Gross efficiency and cycling performance: a brief review

Abstract

Efficiency, the ratio of work generated to the total metabolic energy cost, has been suggested to be a key determinant of endurance cycling performance. The purpose of this brief review is to evaluate the influence of gross efficiency on cycling power output and to consider whether or not gross efficiency can be modified. In a re-analysis of data from five separate studies, variation in gross efficiency explained ~30% of the variation in power output during cycling time-trials. Whilst other variables, notably VO2max and lactate threshold, have been shown to explain more of the variance in cycling power output, these results confirm the important influence of gross efficiency. Case study, cross-sectional, longitudinal, and intervention research designs have all been used to demonstrate that exercise training can enhance gross efficiency. Whilst improvements have been seen with a wide range of training types (endurance, strength, altitude), it would appear that high intensity training is the most potent stimulus for changes in gross efficiency. In addition to physiological adaptations, gross efficiency might also be improved through biomechanical adaptations. However, ‘intuitive’ technique and equipment adjustments may not always be effective. For example, whilst ‘pedalling in circles’ allows pedalling to become mechanically more effective, this technique does not result in short term improvements in gross efficiency.

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J Sci Cycling. Vol. 1(1), 3-8
© 2012 Jobson; licensee JSC. This is an Open Access article distributed under the terms of the Creative Commons Attribution License
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REVIEW ARTICLE
Open Access
Gross efficiency and cycling performance: a
brief review
Simon A Jobson1, James G Hopker2, Thomas Korff3 and Louis Passfield2
Abstract
Efficiency, the ratio of work generated to the total metabolic energy cost, has been suggested to be a key
determinant of endurance cycling performance. The purpose of this brief review is to evaluate the influence of gross
efficiency on cycling power output and to consider whether or not gross efficiency can be modified. In a re-analysis
of data from five separate studies, variation in gross efficiency explained ~30% of the variation in power output
during cycling time-trials. Whilst other variables, notably VO2max and lactate threshold, have been shown to explain
more of the variance in cycling power output, these results confirm the important influence of gross efficiency. Case
study, cross-sectional, longitudinal, and intervention research designs have all been used to demonstrate that
exercise training can enhance gross efficiency. Whilst improvements have been seen with a wide range of training
types (endurance, strength, altitude), it would appear that high intensity training is the most potent stimulus for
changes in gross efficiency. In addition to physiological adaptations, gross efficiency might also be improved through
biomechanical adaptations. However, ‘intuitive’ technique and equipment adjustments may not always be effective.
For example, whilst ‘pedalling in circles’ allows pedalling to become mechanically more effective, this technique
does not result in short term improvements in gross efficiency.
Keywords: cycle training, biomechanics, pedalling, pedaling
 Contact email: simon.jobson@winchester.ac.uk (SA.
Jobson)
1 Department of Sports Studies, University of Winchester, Hampshire,
England.
2 Centre for Sports Studies, University of Kent, Kent, England.
3 School of Sport and Education, Brunel University, Middlesex, England.
__________________________________________________
Received: 8 March 2012. Accepted: 30 June 2012.
Introduction
Efficiency, defined as the ratio of work generated to the
total metabolic energy cost, has been suggested to be a
key determinant of endurance cycling performance
(Joyner & Coyle 2008). The efficiency of energy
consumption during cycling has been reviewed
previously (Ettema & Lorås, 2009). However, whilst
some consideration of the factors that influence gross
efficiency (e.g. muscle fibre type) has been given
(Coyle et al. 1992), several fundamental assumptions
related to the importance of gross efficiency have
received very little experimental verification. The
purpose of this brief review is to evaluate the influence
of gross efficiency on cycling power output and to
consider whether or not gross efficiency can be
modified. In theory, gross efficiency could be affected
both by physiological and biomechanical changes.
However, there is much debate over the relative
importance, indeed, existence, of such changes. This
brief review will consider: 1) the influence of gross
efficiency on cycling power output; 2) the effects of
training on gross efficiency in cycling; and 3) the
relationship between pedalling mechanics and gross
efficiency in cycling.
The influence of gross efficiency on cycling
performance
Athletic performance has long been known to have a
wide range of physiological determinants. In 1925 A.V.
Hill emphasised the importance of muscle fatigue and
discussed issues related to energy stores and oxygen
demand (Hill 1925). Recently, more comprehensive
models of athletic performance have been presented.
