Evaluation eines radsportspezischen Tests
zur Ermittlung der funktionellen Leistungs-
Evaluation of a Cycling Exercise Test. Is Functional Threshold
Power an Accurate Measure of Endurance Capacity?
Wissenschaftliche Arbeit zur Erlangung des Grades
an der Fakultät für Sport- und Gesundheitswissenschaften
der Technischen Universität München
Dr. rer nat. Jan Müller
Lehrstuhl für Präventive Pädiatrie
Am Sonnenhof 32
+49 177 273 5587
München, den 04.09.2017
Table of contents
Abstract .............................................................................................................. I!
List of figures ..................................................................................................... II!
List of tables ..................................................................................................... III!
List of abbreviations ......................................................................................... IV!
1.!Introduction ................................................................................................. 1!
2.!Scientific background .................................................................................. 2!
2.1!Maximal oxygen uptake ......................................................................... 2!
2.2!Ventilatory threshold .............................................................................. 3!
2.3!Functional threshold power ................................................................... 4!
3.!Research question, hypotheses and relevance .......................................... 6!
4.!Methods ...................................................................................................... 7!
4.1!Experimental approach to the problem ................................................. 7!
4.2!Subjects ................................................................................................. 7!
4.3!Procedures ............................................................................................ 8!
4.3.1!Continuous ramp protocol ............................................................... 8!
4.3.2!FTP test .......................................................................................... 9!
4.4!Statistical analysis ............................................................................... 10!
5.!Results ...................................................................................................... 11!
5.1!Associations between FTP and ventilatory endurance parameters .... 11!
5.2!Differences between cyclists and non-cyclists .................................... 13!
5.3!Training recommendations based on FTP .......................................... 16!
6.!Discussion ................................................................................................. 17!
6.1!Discussion of results ........................................................................... 17!
6.2!Discussion of methodology ................................................................. 19!
7.!Conclusion and prospect .......................................................................... 20!
8.!References ................................................................................................ 21!
Introduction: In endurance training variation of intensity is crucial, because
intensity is ultimately linked to specific cellular adaptations. In cycling and
other endurance sports, the assessment of physiological parameters such as
maximal oxygen uptake (VO2max), lactate and ventilatory thresholds is
considered the highest standard. However, in the age of power measurement,
functional threshold power (FTP) has become a popular measure to quantify
maximal intensity that can be maintained for one hour without fatiguing.
Previous research could show that FTP assessed with a field-based exercise
test is significantly associated with physiological endurance determinants
assessed with laboratory testing. On this account, this study aims to evaluate
the reliability of the FTP test, proposed by Allen and Coggan (2012), including
a standardized warm-up phase and a 20-minute time trial.
Methods: A sample of 14 active male individuals (age 25.4 ± 8.2years, height
183.1 ± 5.5cm, weight 77.0 ± 6.1kg, VO2max 55.9 ± 6.4 ml·min-1·kg-1) underwent
two types of exercise tests on an electronically braked bicycle ergometer to
determine VO2max, the first ventilatory threshold (VT1) and the second
ventilatory threshold (VT2) on the one hand, and FTP on the other hand.
VO2max and ventilatory thresholds were assessed with a ramped exercise test
(30W·min-1) until exhaustion. FTP was assessed in the laboratory with a
20MTT preceded with a standardized warm-up phase and estimated as 95%
of the mean power output during the 20MTT.
Results: Strong correlations were observed between FTP and absolute
VO2max (r = 0.890; p < 0.001) and power output at VT2 (r = 0.820; p < 0.001).
Correlation between FTP and power output at VT1 was moderate (r = 0.547;
p = 0.043). Regression analyses between ventilatory variables and FTP were
significant for VO2max (R2 = 0.776, p < 0,001), VT1 (R2 = 0.241, p = 0,043) and
VT2 (R2 = 0.645, p < 0,001). Differences between two sub-samples (cyclists
and non-cyclists) were investigated via t-tests for independent groups. Cyclists
showed significantly higher values in VO2max (p = 0.016), power output at VT1
(p = 0.017), FTP (p = 0.011) and average power output throughout all stages of
the FTP test. Mean difference between FTP and power output at VT2 was
lower for cyclists than for non-cyclists (exact Wilcoxon rank-sum test:
U = 11.000; p = 0.147).
Conclusion: Due to significant associations of endurance related ventilatory
parameters with the performance during a 20-minute time trial, FTP testing
appropriately reflects the actual state of an athlete’s fitness. FTP is suitable to
estimate VO2max and VT2.
List of figures
Fig. 1: Schematic diagram of the presetting of intensity relative to the
individual’s power output at VT1 and VT2 (y-axis) for each stage of the FTP
test protocol. VT1 = First ventilatory threshold; VT2 = Second ventilatory
threshold; rpm = revolutions per minute; 20MTT = 20-minute time trial; t = time
Fig. 2: Illustration of the correlation between absolute VO2max values and
FTP. The dashed line represents linear regression (y=0.67+0.01·x; adjusted
R2=0.776). Solid dots represent “non-cyclists” and circles represent “cyclists”.
FTP = Functional threshold power; VO2max = maximal oxygen uptake. ........ 12!
Fig. 3: Illustration of the correlation between power output at VT1 and FTP.
The dashed line represents linear regression (y=74.13+0.48·x; adjusted
R2=0.241). Solid dots represent “non-cyclists” and circles represent “cyclists”.
FTP = Functional threshold power; VT1 = First ventilatory threshold. ............. 12!
Fig. 4: Illustration of the correlation between power output at VT2 and FTP.
The dashed line represents linear regression (y=132.2+0.78x; adjusted
R2=0.645). Solid dots represent “non-cyclists” and circles represent “cyclists”.
FTP = Functional threshold power; VT2 = Second ventilatory threshold. ....... 13!
Fig. 5: Oxygen intake relative to VO2max and power output during the FTP
test for “cyclists” and “non-cyclists”. VO2max = maximal oxygen uptake; t =
time .................................................................................................................. 15!
Fig. 6: Training intensity zones derived from a classical 3-zone model based
on ventilatory thresholds in comparison with training intensity zones based on
FTP according to the model by Allen and Coggan (2012, p. 67). 3ZM = 3-zone
model; FTP = Functional threshold power; LT = Lactate threshold; ................ 16!
