ORIGINAL RESEARCH ARTICLE
A Comparison of the Energetic Cost of Running in Marathon
•Jesse H. Frank
•Emily M. Farina
Published online: 16 November 2017
ÓThe Author(s) 2017. This article is an open access publication
Background Reducing the energetic cost of running seems
the most feasible path to a sub-2-hour marathon. Footwear
mass, cushioning, and bending stiffness each affect the
energetic cost of running. Recently, prototype running
shoes were developed that combine a new highly compliant
and resilient midsole material with a stiff embedded plate.
Objective The aim of this study was to determine if, and to
what extent, these newly developed running shoes reduce
the energetic cost of running compared with established
marathon racing shoes.
Methods 18 high-caliber athletes ran six 5-min trials (three
shoes 9two replicates) in prototype shoes (NP), and two
established marathon shoes (NS and AB) during three
separate sessions: 14, 16, and 18 km/h. We measured
submaximal oxygen uptake and carbon dioxide production
during minutes 3–5 and averaged energetic cost (W/kg) for
the two trials in each shoe model.
Results Compared with the established racing shoes, the
new shoes reduced the energetic cost of running in all 18
subjects tested. Averaged across all three velocities, the
energetic cost for running in the NP shoes
(16.45 ±0.89 W/kg; mean ±SD) was 4.16 and 4.01%
lower than in the NS and AB shoes, when shoe mass was
matched (17.16 ±0.92 and 17.14 ±0.97 W/kg,
respectively, both p\0.001). The observed percent chan-
ges were independent of running velocity (14–18 km/h).
Conclusion The prototype shoes lowered the energetic cost
of running by 4% on average. We predict that with these
shoes, top athletes could run substantially faster and
achieve the ﬁrst sub-2-hour marathon.
Recently, running shoes were developed that
combine a new highly compliant and resilient
midsole material with a stiff embedded plate.
We showed that these newly developed running
shoes reduce the energetic cost of running by an
average of 4% compared with established marathon
We predict that with these shoes, top athletes can run
substantially faster and achieve the ﬁrst sub-2-hour
Like the quest to run the ﬁrst sub-4-minute mile , the
possibility of running a sub-2-hour marathon has captivated
the interest of the public, athletes, and scientists [2–4]. The
world record for the 42.2 km (26.2 miles) marathon is
2:02:57 and thus a 1:59:59 time would require running
2.5% faster. Three physiological parameters generally
determine and predict the running velocity that can be
Locomotion Lab, Department of Integrative Physiology,
University of Colorado, Boulder, 354 UCB, Boulder, CO
Nike Sport Research Lab, One Bowerman Drive, Beaverton,
OR 97005, USA
Sports Med (2018) 48:1009–1019
sustained: the maximal rate of oxygen uptake (
lactate threshold, and the energetic cost of running (running
economy) [5,6]. Running economy has traditionally been
deﬁned as the rate of oxygen uptake in mL O
required to run at a speciﬁed velocity. However, since
oxygen uptake alone does not reﬂect metabolic substrate
differences , we prefer to deﬁne running economy as the
energetic cost of running at a speciﬁc velocity expressed in
W/kg. Among elite distance runners with a similar
and lactate threshold, a runner with a better running
economy (i.e., lower energetic cost of running) can be
expected to outperform runners with a higher energetic cost
of running . If an athlete can lower their energetic cost to
run at a speciﬁed velocity, then they should be able to run
faster with their existing physiological capacities .
Footwear mass, cushioning, and longitudinal bending
stiffness each affect the energetic cost of running. Lighter
running shoes reduce the energetic cost of running [10,11],
likely due to the reduced inertia for leg swing. Such
energetic savings directly translate to faster performance
. Running barefoot might seem optimal since it involves
zero shoe mass, but barefoot running is not energetically
optimal because it requires greater muscular effort for
cushioning the foot–ground impact [12,13]. Experiments
using special treadmills with springy or cushioned surfaces
have demonstrated up to 12% energy savings [13,14] that
are attributed to two factors. First, cushioning allows a
person to run with straighter legs (less knee ﬂexion) and
thus less muscular effort [14,15]. Second, treadmill sur-
faces can store and return mechanical energy [14,16,17].
Virtually all modern running shoes have midsoles made
from various foam materials that, to varying degrees,
cushion impact, store and return mechanical energy. The
amount of energy stored by a foam material depends on its
compliance—the amount of compression that occurs when
loaded with a certain force. Compliant foams are commonly
described as soft. Inevitably, all foams are viscoelastic; i.e.,
they dissipate some energy as heat . The percent of the
stored mechanical energy that is returned is called resilience.