Joyner and Coyle (2008) described a model where
performance velocity or performance power is
dependent upon 3 key parameters: performance VO2,
performance O2 deficit, and gross efficiency. The
determinants of performance VO2, suggested to be
primarily VO2max and lactate threshold, and
performance O2 deficit, have received comprehensive
research attention. In contrast, very few studies have
evaluated the relative influence of gross efficiency.
Indeed, despite being elevated to one of the 3
determinants of performance by Joyner and Coyle
(2008), to the authors’ knowledge, only two studies
have described any link between efficiency and
performance (Horowitz et al. 1994; Passfield & Doust
2000). Horowitz et al. divided an apparently
homogeneous group of 14 endurance-trained cyclists
according to gross efficiency during a 1-hour
laboratory time-trial (i.e. a high- and a low-efficiency
group). Both groups maintained the same VO2
throughout the time-trial, but the high-efficiency
groups were able to generate 10% more power. Whilst
providing an initial insight into the importance of gross

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Jobson et al.
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efficiency, it is difficult to generalize this result
because of the homogeneous nature of the participants
used and limitations in the determination of gross
efficiency.
In order to clarify the link between gross efficiency and
cycling performance, we here provide a re-analysis of
data from three published and two unpublished
investigations. Linear regression was used to determine
the correlation between gross efficiency and cycling
power output data from five separate studies (S1–S5).
S1 (Jobson et al. 2008) measured gross efficiency at 3
W•kg-1 and power output during a 40-km laboratory
time-trial. S2 (Horowitz et al. 1994) measured gross
efficiency during a 1-hour laboratory time-trial. Gross
efficiency values were derived from Figure 1 in
Horowitz et al. (1994). S3 (Hopker et al. unpublished
observations) measured gross efficiency at 200 W and
300 W in a group of 10 untrained and 9 trained cyclists
respectively. S4 (Jobson et al. unpublished
observations) measured gross efficiency at 150 W in a
group of 10 trained cyclists. S5 (Passfield & Doust
2000) measured gross efficiency at 208 W. Power
output was measured during a 5-min laboratory time-
trial in S3, S4, and S5.
Gross efficiency was correlated with ‘long’ (40-km and
1-hour) time-trial cycling power output (S1: r=0.74,
p=0.04; S2: r=0.51, p=0.06; S1 and S2 combined:
r=0.58, p=0.004) and ‘short’ (5-min) time-trial cycling
power output (S3: r=0.53, p<0.0001; S4: r=0.59,
p=0.73; S5: r=0.51, p=0.02; S3, S4 and S5 combined:
r=0.48, p<0.0001).
Variation in gross efficiency explained 34% and 26%
of the variation in power output during long and short
cycling time-trials respectively. Whilst other variables,
notably VO2max and lactate threshold, have been shown
to explain more of the variance in cycling power
output, these results confirm the important influence of
gross efficiency.
The effects of training on gross efficiency
Given that gross efficiency has been shown to correlate
with cycling power output, it is important to consider
whether or not efficiency can be modified. There is
growing evidence in the scientific literature for the
possibility of increasing gross efficiency in cycling
through training (Hopker et al. 2007; Hopker et al.,
2009; Santalla et al. 2009; Hopker et al. 2010). Recent
results indicate that gross efficiency increases over the
period of one (Hopker et al. 2009) and many cycling
seasons (Santalla et al. 2009). Thus, increases in gross
efficiency may be related to the volume and intensity of
training undertaken by cyclists.
To investigate this hypothesis, Hopker et al. (2010)
evaluated the impact of training intensity on efficiency
in competitive cyclists. In this study, 29 endurance-
trained competitive male cyclists completed three
laboratory visits over a 12-week training period. At
each visit, gross efficiency and maximal oxygen uptake
were determined. Cyclists were randomly split into two
groups (A and B). Over the first 6 weeks, group A was
prescribed two specific high-intensity training sessions
per week, whereas group B did not complete high-
intensity training. For the second 6-week period, group
B introduced high-intensity training, whilst group A
continued unrestricted. Gross efficiency increased in
group A (+1.6 ± 1.4%; p<0.01) following the high-
intensity training, whereas no significant change was
seen in group B (+0.1 ± 0.7%; p>0.05) (see Figure 1).
Group B cyclists did increase their gross efficiency
over weeks 6 to 12 (+1.4 ± 0.8%; p<0.01). No changes
in gross efficiency were observed in group A over this
period (+0.4 ± 0.4%; p>0.05).