VO2max = maximal oxygen uptake; VT1 = First ventilatory threshold; VT2 =
Second ventilatory threshold ........................................................................... 16!
List of tables
Table 1: Anthropometric and physiological data of the whole sample and of
the sub-samples “cyclists” and “non-cyclists”. Values are presented as mean ±
standard deviation. ............................................................................................ 7!
Table 2: Correlations and partial correlations between FTP and selected
ventilatory endurance predictors. The partial correlation coefficient controls for
the confounding variables age, height and body weight. ................................. 11!
Table 3: Power output [W] during each stage of the functional threshold power
test (mean ± standard deviation) ..................................................................... 15!
Table 4: Oxygen uptake relative to maximal oxygen uptake [%VO2max] during
each stage of the functional threshold power test test (mean ± standard
deviation) ......................................................................................................... 16!
List of abbreviations
20MTT 20-minute time trial
4MTT 4-minute time trial
8MTT 8-minute time trial
AT Aerobic threshold
CO2 Carbon dioxide
FTP Functional threshold power
LT Lactate threshold
LT∆1 Lactate threshold defined as an increase of 1mmol·l-1 or
greater compared to the previous stage
LT4.0 Lactate threshold at 4.0mmol·l-1
LTP2 Second lactate turn point
LTvisual Visually determined lactate threshold
PETCO2 End-tidal carbon dioxide tension
Plact Power at lactate threshold
Pmax Maximal power output
RCP Respiratory compensation point
SD Standard deviation
SRM Schoberer Rad Messtechnik
VCO2 Rate of carbon dioxide expiration
VE Respiratory equivalent
VO2 Rate of oxygen intake
VO2max Maximum rate of oxygen intake
VT1 First ventilatory threshold
VT2 Second ventilatory threshold
In endurance sports such as cycling, training recommendations and intensities
are commonly based on the current state of fitness. The assessment of the
current state is realized by exercise testing, either in a laboratory or field
setting. Depending on the equipment available and the facilities accessible,
there exist a vast variety of exercise tests with one common goal: The
prediction of the actual performance capability. It seems apparent and
plausible that exercise tests be an essential part of the training monitoring
process: On one hand the efficacy of training stimuli can be assessed, while
on the other hand new intensity zones for subsequent training sessions can be
derived (Seiler & Tønnessen, 2009).
Laboratory incremental exercise tests along with gas exchange and/or blood
lactate measurements are unarguably the most reputable tests at the time. As
lactate is a byproduct when carbohydrates are metabolized anaerobically,
blood lactate levels give information about energy supply during exercise.
Blood lactate dynamics also manifest themselves in ventilation patterns and
respiratory air composition and can therefore be measured indirectly via
spirometry (Westhoff et al., 2013). However, recent developments in the realm
of power measurement have shifted the spotlight from laboratory exercise
tests towards field-based exercise tests for cyclists. In the late 1980’s, SRM
(Schoberer Rad Messtechnik GmbH, Jülich, Germany) ushered in a new era
of performance training by enabling the direct measurement of the actual
power produced by the athlete while cycling. And there are several reasons
distinguishing power as a superior exercise parameter to velocity and heart
rate. Firstly, especially in cycling, velocity may be affected by environmental
conditions such as wind and gradient, regardless of exercise intensity (Balmer,
Davison, & Bird, 2000). Secondly, while heart rate does reflect intensity,
cardiovascular drift causes a considerable degree of imprecision (Heaps,
Gonzáles-Alonso, & Coyle, 1994; Vogt et al., 2006). Finally, power has
become an increasingly popular performance parameter due to greater
affordability and abundance of power meters in the market.
A growing number of professional and amateur athletes in cycling and triathlon
use power as a measure to control exercise intensity in training and during
competition. Therefore, a valid and reliable field-based exercise test that is
based on power and that is easy to implement into the athlete’s training
regimen would be of high interest. This may be especially true for non-
professional athletes who do not have access to high quality diagnostic
facilities on a regular basis. The functional threshold power test (FTP test) is
one example, that has been the subject of scientific investigation over the last
decade (Gavin et al., 2012; Klika, Alderdice, Kvale, & Kearney, 2007; Sanders,
Taylor, & Myers, 2017) and is based on power measurement. On that account,
it shall be the goal of this study to evaluate whether the FTP test is suitable for
the assessment of endurance performance capability.
2. Scientific background
2.1 Maximal oxygen uptake
In a clinical as well as performance physiology related context, maximal
oxygen uptake (VO2max) is an important and commonly used parameter in
order to evaluate aerobic capacity. It depicts the maximal amount of oxygen
that can be absorbed, transported and utilized during strenuous exercise and
thus assesses the integral activity of the pulmonary and cardiovascular
systems (Meyer & Kindermann, 1999).
This traditional view of VO2max is largely based on the work by Hill and Lupton
(1923). They examined the relationships between oxygen intake (VO2) and
exercise intensity. Observations concluded a strong and linear relationship
between VO2 and running speed until VO2 reaches its limit. This point, beyond
which no further increase in intensity can elicit higher VO2 values, is called
VO2max and is defined by the formation of a VO2 plateau. Furthermore, they
stated that VO2max differs between individuals and is limited by the
cardiovascular and respiratory systems. Thus, at very high intensities,
pulmonary diffusion capacity, cardiac output, peripheral circulation and
diffusion of oxygen into the muscle cells reach their limit and, hence, so does
Contrary to the work of Hill and Lupton, Dr. Timothy Noakes proposes an
alternative and controversially discussed theory regarding the limitation of
VO2max. Both perspectives are summarized and compared by Basset and
Howley (1997). Noakes suggests a central nervous system governor limits
VO2max to prevent organ damage or death during severe exercise. He
substantiates his hypothesis by arguing that Hill and Lupton did not provide
enough evidence that a true VO2 plateau could be attained, and that
improvement in performance and alterations in metabolism could occur before
muscular adaptations were measurable (Noakes, 1997).
The current consensus is that VO2max is limited by a variety of factors
associated with the cascade of oxygen transport to mitochondria (Howley,
Basset, & Welch, 1995; Levine, 2008). Additionally, Van der Zwaard et al.
