peak power (1 s) and Maximal Mean Power (MMP) for durations of 5, 10, 20 and 30 s and 1, 2, 5, 10, 20, 30 and 60 min expressed as power to weight ratio were analysed in T10 and N-T10. The percentage of total race time spent at different power bands was compared between T10 and N-T10 using 0.75 W˖kg(-1) power bands, ranging from <0.75 to >7.50 W˖kg(-1). The number of efforts in which the power output remained above 7.50 W˖kg(-1) for at least 10 seconds were recorded. Results: MMP were significantly higher in T10 than in N-Top 10, with a large effect size for durations between 10 seconds and 5 minutes. N-T10 spent more time in the 3.01-3.75 W·kg(-1) power band when compared to T10 (P=0.011); conversely, T10 spent more time in the 6.75-7.50 and >7.50 W·kg(-1) power bands (P=0.009 and 0.005, respectively) than N-T10. A significantly higher number of short and high intensity efforts (≥10s, >7.5 W·kg(-1)) was ridden by T10, compared to N-T10 (P=0.002). Specifically, 46±20 and 30±15 efforts for T10 and N-T10, respectively. Conclusions: The ability to ride at high intensity was determinant for successful road cycling performances in WC races.
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Purpose: This study aims to evaluate training intensity distribution using different intensity measures based on session rating of perceived exertion (sRPE), heart rate (HR) and power output (PO) in well-trained cyclists. Methods: Fifteen road cyclists participated in the study. Training data was collected during a 10-week training period. Training intensity distribution was quantified using HR, PO and sRPE categorized in a 3-zone training intensity model. Three zones for HR and PO were based around a first and second lactate threshold. The three sRPE zones were defined using a 10-point scale: zone 1, sRPE scores 1-4; zone 2, sRPE scores 5-6; zone 3, sRPE scores 7-10. Results: Training intensity distribution as percentages of time spent in zone 1, zone 2 and zone 3 was moderate to very largely different for sRPE (44.9%, 29.9%, 25.2%) compared to HR (86.8%, 8.8%, 4.4%) and PO (79.5%, 9.0%, 11.5%). Time in zone 1 quantified using sRPE was large to very largely lower for sRPE compared to PO (P < 0.001) and HR (P < 0.001). Time in zone 2 and zone 3 was moderate to very largely higher when quantified using sRPE compared to intensity quantified using HR (P < 0.001) and PO (P < 0.001). Conclusions: Training intensity distribution quantified using sRPE demonstrates moderate to very large differences compared to intensity distributions quantified based on HR and PO. The choice of intensity measure impacts on the intensity distribution and has implications for training load quantification, training prescription and the evaluation of training characteristics.
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Purpose: The aim of this study was to assess the dose-response relationships between different training load methods and aerobic fitness and performance in competitive road cyclists. Method: Training data from 15 well-trained competitive cyclists were collected during a 10-week (December - March) pre-season training period. Before and after the training period, participants underwent a laboratory incremental exercise test with gas exchange and lactate measures and a performance assessment using an 8-min time trial (8MT). Internal training load was calculated using Banister's TRIMP (bTRIMP), Edwards' TRIMP (eTRIMP), individualized TRIMP (iTRIMP), Lucia's TRIMP (luTRIMP) and session-RPE (sRPE). External load was measured using Training Stress Score™ (TSS). Results: Large to very large relationships (r = 0.54-0.81) between training load and changes in submaximal fitness variables (power at 2 and 4 mmol·L(-1)) were observed for all training load calculation methods. The strongest relationships with changes in aerobic fitness variables were observed for iTRIMP (r = 0.81 [95% CI: 0.51 to 0.93, r = 0.77 [95% CI 0.43 to 0.92]) and TSS (r = 0.75 [95% CI 0.31 to 0.93], r = 0.79 [95% CI: 0.40 to 0.94]). The highest dose-response relationships with changes in the 8MT performance test were observed for iTRIMP (r = 0.63 [95% CI 0.17 to 0.86]) and luTRIMP (r = 0.70 [95% CI: 0.29 to 0.89). Conclusions: The results show that training load quantification methods that integrate individual physiological characteristics have the strongest dose-response relationships, suggesting this to be an essential factor in the quantification of training load in cycling.