To our knowledge, this was the first study to
experimentally demonstrate that exercise training alone
increases efficiency. These changes in efficiency
appear to be influenced by the volume and intensity of
training undertaken by cyclists. More specifically, it
would appear that high intensity training is the most
potent stimulus for changes in gross efficiency.
However, our work (Hopker et al. 2009; Hopker et al.
2010) also suggests that in trained cyclists, training
increases GE, but not VO2max. Indeed, an inverse
relation between GE and VO2max appears to exist.
Cyclists with a high VO2max seem to be less responsive
to training related changes in GE than those with a
lower VO2max (Hopker et al. 2012).
Improvements in cycling efficiency have also been
shown following a period of acclimatization at altitude
in a group of mountaineers (Green et al. 2000).
Following return to sea level, the climbers
demonstrated increases in cycling net efficiency. This
finding was repeated by Gore et al. (2001) using a
group of trained athletes living in a normobaric hypoxic
environment (O2 15.48%) for 9.5 hours per night for
twenty-three consecutive nights. Using groups matched
for fitness, participants followed either a live high
(simulated 3000 m): train low (600 m) (LHTL), or a
control (600 m) training strategy. Exercise tests for
cycling net efficiency were conducted at baseline, 11
Figure 1. Relative changes in gross efficiency (GE) across the study
period. Values are averaged across intensities to the highest common
work rate and presented as means ± standard deviation. Group A
completed: high intensity training between tests 1 and 2; unrestricted
training between tests 2 and 3. Group B completed: no high intensity
training between tests 1 and 2; unrestricted training between tests 2 and
3. * = significant increase above previous test (p < 0.05); † = significant
difference between groups (p < 0.05). Source: Hopker et al. (2010).

Jobson et al. (2012). Gross efficiency and cycling performance: a brief review. Journal of Science and Cycling, 1(1): 3-8
Page 5
days into the training regimen, and after a 23-day
acclimatization period. Results of the study
demonstrated that submaximal VO2 was reduced
(4.4%, p<0.05) and net efficiency improved (0.8%,
p<0.05) in the LHTL condition, fuel utilization shifting
from fat to carbohydrate oxidation (as shown by a
higher RER post acclimatization). Interestingly, Gore et
al. also demonstrated a significant decline in VO2max in
the altitude-acclimatized group, resulting in an inverse
relation between efficiency and VO2max.
Whilst many factors no doubt influence both gross
efficiency and VO2max, a possible mechanism for the
inverse relation between these parameters is suggested
by studies that have investigated the effects of nitrate
supplementation. A simple inorganic anion abundant in
green leafy vegetables, nitrate appears to be readily
reduced to nitric oxide and other reactive nitrogen
intermediates (Lundberg et al. 2008). Short-term nitrate
supplementation has been shown to reduce exercise
oxygen cost (i.e. to increase efficiency) (Bailey et al.
2009, 2010; Larson et al. 2007, 2011) and to decrease
VO2max (Larson et al. 2010).
The results of Larson et al. (2011) suggest that nitrate
supplementation has a direct impact on mitochondrial
function, reducing proton leak as a result of the
downregulation of adenine nucleotide translocator (and
possibly uncoupling protein 3). This necessarily
increases the number of molecules of ATP generated
per atom of oxygen consumed (the P/O ratio) and,
therefore, mitochondrial efficiency. The nitrate-induced
reduction in VO2max appears to be the result of a small
increase in p50, the oxygen tension where half-
maximal respiration occurs. Larson et al. (2011) have
shown that such an increase leads to an oxygen
limitation remarkably similar to observed reductions in
VO2max. Thus, nitrate may increase gross efficiency, by
increasing the P/O ratio, and reduce VO2max, by
increasing p50. Given the similarity of the gross
efficiency/ VO2max response in these studies to those
described in the training studies above, we might
speculate that training leads to a natural increase in the
body’s nitrate levels.
Whilst this ‘nitrate hypothesis’ might be dismissed for
its disconnect from the real exercise training-related
inverse relation described above, it finds support in
research on high-altitude-living Tibetans. These high
altitude natives have been shown to have significantly
lower VO2 at submaximal work rates (i.e. higher gross
efficiency), lower VO2max values and >10-fold higher
circulating nitrate levels than inhabitants of lower
altitudes (Curran et al. 1998; Erzurum et al. 2007; Ge et
al. 1994).