(2016) could show that VO2max is proportional to mitochondrial oxidative
capacity in chronic heart failure patients, healthy controls and highly trained
When it comes to exercise testing in order to determine VO2max, various test
protocols have been employed in the past. As highly trained elite-level cyclists
need a much higher intensity to reach their individual maximum than
recreational cyclists, the question arises, which intensity to start with and at
what rate to increase it? Buchfuhrer et al. (1983) set out to determine the
optimal exercise protocol for the assessment of cardiopulmonary variables by
comparing test protocols of varying duration. A small sample of five
participants completed several exercise tests to exhaustion on a cycle
ergometer and work rate was increased at a rate of 15W, 30W or 60W per
minute. According to their results, subjects achieved maximal VO2 when work
rate was increased at 30W/min, which led to a test duration of approximately
ten minutes. The authors concluded that increments of intermediate size
(30W/min) and duration of 10±2 minutes are best to elicit VO2max. A dogmatic
generalization of the findings by Buchfuhrer et al. (1983) was criticized by
Midgley, Bentley, Luttikholt, McNaughton, and Millet (2008). They retorted that
there was enough evidence proving shorter and longer test protocols to elicit
just as high values of VO2 (Bentley & McNaughton, 2003; Bishop, Jenkins, &
Mackinnon, 1998; Weston, Gray, Schneider, & Gass, 2002).
In spite of all controversy, VO2max and VO2max relative to body weight remain
valuable indicators for aerobic performance: Elite endurance athletes produce
much higher values than patients or individuals with a sedentary lifestyle, due
to a higher cardiac output and a higher capillary and mitochondrial density.
Nonetheless there are large inter-individual differences in regard to
performance among athletes with similar relative VO2max values (Levine,
2.2 Ventilatory threshold
Like VO2max, ventilatory thresholds can be assessed via spirometry and
represent important landmarks of the cascade of oxygen uptake,
transportation and utilization during exercise. However, contrary to VO2max,
ventilatory thresholds are more closely related to the change of metabolites
used within the energy providing systems of the body. Consequently,
ventilatory thresholds represent the cardiorespiratory response to metabolic
processes during physical exertion (Westhoff et al., 2013). Generally, two
ventilatory thresholds are to be distinguished: First ventilatory threshold (VT1)
and second ventilatory threshold (VT2). Although they are closely related to
lactate thresholds, mostly referred to as anaerobic threshold (AT) and lactate
threshold (LT), both denominations should not be used interchangeably.
In the attempt to determine AT in a bloodless way via respiratory gas
exchange analysis, Wasserman, Whipp, Koyal, and Beaver (1973) studied the
underlying mechanisms. At lower intensities the majority of energy is
generated aerobically. As intensity increases, more and more energy is
supplied by the anaerobic glycolysis, which leads to the formation of lactic
acid. Blood lactate is then buffered by the bicarbonate system in order to
prevent acidosis and maintain a physiological pH-value. This is highly
effective, for the carbon dioxide (CO2) that remains after the buffering process
can be readily exhaled through the lungs. The additional CO2 that is exhaled
results in an increased rate of respiration and a disproportionate increase CO2
output (VCO2), easily detectable by breath-by-breath gas exchange analysis. If
these criteria are met, VT1 is achieved.
As intensity increases further, the elimination of lactic acid by the bicarbonate
system will reach its limit. Lactate accumulation then leads to metabolic
acidosis, which stimulates respiration to increase disproportionately compared
to VCO2 (Kindermann, 2004). This point is defined as VT2 and marks the
upper end of the aerobic-anaerobic transition. Both values, VT1 and VT2, can
be determined by means of respiratory gas exchange analysis during exercise
testing. The non-invasive nature of this procedure has led to great popularity.
Therefore, the determination of ventilatory thresholds is often preferred and
recommended over the determination of lactate thresholds (Amann, Subudhi,
& Foster, 2006; Tschopp, Held, Villiger, & Marti, 2001; Westhoff et al., 2013).
While lactate concentration values may take up to ten minutes to reach
equilibrium (Rusko et al., 1986), the ventilatory response to an increase in
workload stabilizes after only up to 40 seconds (Amann et al., 2006). For the
measurement of lactate variables an incremental increase in intensity has
proved its worth, whereas a continuous increase is advantageous for the
measurement of ventilatory variables (Meyer & Kindermann, 1999; Tschopp et
2.3 Functional threshold power
Functional threshold power (FTP) is a threshold value specific to cycling that
aims to predict the highest possible power a rider is able to maintain for one
hour without fatiguing (Allen & Coggan, 2012). The FTP test is solely based on
the power output produced by the cyclist during one single test period. It is
essentially a time trial over a preset period of time, which usually ranges
between eight to 20 minutes. The purpose of the FTP test is to provide a
reliable and valid exercise test that can be conducted in the field and makes
use of the same bicycle and power meter the cyclist utilizes for training and
racing purposes. Advantages of this kind of exercise test include cost-
effectiveness, independence of laboratory access and applicability for training
Klika et al. (2007) conducted a study in order to evaluate the efficacy of an
eight-week training intervention based on the results of an eight-minute time
trial (8MTT) very similar to the concept of the FTP test proposed by Allen and
Coggan. Training instructions were given according to Carmichael Training
Systems (Carmichael, 2004, p. 89). They also compared the changes in
average power during the 8MTT to changes in physiological parameters
related to endurance performance. These included VO2max, power output at
lactate threshold (PTlact; defined as an increase of 1mmol·l-1 above baseline)
and maximal power (Pmax). Klika and colleagues documented strong
correlations between all variables (0.71 < r < 0.98) before and after the training
intervention. Power output during the 8MTT was approximately 7.5% higher
This discrepancy was confirmed by Gavin et al. (2012). In addition, Gavin et al.
compared four common methods to identify power output at lactate threshold:
PTlact as described by Klika et al., LT∆1 (defined as a 1mmol·l-1 or greater raise
in lactate values from one stage to the next), a visual determination of lactate
threshold by two independent investigators (LTvisual), and LT4.0 (defined as the
point at which blood lactate concentration reaches 4.0mmol·l-1). Unlike Klika et
al., Gavin and colleagues derived FTP by deducting 10% from the average
power output during the 8MTT. They could show that FTP (301 ± 13W) (mean
± standard deviation (SD)) was equivalent to power output at lactate threshold
(303 ± 23W), if lactate threshold was determined according to the LT4.0 method.