Some materials/surfaces are compliant, but have low resi-
lience (e.g., a sandy beach) and thus increase the energetic
cost of running . However, compliance and resilience
are not mutually exclusive and new materials continue to
advance shoe technology. Recently, more compliant and
resilient shoe midsoles have been shown to reduce the
energetic cost of running by *1% . Taking these
observations together, theoretically, the best running shoe
foam would be lightweight, highly compliant, and resilient.
Running shoes can also enhance how the human foot
acts like a lever  to transmit the force developed by the
leg muscles (e.g., the calf) to the ground so that the body is
propelled upward and forward. To do so, scientists have
incorporated carbon-ﬁber plates into the midsole, thereby
increasing the longitudinal bending stiffness. Such plates
can reduce the energetic cost of running by *1% 
through changes in the leverage of the ankle joint and the
foot–toe joint (metatarsophalangeal joint) [22–24].
Recently, prototype running shoes were developed by
Nike, Inc. that combine a new highly compliant and resilient
midsole material with a stiff embedded plate (Fig. 1). The
purpose of this study was to determine if, and to what extent,
these newly developed running shoes reduce the energetic
cost of running (i.e. improve running economy) compared
with established marathon racing shoes. We compared both
the energetics and gross biomechanics of running in the
Nike prototype shoes (NP) with those of baseline marathon
racing shoes, the Nike Zoom Streak 6 (NS) and the shoes
used to run the ofﬁcial marathon world record, the adidas
adizero Adios BOOST 2 (AB). The NS and AB or their
predecessors were used to run the 10 fastest marathons prior
to the start of this study (early April 2016).
We hypothesized that the energetic cost of running
would be substantially reduced in the prototype shoes as
compared with the two established marathon racing shoe
models. We had no a priori hypotheses regarding biome-
chanics, but collected the data to possibly explain any
energetic differences found. Furthermore, we set out to
relate any potential reductions in the energetic cost of
running in the prototype shoes to elite marathon running
performance and the sub-2-hour marathon barrier.
2 Materials and Methods
2.1 Shoe Conditions
We compared new prototype shoes (NP, a prototype of the
recently released Nike Zoom Vaporﬂy) to baseline
Fig. 1 Exploded view of the Nike prototype shoe that incorporates a
newly developed midsole material and a full-length carbon-ﬁber plate
with forefoot curvature, embedded in the midsole
1010 W. Hoogkamer et al.
marathon racing shoes, the Nike Zoom Streak 6 (NS), and
the shoes that Dennis Kimetto wore when he set the current
marathon world record, the adidas adizero Adios BOOST 2
(AB) (Fig. 3). We added 51 and 47 g of lead pellets to the
NP and NS shoes, respectively, to equalize to the greater
mass of the AB shoes (250 g for size US10). This pre-
vented the confounding effects of shoe mass on the ener-
getic cost of running [9–11]. To prevent excessive wear
accumulation in the shoes, we used three pairs of each shoe
model in size US10 and two additional pairs of AB size
US9.5, because that model ﬁts a little bigger than the Nike
models. Total running use for any pair of shoes did not
exceed 50 km.
2.2 Mechanical Testing Protocol
To evaluate the relevant midsole properties, we used a
custom mechanical testing method developed in the Nike
Sport Research Lab. Rather than a more conventional
energy-constrained impact test , we implemented a
force-constrained mechanical testing approach [20,26].
This method allows for more realistically quantifying of
underfoot mechanical energy storage and return. We per-
formed the shoe mechanical testing after the running tests
to obviate possible cushioning inconsistencies that can
arise during an initial midsole ‘break-in’ period.
To properly execute a force-constrained mechanical
test, the compression force and regional distribution of
force needs to resemble that of human running. To
implement this, we mounted a rigid foot-form (shoe last)
to a material testing machine (Instron 8800 Series Ser-
vohydraulic System, Norwood, MA, USA) and snugly ﬁt
the foot-form into the fully constructed shoes (Fig. 2).
The material testing machine compressed the midsole in
the vertical direction by matching a general time history
of the vertical ground reaction force measured during
running. The force proﬁle had a peak magnitude
of *2000 N and a contact time of *185 ms, which is
similar to the loading that we measured for our subjects
at 18 km/h (Table 2). The foot-form shape and its
material testing machine attachment location produced
insole pressure patterns and magnitudes similar to those
recorded during running. We calculated the amount of
mechanical energy stored and returned for each shoe
condition from the area under the rising (storage) and
falling (return) portions of the force-deformation curves.