Recent research findings suggest that short-term
strength training can also enhance gross efficiency
(Paton & Hopkins 2005; Sunde et al. 2010; Ronnestad
et al. 2011). Ronnestad et al. (2011) have shown that a
12-week period of heavy strength training can enhance
gross efficiency during the last hour of a 3-hour bout of
submaximal cycling. This was also accompanied by
reductions in blood lactate concentration and reductions
in ratings of perceived exertion. The mechanisms
linking strength training and improvements in gross
efficiency are unknown, though this link is no doubt
dependent upon the mechanism that causes the strength
gain. Whilst we cannot discount a neurological
mechanism, we speculate that the improvement in gross
efficiency is due to strength gains resulting from
muscle hypertrophy. Heavy strength training increases
maximal force. Consequently, the peak force, or muscle
fibre tension, developed in each pedal thrust becomes a
lower percentage of the maximal force. In turn, this
might allow greater recruitment of more efficient and
fatigue-resistant type I muscle fibers.
The biomechanics of efficiency in cycling
Using instrumented force pedals or cranks in
combination with kinematic analyses allows us to
determine the mechanical effectiveness of the pedal
stroke or the magnitude of rotational forces that
muscles generate about the ankle, knee and hip joints.
From a basic science perspective, biomechanical
analyses enable us to understand how the muscles of
the lower limb work in synergy to deliver force to the
crank. Such knowledge has practical implications for
cycling coaches. In this section, we discuss the
relationship between mechanical effectiveness of the
pedal stroke and efficiency and the usefulness of
mechanical variables in the context of a cyclist’s
selection of the preferred pedalling cadence.
Pedal force effectiveness can be defined as the
proportion of the effective force (the force component
that acts in the direction of the movement) relative to
the resultant pedal force. The meaningfulness of this
measure and its association with gross efficiency has
been under debate. From a purely mechanical
perspective, it seems intuitive to associate greater force
effectiveness with increased cycling efficiency as a
greater proportion of total force is used to propel the
crank. However, this association is limited for two
reasons. First, forces measured on the pedal include
gravitational and motion dependent influences. Thus,
only a portion of the measured pedal force can be
attributed to muscular effort (Kautz & Hull 1993;
Neptune & Herzog, 1999). The second reason for the
limited meaningfulness of pedal force effectiveness is
the unique configuration of our musculo-skeletal
anatomy. Maximising the effective force relative to
total force implies minimizing the radial force (the
force component acting along the crank toward the
centre of rotation). Due to the constrained positions of
body segments with respect to the bicycle and of
muscles with respect to the bones, a certain amount of
radial force is needed for muscles to work efficiently.
In an elegant modelling study, Höchtl et al. (2010)
demonstrated that a significant amount of radial force is
necessary to maximize cycling efficiency,
demonstrating the limited usefulness of measures of
mechanical effectiveness of pedal forces.
Several authors have investigated the relationship
between force effectiveness and cycling efficiency
experimentally. Both Zameziati et al. (2006) and
Leirdal & Ettema (2011) showed that mechanical force

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Page 6
effectiveness is positively correlated with gross
efficiency when analysed across participants. This
result is in contrast to Edwards et al. (2009) who found
no association between mechanical force effectiveness
and gross efficiency across participants and across a
range of cycling conditions. The different results are
possibly explained by differences in the measurement
of efficiency. Edwards et al. (2009) measured
efficiency at absolute power outputs and cadences,
whilst Leirdal & Ettema (2011) measured efficiency at
relative power outputs and with participant selected
cadences.
A limitation to all of these studies is the cross sectional
nature of the study design, as the correlational analyses
do not provide incontrovertible evidence about cause
and effect. Using a within subject design, which
overcomes this limitation, Korff et al. (2007) showed
that, when a cyclist is instructed to change his/her
preferred pedalling style to increase the ratio of force
effectiveness (“pedal in circles” or “pull on the pedal”),
gross efficiency is significantly reduced. This suggests
that short-term changes in pedalling technique can be
detrimental to submaximal cycling performance. In this
study, participants performed all tests on one day
without the possibility of getting used to the new
pedalling style. Therefore, the question arises as to
whether or not changes in pedalling technique can
affect cycling efficiency if participants are given the
opportunity to adapt to a new pedalling style. To
address this question, several authors have used the
decoupled crank paradigm to investigate the issue
longitudinally. Training with decoupled cranks forces
the cyclist to actively pull on the pedal during the
upstroke, with potential implications for pedalling
technique and cycling efficiency. Luttrell & Potteiger
(2003) reported that 6 weeks of training with decoupled
cranks resulted in improved cycling efficiency.