The strong relationship between FTP and endurance performance
determinants could again be confirmed by Sanders et al. (2017). However,
they could not reassure the equivalency of FTP (341 ± 33W) and power output
at LT4.0 (319 ± 25W). Sanders et al. analyzed the test results of 19 competitive
male cyclists. Subjects used their own bicycles and power meters, which may
have lead to a certain degree of inaccuracy. The 8MTT was performed in the
field after a controlled warm-up, whose intensity was determined by power
output at LT4.0 assessed during laboratory testing. FTP was then estimated as
90% of the mean power output during the 8MTT.
For a homogenous group of 15 professional road and mountain bike cyclists
Nimmerichter, Williams, Bachl, and Eston (2010) could show high agreement
between a four-minute (4MTT) time trial and a 20MTT with maximal and
submaximal physiological endurance markers. These included lactate and
ventilatory threshold values. Participants completed both time trials during one
session with 30 minutes of active recovery in between. Mean power output
during the 4MTT and mean power output during the 20MTT showed high
correlation (r = 0.93; p < 0.001). Power output at lactate threshold (344 ± 38W)
and ventilatory threshold (344 ± 37W), denominated as second lactate turn
point (LTP2) and respiratory compensation point (RCP) respectively, were
equivalent to the average power output during the 20MTT (347 ± 42W).
Previous research suggests that FTP be an accurate measure in order to
assess endurance capacity and predict performance capability in an
economical and easily employable manner. Strong correlations between FTP
and endurance determinants, such as VO2max, lactate and ventilatory
threshold, affirm that FTP reflects endurance in recreational and competitive
cyclists. Furthermore, the implementation of training recommendations based
on FTP can yield significant improvements in FTP as well as physiological
endurance parameters (Klika et al., 2007). Yet, previous research has focused
mainly on the relationship between FTP, assessed with an 8MTT, and fixed
blood lactate concentration values. Only few have evaluated the association of
ventilatory markers with FTP.
The FTP test based on a 20MTT, as proposed by Allen and Coggan (2012),
has not yet been investigated as to which degree it correlates with
physiological endurance determinants. Although, as mentioned above, it has
been suggested that ventilatory threshold variables are superior to lactate
threshold variables in predicting time trial performance in cycling (Amann et
3. Research question, hypotheses and relevance
The assessment of the current state of endurance capacity and the prediction
of performance are of great value to athletes and coaches alike. Variation in
training intensity is crucial for long-term adaptation to training stimuli and is
usually based on maximal or sub-maximal physiological endurance
determinants (Seiler & Tønnessen, 2009; Wolpern, Burgos, Janot, & Dalleck,
2015). For cyclists of all performance levels, a valid, reliable and easily
implementable field-based test to evaluate endurance capacity and determine
exercise intensity zones would be highly beneficial. Allen and Coggan (2012)
proposed a field-based exercise test to determine functional threshold power,
based on the average power output during a 20MTT, preceded with a
standardized warm-up protocol. Based on past research the following
hypotheses have been formulated in order to determine whether the FTP test
is suitable for the assessment of endurance capacity:
Hypothesis 1: Ventilatory performance determinants (VO2max, VT1 and VT2)
are associated with the magnitude of functional threshold power assessed with
Hypothesis 2: Experienced cyclists are able to maintain a greater intensity in
relation to their maximal oxygen uptake, during the 20MTT.
Hypothesis 3: Functional threshold power is equivalent to power at ventilatory
4.1 Experimental approach to the problem
This study evaluates the relationship of functional threshold power assessed
with 20MTT and physiological endurance parameters assessed with a graded
laboratory exercise test to exhaustion. In a first step, the performance during
the 20MTT is compared to physiological performance predictors such as
ventilatory thresholds VT1 and VT2, as defined by Westhoff et al. (2013), and
VO2max. Then differences between two sub-samples (cyclists and non-
cyclists) are investigated to determine the influence of experience and cycling
specific training. Finally, training recommendations derived from both, the
incremental laboratory test and the FTP test, are evaluated as to which degree
Table 1: Anthropometric and physiological data of the whole sample and of the sub-samples “cyclists”
and “non-cyclists”. Values are presented as mean ± standard deviation.
Fourteen male participants (age 25.43 ± 8.2years, height 183.09 ± 5.51cm,
weight 77.03 ± 6.14kg, VO2max 55.87 ± 6.43 ml·min-1·kg-1) (mean ± SD)
volunteered to take part in this study. Subjects reported to be healthy and free
from orthopedic ailments. All participants were asked to complete a
questionnaire in order to assess sports that are practiced on a weekly basis
and their respective weekly training times as well as previous experience
regarding road cycling, cycling or triathlon competition, performance
diagnostics, FTP testing and power measurement. Nine out of 14 participants
were considered cyclists, since they reported cycling as their primary sport. As
prior experience and familiarization tend to be associated with cycling
performance (Hibbert, Billaut, Varley, & Polman, 2017), this classification
(cyclist vs. non-cyclist) will be used in order to highlight differences and
determine whether experience associates with the prediction of endurance
capability based on FTP test results. Anthropometric and physiological data of
the entire sample and of the two sub-samples are presented in table 1.
Participants reported to the laboratory twice on two separate and non-
consecutive days within one week. There were two exemptions to this rule due
to equipment malfunctioning, thus leading to a time span up to 14 days
between tests. Malfunctioning equipment was detected immediately and
testing was not continued until faultless measurements could be assured. Both
tests were completed on an electronically braked bicycle ergometer, Lode
Excalibur (Lode, Groningen, NED). Respiratory air composition was analyzed
and logged with a Cortex Metalyzer 3B (Cortex Biophysik GmbH, Leipzig,
GER) and heart rate was monitored with a Polar H7 heart rate sensor (Polar
Instruments Inc., Oulu, FIN). Participants wore conventional running shoes
that were fixated to the pedals by straps. Prior to both procedures each
participant was instructed to refrain from exercising vigorously and consuming
any food, forty-eight hours and two hours before the test, respectively.
Furthermore, they were advised to maintain their usual training schedule and
to show up well hydrated.