This custom test is limited to 1-dimensional actuation of
force over a pre-deﬁned contact region. True running force
ﬁdelity would require 3-dimensional forces, with options
for different loading phases to impart load on different
regions of the midsole. In addition, the way each runner
interacts with a shoe can vary due to many factors
including body mass, running velocity, and foot strike
pattern. Though limited, this simpliﬁed testing method
does provide a clean, general characterization of midsole
mechanical energy storage and return capabilities in a
direction relevant to the spring-mass behavior of runners
The mechanical testing revealed that the NP was
approximately twofold more compliant than the NS and
AB shoes, deforming 11.9 mm versus 6.1 and 5.9 mm,
respectively (Fig. 3). The NP stored substantially more
mechanical energy (area under the top trace). Furthermore,
the NP shoes were more resilient (87.0% energy return)
than the AB (75.9%) and NS (65.5%) shoes. Thus, com-
bined, the NP shoes can return more than twice the amount
of mechanical energy as the other shoes, which is mainly
due to its substantially greater compliance rather than the
greater percent resilience.
2.3 Human Subjects
18 male (aged 23.7 ±3.9 years, mass 64.3 ±4.7 kg, height
177.8 ±4.6 cm) high-caliber runners who wear men’s shoe
size US10 completed the testing protocol (
VO2max at the
local altitude *1655 m: 72.1 ±3.4 mL O
66.4–81.4 mL O
/kg/min). All had recently run a sub-
31 minute 10-km race at sea level, a sub-32 minute 10-km
race at the local altitude, or an equivalent performance in a
different distance running event. The study was performed
Fig. 2 A rigid foot-form (shoe last) was mounted to the material
testing machine actuator and snugly ﬁt into a fully-constructed shoe.
The actuated foot-form compressed the midsole in the vertical
direction to match the displayed general time history of the vertical
ground reaction force, producing insole pressure patterns similar to
those recorded during running at 18 km/h
Energetic Cost of Running Shoes 1011
in accordance with the ethical standards of the Declaration
of Helsinki. Ethics approval was obtained from the
University of Colorado Institutional Review Board (Pro-
tocol# 15-0114). Before taking part in the study, partici-
pants provided informed written consent.
2.4 Experimental Protocol
The study comprised four visits for each subject. Visit 1
established that subjects could run below their lactate
threshold  at 14, 16, and 18 km/h by measuring blood
lactate concentrations ([La]). During visits 2, 3, and 4, we
measured the subjects’ metabolic energy consumption rates,
ground reaction forces, and [La] at 14, 16, or 18 km/h while
wearing each of the three shoe conditions.
Subjects presented a 24-h dietary, sleep, and training log
before each visit. We strongly encouraged the subjects to
replicate their diet, sleep, and training pattern for all lab-
oratory visits. If replication was not met, we postponed the
2.4.1 Visit 1
Subjects wore their own shoes to run 5-min trials at
velocities of 14, 16, and 18 km/h on a level treadmill and
took a 5-min break between all trials. We used a hand-held
digital tachometer (Shimpo DT-107A, Electromatic
Equipment Inc., Cedarhurst, NY, USA) to verify the
treadmill velocities. To allow familiarization, subjects
breathed through the expired-gas analysis system during
Fig. 3 We performed mechanical testing on three marathon racing
shoe models. (Top left) The Nike Zoom Streak 6 (NS) midsole
comprises lightweight EVA (ethylene-vinyl acetate) foam, a rearfoot
Zoom air bag, 23 mm heel height, and 15 mm forefoot height. (Top
middle) The adidas adizero Adios BOOST 2 (AB) midsole comprises
BOOST foam made with TPU (thermoplastic polyurethane), 23 mm
heel height, and 13 mm forefoot height. (Top right) The Nike
prototype (NP) midsole comprises a new ZoomX foam made with
PEBA (polyether block amide), an embedded carbon ﬁber plate,
31 mm heel height, and 21 mm forefoot height. (Bottom) Force-
deformation curves, peak deformation, and energy return metrics for
each shoe during vertical midsole loading with a peak force
of *2000 N and contact time of *185 ms (Table 2). As vertical
force is applied, the shoe midsole deforms (upper trace in each graph).