However, the participant selection in this study was
poorly controlled, and thus, the meaningfulness of
these results is limited. Williams et al. (2009)
quantified the effect of training with decoupled cranks
on pedalling technique and cycling efficiency in a more
controlled fashion. These authors found no significant
effects of training with decoupled cranks on cycling
efficiency. Expanding on these results, Böhm et al.
(2008) showed that training with decoupled cranks can
change certain aspects of the pedalling technique
without changing physiological variables. Together, the
experimental evidence suggests that the acquisition of
new pedalling techniques does not result in significant
increases in gross efficiency in the short to medium
term. However, more research is needed to thoroughly
address long-term adaptations to changes in pedalling
technique with respect to cycling efficiency.
Specifically, the aforementioned studies by Zameziati
et al. (2006) and Edwards et al. (2009) allow us to
speculate that years of practicing a mechanically
effective pedalling style may result in improved cycling
efficiency. Within this context, and bearing in mind the
aforementioned limited usefulness of measures of force
effectiveness, researchers may wish to investigate more
meaningful mechanical parameters (Leirdal & Ettema,
2011).
Biomechanical analyses of cycling can also help us
better understand how cyclists choose their preferred
pedalling cadence during submaximal cycling. When
adults are asked to ride at their preferred pedalling rate
at a power output typically experienced during
submaximal cycling, they tend to choose a cadence
between 90 and 100 revolutions per minute (rev•min-1)
(Hagberg et al. 1981; Marsh & Martin 1993; Marsh &
Martin 1997; Marsh & Martin 2000). (It should be
noted that that the preferred cadence depends on
multiple factors including power output as well as a
cyclist’s cycling experience, fitness level and fibre type
distribution. However, an exhaustive discussion of
these factors is beyond the scope of this brief review.)
However, we also know that the cadence at which
metabolic efficiency is maximised is between 60 and
70 rev•min-1 (Seabury et al. 1977; Hagberg 1981;
Böning et al. 1984; Coast & Welch 1985; Sidossis et al.
1992) suggesting that maximising metabolic efficiency
is not an important contributor to the selection of the
preferred cadence. Here, biomechanical analyses of
cycling provide further insights. Several authors have
quantified the magnitude of muscular torques (Redfield
& Hull 1986; McLean & LaFortune 1991; Marsh &
Martin 2000) or forces (Neptune & Hull 1999) across
cadences. These studies consistently show that joint
torques are minimal close to the preferred cadence,
which suggests that the minimisation of muscular
forces is a priority of the nervous system within the
context of the selection of the preferred pedalling rate.
Another mechanical variable, which potentially
influences the selection of the preferred cadence is the
production of (inefficient) negative muscular work.
Neptune and Herzog (1999) quantified negative
muscular work across a range of cadences and found
that there is a significant amount of negative
mechanical work above the preferred cadence of 90
rev•min-1. The authors concluded that at higher
cadences, the nervous system might not be able to
activate and deactivate the muscles fast enough to
produce more efficient force patterns (Neptune &
Herzog 1999). Together, these findings demonstrate
that the selection of preferred cadence is driven by
mechanical factors (rather than the maximisation of
metabolic efficiency). Specifically, they suggest that
cyclists choose their preferred cadence to minimise
muscular forces, muscular stress and inefficient,
negative muscular work, possibly with the goal of
avoiding or delaying muscular fatigue.
Summary
Variation in gross efficiency explains ~30% of the
variation in power output during cycling time-trials.
Whilst other variables, notably VO2max and lactate
threshold, explain more of the variance in cycling
power output, this result confirms that gross
efficiency is an important determinant of cycling
performance. Furthermore, it is apparent that
exercise training can enhance gross efficiency.

Jobson et al. (2012). Gross efficiency and cycling performance: a brief review. Journal of Science and Cycling, 1(1): 3-8
Page 7
Improvements have been seen with a wide range of
training types (endurance, strength, altitude), though
high intensity training appears to provide the most
potent stimulus for changes in gross efficiency. Short
or medium term changes in pedalling technique have
no or detrimental effects on gross efficiency. Further
research is needed to test the effect of long-term
changes in pedalling technique on gross efficiency.
Conflict of interest
The authors declare that they have no conflict of interest.
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