4.3.1 Continuous ramp protocol
On the first day of testing, participants completed a continuous ramp protocol
on the bicycle ergometer until exhaustion in order to determine ventilatory
thresholds (VT1 and VT2) and VO2max via spirometry. Before each test, flow
and volume were calibrated with the integrated system according to the
manufacturer’s guidelines. After a three-minute baseline measurement at rest,
subjects began pedaling for three minutes without any resistance, before
resistance was increased continuously by 30W/min. Subjects that had
reported no previous experience in cycling and that had not listed cycling as
one of their primary and regularly practiced sports, were instructed to keep up
a cadence between 80 and 90 rpm in order to minimize influence of pedal rate
on VO2 and energy cost alike (Belli & Hintzy, 2002). Experienced riders were
encouraged to ride at their preferred individual cadence on condition not to
change it more than ±10 rpm over the course of the test. The test was ended, if
the subject voluntarily terminated the test or cadence dropped below 60 rpm.
Subsequently, VT1 was defined as a disproportionately steep increase of
VCO2 versus VO2 (V-slope), while VT2 was defined as a disproportionately
steep increase of the ventilatory equivalent (VE) versus VCO2 and a
simultaneous decrease of end-tidal carbon dioxide tension (PETCO2)
(Westhoff et al., 2013). In order to assert that each subject reached their
individual VO2max, at least one of two decisive criteria had to be fulfilled: The
formation of a VO2 plateau before test termination (Tschopp et al., 2001) and a
maximum respiratory exchange ratio larger than 1.10 (Keteyian et al., 2010;
Meyer & Kindermann, 1999).
4.3.2 FTP test
On the second day of testing, subjects completed a slightly modified version of
Allen and Coggan’s (2012, p. 66) FTP test protocol. For economical reasons
the warm-up phase was reduced from 20 minutes to ten minutes and the cool-
down phase was reduced from ten minutes to five minutes. Both modifications
were assumed not to affect the outcome of the 20MTT significantly. Power
outputs at ventilatory thresholds derived on the first day of testing, were used
to preset intensities for every stage of the FTP test (figure 1) relative to the
individual’s performance capability. This was a necessity due to the software
that was used to control the resistance of the stationary bike. In order to
assimilate field conditions as much as possible, subjects were instructed to fit
resistance to their respective need and feel during the entire test. Also, if
requested by the participant, an electric fan was used for cooling purposes
during the 20MTT. Before the test commenced, participants received a
detailed description of the test and strategic instructions for the 20MTT with
the intention to reduce influence of cycling experience.
Fig. 1: Schematic diagram of the presetting of intensity relative to the individual’s power output at VT1
and VT2 (y-axis) for each stage of the FTP test protocol. VT1 = First ventilatory threshold; VT2 = Second
ventilatory threshold; rpm = revolutions per minute; 20MTT = 20-minute time trial; t = time
The FTP test comprised a total duration of 60 minutes. It started with a ten-
minute ramped warm-up phase (50W to 80% of power output at VT1). The
warm-up phase was followed by three one-minute intervals with a preset
intensity equal to power output at VT1 with the instruction to raise and keep
cadence above 120rpm. Active rest between intervals was one minute with
intensity set equal to 80% power output at VT1. After five minutes of active
recovery at 80% VT1 (power output) resistance was increased to 95% power
output at VT2. As prescribed by Allen and Coggan (2012) participants were
instructed to go “all-out”. Before the 20MTT, participants completed another
ten minutes of active recovery at 80% VT1 (preset power output). The initial
intensity of the 20MTT was set equal to 90% power output at VT2. Subjects
were advised to start off at a fairly high but constant pace aiming to increase
resistance considerably in the final five minutes of the 20MTT. They also
received vigorous verbal encouragement. Current power, heart rate, VO2,
VCO2, respiratory quotient, and remaining stage time were displayed on a
monitor in real-time.
Respiratory air composition was analyzed throughout the entire test, allowing a
retrospective conclusion about pacing and effort relative to VO2max and
ventilatory thresholds. FTP was calculated as 95% of the average power
output during the 20MTT (FTP = 0.95 · 20MTT).
4.4 Statistical analysis
All statistical operations were performed using IBM SPSS Statistics Version 23
(IBM Corp., Armonk, NY) and Microsoft Excel for Mac Version 14.6.6
(Microsoft Corp., Redmond, WA). Initial evaluation of the present data was
conducted via correlation analysis. Partial correlation was performed in order
to control for potential confounding variables. All descriptive results are
presented as mean ± SD.
In order to reveal influence on functional threshold power, ventilatory
endurance parameters (independent variables) were each introduced into a
linear regression model. The prediction of VO2max based on FTP, age, height
and weight was modeled by means of a multiple regression analysis.
Differences in the average value of FTP, VO2max, VT1 and VT2 between the
sub-samples “cyclists” and “non-cyclists” were assessed using t-tests for
independent groups. Disparities between groups regarding the individual
difference between power output at VT2 and FTP were assessed using a
Wilcoxon rank-sum test. Power output and oxygen consumption in relation to
VO2max during each stage of the FTP test was analyzed in order to reveal
between-group differences in effort and pacing. This was realized by
comparing means with a t-test for independent groups. Statistical significance
was accepted at p < 0.05.
5.1 Associations between FTP and ventilatory endurance parameters
A total of 14 cases were analyzed in matters of identifying the relationships of
ventilatory endurance parameters with the measure of FTP. Correlations
between FTP and the ventilatory endurance parameters VO2max relative to
body weight (r = 0.653; p = 0.011), absolute VO2max (r = 0.890; p < 0.001),
power output at VT1 (r = 0.547; p = 0.043) and power output at VT2 (r = 0.820;
p < 0.001) revealed moderate to strong effects (Cohen, 1992).
Partial correlations were calculated in order to control for the potential
confounding variables age, height and body weight (table 2). After taking
account for these confounding factors, FTP remained strongly and positively
linked to VO2max, VT1 and VT2. Based on the correlation coefficients, positive
linear connections were assumed and followed up by linear regression
Table 2: Correlations and partial correlations between FTP and selected ventilatory endurance
predictors. The partial correlation coefficient controls for the confounding variables age, height and body
At this point, it shall be pointed out that there seems to be a stronger
connection between the absolute VO2max and FTP than between VO2max
relative to body weight and FTP. Therefore, further assessment of interrelation
was continued using the absolute value of VO2max.