Then, as the shoe is unloaded, the force returns to zero as the midsole
recoils (lower trace in each graph). The area between loading and
unloading curves indicates the mechanical energy (J) lost as heat. The
area below the lower traces represents the amount of elastic energy
(J) that is returned
1012 W. Hoogkamer et al.
this session (True One 2400, Parvo Medics, Salt Lake City,
UT, USA). Within 1 min after the completion of each 5-min
trial, we obtained a ﬁnger-prick blood sample for [La]
determination. We analyzed the blood samples in duplicate
with a YSI 2300 lactate analyzer (YSI, Yellow Springs, OH,
USA). Two individuals were excluded from the study after
Visit 1, reaching [La] values of 5.27 and 5.69 mmol/L at
18 km/h. The remaining 18 subjects were running at an
intensity below the onset of blood lactate accumulation
(OBLA), which speciﬁes an [La] of 4 mmol/L , and the
average [La] at 18 km/h was 2.81 ±0.71 mmol/L.
2.4.2 Visits 2, 3, and 4
Subjects began with a 5-min warm-up trial at 14 km/h in
their own shoes. Following the warm up, subjects com-
pleted six 5-min trials at one of the three velocities (14,
16, or 18 km/h, randomized) on a level force-measuring
treadmill with a rigid, reinforced aluminum deck, that
recorded horizontal and vertical ground reaction forces
. We measured the submaximal rates of oxygen
consumption and carbon dioxide production during each
trial using the expired-gas analysis system and calculated
the rate of metabolic energy consumption over the last
2 min of each trial, using the Brockway equation . In
each of the six trials, subjects wore one of the three shoe
conditions. In between trials, subjects took a 5-min break
while they changed shoes. Note that runners mechanically
adapt their biomechanics very quickly in response to
changes in surface stiffness . Subjects wore each shoe
model twice per visit, in a mirrored order, which was
counterbalanced and randomly assigned. With three shoe
conditions, there were six possible shoe orders and we
randomly assigned three subjects to each order. One
example of a mirrored order is AB, NS, NP, NP, NS, AB.
For all metrics, we averaged the two trials for each shoe
During the last 30 s of each trial, we recorded high-
speed video (240 frames/s, 1/1000 s shutter) using a Casio
EX-FH20 camera (Casio America, Inc., Dover, NJ, USA).
During the same 30 s, we recorded horizontal and vertical
ground reaction forces using a National Instruments
6009-DAQ and custom-written LabView software (Na-
tional Instruments, Austin, TX, USA). We low-pass ﬁltered
the ground reaction force data at 25 Hz using a recursive
4th order Butterworth digital ﬁlter and used a 30 N
threshold to determine foot-strike and toe-off events. We
used the video recordings to help determine the foot strike
patterns of the runners during all trials (rearfoot strike vs.
mid/forefoot strike). This was done by two raters (SK and
JHF) independently. When the video-based classiﬁcation
disagreed between raters (n=4), strike pattern was
classiﬁed based on visual inspection of the vertical ground
reaction force traces by a third rater (WH).
Following the sixth trial on each day, subjects ran an
additional trial at 14 km/h in a pair of control shoes (Nike
Zoom Streak LT 2). This allowed us to measure the indi-
vidual day-to-day variation in energetic cost of the subjects.
Only during visit 4, after a 10-min break, the subjects
VO2max test on a classic Quinton 18–60
treadmill. We set the treadmill velocity to 16 km/h and
increased the incline by 1% each minute until exhaustion
. Subjects wore their own shoes or the control shoes. We
continuously measured the rate of oxygen consumption and
VO2max as the highest 30-s mean value obtained.
Our criterion for reaching
VO2max was a plateau in oxygen
consumption rate after an increase in incline .
We compared energetic cost, peak vertical ground reaction
force, step frequency and contact time while running in the
three shoe conditions over three velocities using a two-way
ANOVA with repeated measures. When we observed a
signiﬁcant main effect for shoe, we performed Tukey’s
honest signiﬁcant difference post hoc analyses to determine
which shoe-by-shoe comparisons differed signiﬁcantly. To
evaluate any potential effects of foot strike pattern, we
compared energetic cost, peak vertical ground reaction
force, step frequency, and contact time using a three-way
ANOVA with repeated measures (shoe 9veloc-
ity 9strike pattern). Furthermore, we applied multiple
regression analyses to evaluate potential relationships
between changes in biomechanical measures and in ener-
getic cost of running. We used a traditional level of sig-
niﬁcance (p\0.05) and performed analyses with
MATLAB (The MathWorks, Inc., Natick, MA, USA) and
STATISTICA (Statsoft, Tulsa, OK, USA).