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This study examined the acceptability of a retrospective rating of perceived exertion in soccer. Two attributes were investigated: response shift and recall bias. Response shift refers to a change in perception due to changes in internal standards and recall bias can influence the response shift assessment. Ratings were collected with the Borg-CR100® scale. Study 1: during competitive season 58 players (age 22 ± 5 years, height 178 ± 6 cm, body mass 72 ± 6 kg) were asked their rating following cessation of the matches and again at48 h post match. Response shift (first part of the season) was investigated by difference between the two ratings and recall bias (second part of the season) asking players whether they remembered exactly the rating given 48 h before. No response shift or recall bias were found. Study 2: 21 players (age 25 ± 5 years, height 176 ± 6 cm, body mass 71 ± 7 kg) were asked ratings at the end and 48 h following a field session, equated for internal and external loads. The same session was repeated after 10 days in a randomized crossover design. No significant differences (P > 0.05) between conditions were found. Retrospective rating was appropriate, however, the inconsistency of some ratings (i.e., after training) suggested it should be used only under special circumstances.
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Purpose: To describe the within-season external workloads of professional male road cyclists for optimal training prescription. Methods: Training and racing of four international competitive professional male cyclists (age 24 ± 2 y, body mass 77.6 ± 1.5 kg) were monitored for 12 months prior to the world team time trial championships. Three within-season phases leading up to the team time trial world championships on 20(th) Sept 2015 were defined as phase one (Oct - Jan), phase two (Feb - May) and phase three (June - Sept). Distance and time were compared between training and racing days and over each of the various phases. Time spent within absolute (<100 W, 100 to 300 W, 400 to 500 W, >500W) and relative (0 to 1.9 W·kg(-1), 2.0 to 4.9 W·kg(-1), 5.0 to 7.9 W·kg(-1), >8 W·kg(-1)) power zones were also compared for the whole season and between phases one to three. Results: Total distance (3859 ± 959 vs 10911 ± 620 km) and time (240.5 ± 37.5 vs 337.5 ± 26 h) was lower (P <0.01) in phase one than phase two, respectively. Total distance decreased (P <0.01) from phase two to phase three (10911 ± 620 vs 8411 ± 1399 km, respectively). Mean absolute (236 ± 12.1 vs 197 ± 3 W) and relative (3.1 ± 0 vs 2.5 ± 0 W·kg(-1)) power output was higher (P <0.05) during racing compared with training, respectively. Conclusions: Volume and intensity differed between training and racing over each of three distinct within-seasonal phases.
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Finding the optimal balance between high training loads and recovery is a constant challenge for cyclists and their coaches. Monitoring improvements in performance and levels of fatigue is recommended to correctly adjust training to ensure optimal adaptation. However, many performance tests require a maximal or exhaustive effort, which reduces their real-world application. The purpose of this review was to investigate the development and use of submaximal cycling tests that can be used to predict and monitor cycling performance and training status. Twelve studies met the inclusion criteria, and 3 separate submaximal cycling tests were identified from within those 12. Submaximal variables including gross mechanical efficiency, oxygen uptake ( . VO2), heart rate, lactate, predicted time to exhaustion (pTE), rating of perceived exertion (RPE), power output, and heart-rate recovery (HRR) were the components of the 3 tests. pTE, submaximal power output, RPE, and HRR appear to have the most value for monitoring improvements in performance and indicate a state of fatigue. This literature review shows that several submaximal cycle tests have been developed over the last decade with the aim to predict, monitor, and optimize cycling performance. To be able to conduct a submaximal test on a regular basis, the test needs to be short in duration and as noninvasive as possible. In addition, a test should capture multiple variables and use multivariate analyses to interpret the submaximal outcomes correctly and alter training prescription if needed.