Subsequently, each independent variable (VO2max, VT1 and VT2) was
introduced into a regression model in order to evaluate associations with FTP
(dependent variable). A linear relationship between VO2max and FTP was
assumed by visual inspection of the present data, as illustrated in figure 2, and
based on their correlation coefficient (table 2). F-test analysis showed overall
significance of the model (F(1, 12) = 45.907; p < 0.001). VO2max has a
significant effect on FTP (t = 6.776; p < 0.001) and goodness of fit (adjusted R2)
revealed that 77.6% of the FTP’s variance can be attributed to the association
with VO2max (f = 1.86).
The regression model of power output at VT1 on FTP (figure 3) showed overall
significance for the prediction of FTP based on the independent variable
(F(1, 12) = 5.131; p = 0.043). Significant association with the independent
variable (t = 2.265; p = 0.043) could also be shown. 24.1% of the FTP’s total
variance occurred due to differences in power output at VT1. This conforms to
a strong effect (f = 0.56) according to Cohen (1992).
As expected, power output at VT2 proved to be significantly associated with
FTP, as well (t = 4.959; p < 0.001). F-test analysis affirmed overall significance
of the regression model (F(1,12) = 24.595; p < 0.001). 64.5% of the FTP’s total
variance can be attributed to changes in power output at VT2. Hence, an
increase in power at VT2 of 10W, would lead to an increase of 8.59W in
functional threshold power.
Fig. 2: Illustration of the correlation between absolute VO2max values and FTP. The dashed line
represents linear regression (y=0.67+0.01·x; adjusted R2=0.776). Solid dots represent “non-cyclists” and
circles represent “cyclists”. FTP = Functional threshold power; VO2max = maximal oxygen uptake.
Fig. 3: Illustration of the correlation between power output at VT1 and FTP. The dashed line represents
linear regression (y=74.13+0.48·x; adjusted R2=0.241). Solid dots represent “non-cyclists” and circles
represent “cyclists”. FTP = Functional threshold power; VT1 = First ventilatory threshold.
Fig. 4: Illustration of the correlation between power output at VT2 and FTP. The dashed line represents
linear regression (y=132.2+0.78x; adjusted R2=0.645). Solid dots represent “non-cyclists” and circles
represent “cyclists”. FTP = Functional threshold power; VT2 = Second ventilatory threshold.
A multiple regression analysis, including the independent variables FTP, age,
weight and height showed that these variables influence VO2max,
F(4,9) = 9.989, p = 0.002, n = 15. However, the inclusion of additional
anthropometric variables could not increase the overall power of the
regression model in comparison to linear regression of only FTP on VO2max.
5.2 Differences between cyclists and non-cyclists
It was expected that experienced riders have an advantage over participants,
who are not used to the movement patterns and the body position during
cycling and who are not able to resort to past cycling experience. Therefore
potential disparities between the two sub-samples were investigated, by
comparing mean values via t-tests for independent samples.
Firstly, subjects classified as cyclists on average produced significantly higher
values throughout most variables measured relating to endurance
performance. Mean absolute VO2max values for cyclists (4.5 ± 0.42 l·min-1;
n = 9) and for non-cyclists (3.9 ± 0.50 l·min-1; n = 5) differed significantly,
t(12) = 2.791, p = 0.016. Mean values of power output at VT1 were significantly
higher for cyclists (198.3 ± 19.36W; n = 9) than for non-cyclists (163.4 ± 27.84W;
n = 5), t(12) = 2.778, p = 0.017. Power output at VT2 was higher in cyclists
(325.1 ± 27.91W; n = 9) than in non-cyclists (295.8 ± 27.17W; n = 5), yet the t-
test did not show a significant difference between the two groups, t(12) = 1.899,
p = 0.082. Then in turn, FTP also differed significantly between cyclists
(248.4 ± 24.87W; n = 9) and non-cyclists (206.6 ± 25.26W; n = 5), t(12) = 2.995,
p = 0.011.
Secondly, it was suspected that trained cyclists might be able to ride at a
higher relative intensity, based on experience regarding pace, own capabilities
and competition. Therefore, power output and VO2 relative to VO2max was
analyzed for each stage of the FTP test. Differences between sub-samples
were evaluated via t-test analyses (table 3 and 4).
Generally, cyclists were able to produce higher power across all stages of the
FTP test. However, non-cyclists were exercising at a higher oxygen intake
relative to VO2max than cyclists (figure 5). During the ten-minute ramped
warm-up phase (50W – 80% PO at VT1) cyclists (104.6 ± 10.20W; n = 9) and
non-cyclists (89.1 ± 9.26W; n = 5) differed significantly regarding the mean
power output achieved during this phase, t(12) = 2.819, p = 0.015. Oxygen
intake relative to VO2max was higher with no significant effect (t(12) = -1.884;
p = 0.086) in non-cyclists (41.6 ± 3.16%; n = 5) than in cyclists (36.1 ± 5.31%;
n = 9).
During the three one-minute intervals at a cadence above 120rpm and a
preset intensity equal to power output at VT1, cyclists (203.5 ± 22.97W; n = 9)
produced a significantly higher power output than non-cyclists
(162.9 ± 22.72W; n = 5), t(12) = 3.176, p = 0.008. At the same time, non-cyclists
(72.6 ± 7.83%; n = 5) were exercising at a higher relative intensity than cyclists
(64.7 ± 8.30%; n = 9). The difference of means between groups was not found
significant, t(12) = -1.607, p = 0.136.
During the first phase of active recovery (five minutes) cyclists
(159.4 ± 19.99W; n = 9) again produced significantly more power than non-
cyclists (127.9 ± 18.36W; n = 5), t(12) = 2.911, p = 0.013. Non-cyclists
(59.7 ± 6.08%; n = 5) rode at a higher oxygen uptake relative to VO2max than
cyclists (54.4 ± 7.94%; n = 9), t(12) = -1.182, p = 0.262.
For the following phase, intensity was increased and participants were
instructed to ride as strong as possible. Similar to the 20MTT, this five-minute
phase was intended to be viewed as a time trial. Non-cyclists (86.9 ± 8.45%;
n = 5) were able to sustain a slightly higher relative intensity than cyclists
(80.9 ± 7.37%; n = 9), t(12) = -1.278, p = 0.228. Meanwhile, cyclists
(313.4 ± 27.78W; n = 9) were averaging significantly higher power values than
non-cyclists (277.6 ± 22.00W; n = 5), t(12) = 2.468, p = 0.030.