To estimate how much of an improvement in marathon
running performance would be predicted from a speciﬁc
reduction in energetic cost, we used the curvilinear rela-
tionship between running velocity and energy cost estab-
lished by Tam et al. . Their model was based on
overground running data in top-level Kenyan marathon
/kg/min) =5.7 ?9.8158 V ?0.0537 V
with velocity (V) in m/s.
The prototype shoes substantially lowered the energetic
cost of running by 4% on average. Notably, at all three
running velocities, energetic cost was lower in NP for each
Energetic Cost of Running Shoes 1013
and every subject compared with both NS and AB (Fig. 4).
Averaged across all three velocities, the energetic cost for
running in the NP shoes (16.45 ±0.89 W/kg; mean ±SD)
was 4.16 and 4.01% lower than in the NS and AB shoes
(17.16 ±0.92 and 17.14 ±0.97 W/kg, respectively, both
p\0.001). The NS and AB shoes were similar (p=0.34).
The percent differences between shoes were similar at the
three running velocities (all p[0.56). Among the 18 sub-
jects, the mean difference in energetic cost over the three
velocities between the NP and NS shoes ranged from -1.59
to -6.26% and from -1.97 to -6.08% for NP versus AB,
indicating considerable inter-individual variation in the
amount of energetic saving the NP shoes provided. For
reference, rates of oxygen uptake, energetic cost of trans-
port, and the oxygen cost of transport for each of the three
shoe models at all three velocities are listed in Table 1.
Respiratory exchange ratios (
remained\0.9 for all trials and [La] values after six trials
were\3 mmol/L for all velocities, but we did detect a
slight slow component in our recordings of oxygen con-
sumption. Across all conditions, the rate of oxygen con-
sumption averaged 1.0% greater during minute 5 versus
minute 4 (p\0.001). This was independent of shoe con-
dition and running velocity, and all the differences between
conditions were consistent for both minutes (all p[0.39).
For the control shoes at 14 km/h, the mean day-to-day
difference in energetic cost was 2.7%, the mean minimum
day-to-day difference was 1.0% and the mean maximum
day-to-day difference was 4.3%. Recall that we random-
ized and counterbalanced the order in which subjects ran at
each of the three velocities (14, 16, 18 km/h) to balance out
this day-to-day variation. Since subjects wore each pair of
shoes twice per visit, in a mirrored order, we could quantify
within-day variation. The mean absolute variation over all
running velocities and shoe conditions was 1.7%.
While running in the NP shoes, the subjects generally
ran with slightly greater peak vertical ground reaction
forces, slower step frequencies, and longer contact times
than in the control shoes (Fig. 5; Table 2). Peak vertical
ground reaction force (F
) was 1.1% greater in the NP
shoes than in the NS shoes (p=0.002) and increased at
faster running velocities in all shoes (all p\0.001). Step
frequency was 0.8 and 0.6% slower in the NP shoes than in
the NS and AB shoes, respectively; that is, slightly longer
steps in NP (both p\0.001). Step frequency increased at
the faster running velocities in all shoes (all p\0.001).
Contact time was slightly (0.6%) longer in the NP shoes
than in the NS shoes (p=0.020) and decreased at faster
running velocities in all shoes (all p\0.001). Together, the
percent changes in peak F
, step frequency, and contact
time explained 20% of the variance in the reductions in
energetic cost between NS and NP (p=0.009). Peak F
was the only individual biomechanical factor contributing
signiﬁcantly and energetic savings were paradoxically
correlated to increases in peak F
. The changes in energetic
cost between AB and NP or between NS and AB were not
signiﬁcantly correlated to changes in biomechanical mea-
sures (p=0.095 and p=0.8, respectively).
Although we did not set out to evaluate the foot strike
pattern interaction on the energetic cost differences
between shoes, our sample of runners did allow for such an
analysis. Eight of our subjects landed on their heels and ten
landed on their mid/forefoot. Overall, the energetic cost of
running was not different between rearfoot strikers and
mid/forefoot strikers (p=0.9; Table 3). However, a
shoe 9foot strike pattern interaction effect (p=0.0502)
suggests that the savings in the NP shoes were likely
somewhat greater for rearfoot strikers (NP vs. NS: 4.78%;
NP vs. AB: 4.63%) than for mid/forefoot strikers (3.67 and
3.50%, respectively). We did not observe signiﬁcant
shoe 9foot strike interactions for any of the biomechani-
cal parameters, but rearfoot strikers ran with longer contact
times than mid/forefoot strikers (p=0.001; Table 3).