During the second phase of active recovery (ten minutes) non-cyclists
(57.7 ± 4.86%; n = 5) maintained very similar VO2 relative to VO2max as cyclists
(55.9 ± 7.43%; n = 9), t(12) = -0.442, p = 0.667. Yet again, cyclists
(155.7 ± 19.31W; n = 9) produced significantly higher mean power outputs than
non-cyclists (118.5 ± 14.29W; n = 5), t(12) = 3.748, p = 0.003.
During the final stage, from which the FTP value was derived, the cyclists’
mean power output (261.4 ± 26.18W; n = 9) was significantly higher than in the
non-cyclists’ sub-sample (217.5 ± 26.59W; n = 5), t(12) = 2.995, p = 0.011. VO2
relative to VO2max was slightly higher in non-cyclists (77.0 ± 6.12%; n = 5) than
in cyclists (74.8 ± 5.62%; n = 9). The t-test did not show significance for the
difference between groups regarding intensity relative to VO2max
(t(12) = 0.665, p = 0.526).
Finally, FTP aims to quantify a certain level of intensity that can be maintained
over a prolonged period of time. After all, this concurs with the concept of any
threshold that aims to identify a maximal steady state, such as MLSS, lactate
threshold, and VT2. Therefore, absolute differences between power outputs at
VT2 and FTP were calculated for each subject. Comparison between sub-
samples was performed using the Wilcoxon rank-sum test in order to identify
potential tendencies. Non-cyclists (median = 84.73) show a greater difference
between power output at VT2 and FTP than cyclists (median = 63.84; exact
Wilcoxon rank-sum test: U = 11.000, p = 0.147).
Fig. 5: Oxygen intake relative to VO2max and power output during the FTP test for “cyclists” and “non-
cyclists”. VO2max = maximal oxygen uptake; t = time
Table 3: Power output [W] during each stage of the functional threshold power test (mean ± standard
Table 4: Oxygen uptake relative to maximal oxygen uptake [%VO2max] during each stage of the
functional threshold power test test (mean ± standard deviation)
5.3 Training recommendations based on FTP
In endurance training different intensities are associated with different
adaptation processes (Seiler & Tønnessen, 2009). Intensity and duration are
manipulated from day to day with the goal to maximize physiological
adaptation. In coaching and training practice, intensity for training prescription
is usually based on maximal or sub-maximal endurance markers. Previous
research has argued that training intensity based on submaximal markers
elicits significantly higher adaptations (Wolpern et al., 2015) and recent studies
examining intensity distribution (Esteve-Lanao, San Juan, Earnest, Foster, &
Lucia, 2005) have used the first and second ventilatory thresholds to define
three intensity zones. Figure 6 depicts a comparison of training intensity zones
derived from the classical 3-zone model and the model proposed by Allen and
Coggan (2012, p. 67) based on mean power output at ventilatory thresholds
and mean FTP, respectively. For the sample of the present study the average
power output at VT1 was found to be at 80.2% FTP (SD = 12.4%) and the
average power output at VT2 was equivalent to 135.8% FTP (SD = 11.1%).
Fig. 6: Training intensity zones derived from a classical 3-zone model based on ventilatory thresholds in
comparison with training intensity zones based on FTP according to the model by Allen and Coggan
(2012, p. 67). 3ZM = 3-zone model; FTP = Functional threshold power; LT = Lactate threshold;
VO2max = maximal oxygen uptake; VT1 = First ventilatory threshold; VT2 = Second ventilatory threshold
6.1 Discussion of results
The primary goal of this study was to evaluate potential relationships between
the ventilatory endurance parameters VO2max, VT1 and VT2 and FTP
assessed with a 20MTT. Previous research by Klika et al. (2007),
Nimmerichter et al. (2010), Gavin et al. (2012), and Sanders et al. (2017) has
shown promising results regarding the association of VO2max and various
lactate and ventilatory threshold values with average power output during time
trials of varying duration.
Results show strong correlation with FTP for VO2max and VT2. Interestingly,
absolute values of VO2max (r = 0.890; p < 0.001) showed greater correlation
with FTP than VO2max relative to body weight (r = 0.653; p = 0.011). This may
indicate that the association of body weight with power output during a 20MTT
is negligible or even confounding. Partial correlation analysis correcting for the
influence of age, height and body weight substantiates this assumption (table
2). However, this is not in line with the report of Gavin et al. (2012), who could
show an almost perfect correlation r = 0.970 (p < 0.001; n=7) for the association
of relative VO2max and FTP. This could be accounted for by the homogenous
sample used by Gavin et al. (body weight: 67.8 ± 1.8kg). Linear regression
revealed that 77.6% of FTP’s total variance could be attributed to absolute
VO2max. From a clinical point of view, where VO2max is associated with the
loss of independence in elderly people (Shephard, 2009) and the risk of death
in patients with cardiovascular disease and healthy subjects (Myers et al.,
2002), FTP testing may be used as an alternative method to indirectly estimate
As FTP is a threshold value estimating the level of power that can be
maintained over one hour without fatiguing (Allen & Coggan, 2012), it was
expected that FTP would be equivalent to or slightly below power output at
VT2. Results showed a correlation coefficient of r = 0.820 (p = 0.001), but FTP
(233.5 ± 31.75W) and average power during the 20MTT (245.7 ± 33.42W)
differed strongly from power output at VT2 (314.6 ± 30.32W). This is in stark
contrast to the results reported by Nimmerichter et al. (2010), who found that
for a sample of 15 professional cyclists power at VT2 was equivalent to
average power output during a 20MTT. Even after considering the inertia of
the pulmonary response to an increase in intensity of 30 to 40 seconds
(Amann et al., 2006), the discrepancy is not accounted for. Further explanation
could be provided by the comparison of methodological approaches. Each
time breath-by-breath analysis of respiratory gas exchange was used and the
second ventilatory threshold was primarily based on a disproportionately steep
increase of respiratory equivalent (VE) compared to VCO2 in both cases.