The prototype shoes substantially lowered the energetic
cost of running by 4% on average. Shoe properties such as
mass, midsole compliance, resilience, and longitudinal
bending stiffness have all been shown to affect the ener-
getic cost of running [20,22]. However, reported energetic
savings due to running shoe properties are typically trivial
to small . For every 100 g of added mass per shoe, the
energetic cost of running increases by *1.0%. To prevent
the confounding effects of shoe mass on the energetic cost
NS AB NP
NS AB NP NS AB NP
Energetic Cost (W/kg)
14 km/h 16 km/h 18 km/h
Fig. 4 Over the three velocities tested, runners in the NP shoes used
an average of 4.16% less metabolic energy than the NS shoes and
4.01% less than in the AB shoes (both p\0.001). The AB and NS
shoes were similar (p=0.34). Values are the gross energetic cost of
running. NS Nike Zoom Streak 6, AB adidas adizero Adios BOOST 2,
NP Nike prototype
1014 W. Hoogkamer et al.
of running [9–11], we added 51 and 47 g of lead pellets to
the NP and NS shoes, respectively, to equalize to the
greater mass of the AB shoes. This suggests that
unweighted NP shoes would likely save an average
of *4.4% versus AB; assuming a conservative 0.8%
savings per 100 g of shoe mass [9,10]. Midsole air bag and
BOOST foam (made with thermoplastic polyurethane)
cushioning have each been shown to reduce the energetic
cost of running by 1–2.8% [12,36] or 1.1% , respec-
tively, as compared with conventional EVA (ethylene-
vinyl acetate) foam. Here, we compared the NP shoes to
two established marathon racing shoe models, which
incorporate either an air bag or BOOST foam, and ﬁnd an
additional 4% savings with the new shoes.
While the observed differences in energetic cost of
running between shoe conditions were as substantial as 4%,
the differences in our gross biomechanical measures (i.e.,
, step frequency, and contact time) were on the
order of only 1% (Table 2). Subjects ran with slower step
frequency, taking longer steps in the NP shoes. This is in
line with the observed higher peak F
and longer contact
time in the NP shoes compared with the NS shoes. How-
ever, differences of\1% in these variables seem too small
to have a substantial inﬂuence on energetic cost of running.
This was conﬁrmed by the multiple regression analyses
between the percent changes in each of the biomechanical
measures and in the energetic cost. A signiﬁcant correlation
was only observed for the differences between NS and NP,
with changes in biomechanics explaining\20% of the
energetic differences. Further, the differences in peak F
and in contact time were only signiﬁcant between NP and
NS, not between NP and AB, even though energetic sav-
ings for NP were similar to those for NS and AB.
Although gross measures of biomechanics showed little
differences between the different shoes, a biomechanical
explanation for the energetic savings is important to con-
sider. When running on compliant surfaces, people main-
tain their center of mass mechanics by reducing knee
ﬂexion during the stance period, which increases leg
stiffness . This improves the mechanical advantage of
the muscles acting around the joints, which reduces the
energetic cost of body weight support [14,37]. This same
mechanism likely contributes to the energy savings of the
very compliant NP shoes. However, we did not record joint
kinematics in the present study and thus cannot yet quan-
tify any differences in peak knee ﬂexion during stance in
the different shoes.