Contrary to the study by Nimmerichter et al. (2010) the 20MTT was executed
under laboratory conditions, which may have led to a certain bias. Karsten,
Jobson, Hopker, Jimenez, and Beedie (2014) reported significant differences
between field and laboratory trials regarding the average power output during
time trials ranging from three to seven minutes. They reasoned that these
differences are due to differences in experimental and environmental
conditions, such as acceleration against air resistance and the use of body
weight during the acceleration phase. Additionally, the sample used by
Nimmerichter et al. (2010) was a group of world class elite cyclists who may
be able to tolerate higher intensities compared to their VO2max and VT2 for a
longer period of time than recreational cyclists (Billat et al., 1996).
In opposition to VT2, VT1 is a measure of aerobic generation of energy rather
than a highest maximal steady state. Since it is in the nature of a 20MTT to
keep the intensity as high as possible, the relationship between power output
at VT1 and FTP was not expected to be as strong. In fact, according to the
adjusted R2 only 24.1% of the FTP total variance can be attributed to changes
in VT1. The correlation coefficient r = 0.547 (p = 0.043; n=14) is lower than the
one reported by Nimmerichter et al. (2010), who could show a strong
correlation of r=0.750. However, based on the evidence, functional threshold
does not provide means to accurately estimate VT1.
Comparison of cyclists with non-cyclists revealed significantly higher values in
cyclists throughout most variables, including absolute VO2max, power output
at VT1, FTP (table 1), and power output during all stages of the FTP test
(table 3). These differences are most likely due to a greater endurance
capacity, experience, and cycling specific motor patterns. The hypothesis, that
cyclists would be able to sustain a higher intensity relative to their VO2max
than non-cyclists could not be confirmed. Cyclists (mean = 74.8%) and non-
cyclists (mean = 77.0%) exercised at very similar relative intensities during the
20MTT. These results are in proximal range to those of other authors. Fifteen
professional cyclists, who participated in a study by Nimmerichter et al. (2010),
averaged ~79% VO2max during a 20MTT. Differences between cyclists and
non-cyclists in this present study may have occurred by chance due to the
small size of the sub-samples.
While intensity relative to maximum during a 20MTT seems to be equal across
performance levels, power output relative to the second ventilatory threshold
differs between groups. The mean difference between FTP and power output
at VT2 was less for cyclists (76.7 ± 18.35W) than for non-cyclists
(89.2 ± 18.34W) and, as reported by Nimmerichter et al. (2010), professional
athletes that compete on the highest level are able to maintain an average
power above 100% of the power output at VT2 over the duration of 20
minutes. Fatigue imposed by the stages prior to the 20MTT may be
additionally explanatory for the difference between groups. Yet, from a
methodological perspective, the study design by Nimmerichter et al. (2010)
was similar to the design of the present study. The 15 professional cyclists
performed an incremental exercise test to determine ventilatory endurance
determinants (25W increase each minute) and a 20MTT after a 4MTT with 30
minutes of active rest in between. Therefore, an initial level of fatigue had been
induced before the 20MTT, as well.
The derivation of training intensity zones based on FTP is illustrated in figure
6. By visual inspection it becomes apparent that FTP underestimates VT2
considerably. As discussed above, this discrepancy decreases with increasing
6.2 Discussion of methodology
The execution of all tests on the same bicycle ergometer under laboratory
conditions entailed several advantages as well as disadvantages. The use of
the same measurement system for each test assured high comparability of
power output. During both tests ventilatory data was collected with the same
equipment under similar environmental conditions. Hence, data was compared
on the assumption of high reproducibility.
Body positioning on the bicycle was fitted to the individuals’ proportions.
Height of saddle and handlebar, as well as distance between saddle,
handlebar and cranks was modifiable. Inexperienced riders were assisted by
the investigator. Generally, body position has an effect on power output, as
reported by Jobson, Nevill, George, Jeukendrup, and Passfield (2008). They
had nine male non-elite competitive cyclists complete three 40.23km time
trials, two of which were completed in the laboratory. The third time trial was
executed in the field. Laboratory time trials were performed in an upright
position and an aerodynamically optimized position. Results showed no
significant difference between power output in an upright position and during
the field trial. However, mean power output in the aerodynamic position was
significantly lower than both other trials. In the present study no instructions
regarding body position were given, and although bicycle ergometer
adjustments were recorded and applied for the FTP test, it was not controlled
for changes in body position between tests. Therefore, confounding effects of
body position on the ergometer cannot be excluded.
All subjects were enabled to manipulate resistance according to their individual
needs with the implicit goal to replicate field conditions. However, with the
ergometer used, power was independent from cadence. Therefore the
participants could not increase power output by pedaling at a higher cadence.
This is in contrast to field conditions, where a higher power output can be
achieved by increasing cadence without shifting into a higher gear, for
example in a finishing sprint. It is unclear whether this has had an altering
effect on the outcome of the tests.
Respiratory gas exchange measurements during the FTP test may have led to
mild hypohydration and to a decrease in performance (James, Moss, Henry,
Papadopoulou, & Mears, 2017). As participants wore a mask throughout the
entire test, they were not able to ingest water. Even though they were
instructed to show up well hydrated, hydration status was not measured
As power output at ventilatory thresholds were key variables of interest in this
study, it is important to point out that the relations between power output and
threshold are influenced by the test protocol used to assess threshold values.
Prior research (Francis Jr., Quinn, Amann, & Laroche, 2010) has shown that
the time to exhaustion in a laboratory test affects power output at ventilatory
endurance parameters. This must be taken into consideration when comparing
the results of the present study to findings of other researchers.
7. Conclusion and prospect
The FTP test aims to quantify the maximal power output that a cyclist is able to
maintain over the course of one hour without fatiguing, in a reliable and easily
implementable manner. Due to significant associations of endurance related
ventilatory parameters with the performance during a 20MTT, FTP testing
appropriately reflects the actual state of an athlete’s fitness. VO2max and VT2
accurately predict FTP. VT1 is not suitable for the prediction of FTP, and vice
versa. For a population of active non-elite males between 20 and 46 years of
age, FTP underestimates power output at VT2 considerably. However with
increasing endurance capacity, this discrepancy tends to decrease. Therefore,
FTP test results should not be interpreted interchangeably with laboratory
As the research has demonstrated, the FTP test based on a 20MTT is an
applicable tool to monitor the training progress and establish training intensity
zones. Further research is needed to verify the finding of the present study in
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