For now, the elastic properties of the NP shoes provide
the best explanation for the metabolic energy savings. Our
mechanical testing quantiﬁed that the NP shoes returned
7.46 J of mechanical energy per step versus 3.38 and 3.56 J
for the NS and AB shoes, respectively (Fig. 3). The greater
mechanical energy return in the NP shoes is mainly due to
Table 1 Energetic costs, rates of oxygen uptake (
VO2), energetics cost of transport (ECOT) and oxygen costs of transport (O
COT) for each of the three shoe models at all three speeds
14 km/h 16 km/h 18 km/h
NS AB NP NS AB NP NS AB NP
Energetic cost (W/kg) 14.17 ±0.82 14.13 ±0.84 13.57 ±0.76 17.07 ±1.02 17.03 ±1.02 16.36 ±0.99 20.26 ±1.06 20.25 ±1.18 19.42 ±1.08
/kg/min) 41.97 ±2.39 41.87 ±2.45 40.24 ±2.19 50.30 ±2.91 50.19 ±2.92 48.27 ±2.87 59.62 ±3.08 59.57 ±3.40 57.26 ±3.10
ECOT (J/kg/m) 60.72 ±3.52 60.57 ±3.59 58.15 ±3.25 64.00 ±3.83 63.85 ±3.84 61.36 ±3.71 67.52 ±3.55 67.49 ±3.94 64.72 ±3.60
COT (mL O
/kg/km) 179.9 ±10.3 179.4 ±2.5 172.5 ±9.4 188.6 ±10.9 188.2 ±10.9 181.0 ±10.6 198.7 ±10.3 198.6 ±11.3 190.9 ±10.4
NS Nike Zoom Streak 6, AB adidas adizero Adios BOOST 2, NP Nike prototype
Values presented are mean ±SD
Energetic Cost of Running Shoes 1015
its substantially greater compliance rather than the greater
percent resilience. For context, the arch of the human foot
and Achilles tendon return 17 and 35 J of stored energy,
respectively, during running at 16.2 km/h . Other
ligaments and tendons of the leg store and return additional
energy [39,40]. Thus, regardless of the shoes worn, in
human running, the vast majority of the mechanical energy
storage and return occurs within our natural biological
structures. However, to operate the tendons as springs, the
muscles that connect tendons to bones must actively con-
tract, which consumes metabolic energy . In contrast,
running shoes with elastic midsoles and stiffening plates
may reduce rather than require the generation of muscular
How much of an improvement in running performance
would be predicted from a 4% reduction in energetic cost?
Hoogkamer et al.  established that percent changes in
the energetic cost of running due to altered shoe mass
translate to similar percent changes in 3000-m running
performance, when both are evaluated at the same running
velocity. But, as recently summarized by Hoogkamer et al.
, the energetic cost of overground running increases
curvilinearly with velocity, due in part to air resistance.
Such curvilinearity implies that a 4% average energetic
savings observed should translate to *3.4% improvement
in running velocity at marathon world record pace
(20.59 km/h) [3,34]. Consistent with that calculation, in
the two years leading up to her amazing world record in the
women’s marathon in 2003, directed training allowed
0 50 100 150 200
0 50 100 150 200
Fig. 5 Average vertical (F
; top) and anterior–posterior ground
reaction force traces (F
; bottom) in the three different shoe models
for runners with rearfoot strike pattern (n=8) (left) and midfoot or
forefoot strike pattern (n=10) (right) during the 16-km/h trials.
Force traces are normalized to body weight (BW). Initial impact and
peaks were greater for the rearfoot strikers in the NP shoes.
recordings for mid/forefoot strikers were similar in the three shoes.
NS Nike Zoom Streak 6, AB adidas adizero Adios BOOST 2, NP Nike
Table 2 While running in the NP shoe, the subjects generally ran with slightly greater peak vertical ground reaction forces, slower step
frequencies and longer contact times than in the control shoes
NS AB NP
14 km/h 2.88 ±0.19 2.89 ±0.20 2.92 ±0.20
16 km/h 2.98 ±0.19 3.00 ±0.19 3.00 ±0.17
18 km/h 3.11 ±0.18 3.14 ±0.18 3.13 ±0.18
Step frequency (Hz) * *
14 km/h 2.90 ±0.14 2.89 ±0.15 2.87 ±0.14
16 km/h 2.97 ±0.15 2.97 ±0.16 2.96 ±0.15
18 km/h 3.05 ±0.16 3.04 ±0.16 3.02 ±0.16
Contact time (ms) *
14 km/h 212 ±8 212 ±8 213 ±8
16 km/h 197 ±8 196 ±7 197 ±7
18 km/h 180 ±5 181 ±5 182 ±5
Peak vertical ground reaction forces (F
) are normalized to body weight (BW)
NS Nike Zoom Streak 6, AB adidas adizero Adios BOOST 2, NP Nike prototype
Values presented are mean ±SD
*Indicates signiﬁcantly different from NP shoes across running velocities
1016 W. Hoogkamer et al.
Paula Radcliffe to reduce her energetic cost of running at
16 km/h by 2.8% and marathon performance by 2.4% .
An acute 3.4% improvement in the marathon world record
would be historic. For example, it took nearly 29 years for
the men’s marathon record to be reduced by *3.4% to the
current 2:02:57, and not since 1952 has the men’s marathon
record been broken by more than 3.4% in one race.
Note that we empirically compared the shoes up to a
running velocity of 18 km/h, about 13% slower than the
average marathon world record velocity. It was challenging
to recruit 18 runners who could sustain 18 km/h below
lactate threshold and also ﬁt the available size US10 pro-
totypes. Therefore, we tested a range of velocities to
determine if any energy savings were dependent on running
velocity. Over the tested velocity range of 14–18 km/h, the
percent savings were constant. The energetic cost of run-
ning for elite marathon runners is likely lower than in our
high-caliber, sub-elite runners [43,44], and the energetic
cost of running may slowly increase over the duration of a
marathon , due to slow component increases in oxygen
uptake kinetics  and muscle damage , as compared
with the energy cost values we observed. How the 4%
savings we observed, interact with all these variables
remains to be determined.
In conclusion, the new running shoes described herein
provide 4% energetic savings. Our extrapolations suggest
that with these shoes the technology is in place to break the
2-h marathon barrier. Now, it is up to the athletes to make
Acknowledgements We thank the subjects for participating, Sewan
Kim for his help with analyzing the blood samples, Xu Cheng for
helping set up the mechanical testing, Joel Greenspan for his help
with the illustrations, and Max Donelan and Andrew Jones for helpful
feedback and comments regarding an earlier version of this
Compliance with Ethical Standards
Ethical approval The study was performed in accordance with the
ethical standards of the Declaration of Helsinki. Ethics approval was
obtained from the University of Colorado Institutional Review Board
Informed consent Informed consent was obtained from all individ-
ual participants included in the study.
Funding This study was supported by a contract from Nike, Inc. with
the University of Colorado, Boulder.
Conﬂict of interest Wouter Hoogkamer, Shalaya Kipp, and Jesse H.
Frank have no conﬂicts of interest relevant to the content of this
article. Emily M. Farina and Geng Luo are employees of Nike, Inc.
Rodger Kram is a paid consultant to Nike, Inc.
Open Access This article is distributed under the terms of the
Creative Commons Attribution 4.0 International License (http://
creativecommons.org/licenses/by/4.0/), which permits unrestricted
Table 3 Energetic costs and biomechanics variables for each of the three shoe models at all three speeds, separated by foot strike type
14 km/h 16 km/h 18 km/h
NS AB NP NS AB NP NS AB NP
Energetic cost (W/kg) rearfoot strike 14.21 ±0.91 14.17 ±0.81 13.54 ±0.82 17.09 ±0.96 17.01 ±0.98 16.25 ±0.95 20.40 ±1.27 20.44 ±1.41 19.43 ±1.31
Energetic cost (W/kg) mid/forefoot strike 14.13 ±0.79 14.10 ±0.90 13.59 ±0.75 17.05 ±1.12 17.04 ±1.11 16.45 ±1.06 20.15 ±0.92 20.10 ±1.01 19.40 ±0.93
(BW) rearfoot strike 2.81 ±0.16 2.82 ±0.16 2.85 ±0.16 2.93 ±0.13 2.95 ±0.12 2.97 ±0.12 3.05 ±0.12 3.09 ±0.14 3.09 ±0.13
(BW) mid/forefoot strike 2.93 ±0.21 2.94 ±0.24 2.98 ±0.24 3.02 ±0.23 3.04 ±0.23 3.03 ±0.21 3.15 ±0.23 3.17 ±0.21 3.17 ±0.21
Step frequency (Hz) rearfoot strike 2.86 ±0.14 2.85 ±0.13 2.84 ±0.14 2.93 ±0.13 2.92 ±0.13 2.89 ±0.13 3.00 ±0.13 2.99 ±0.13 2.96 ±0.12
Step frequency (Hz) mid/forefoot strike 2.93 ±0.15 2.93 ±0.16 2.90 ±0.16 3.02 ±0.16 3.01 ±0.18 3.01 ±0.16 3.09 ±0.18 3.08 ±0.18 3.07 ±0.17
Contact time (ms) rearfoot strike 218 ±3 218 ±5 220 ±2 203 ±5 201 ±5 202 ±4 184 ±3 185 ±4 186 ±3
Contact time (ms) mid/forefoot strike 207 ±8 208 ±8 208 ±7 192 ±8 193 ±7 193 ±7 177 ±5 178 ±5 178 ±4
NS Nike Zoom Streak 6, AB adidas adizero Adios BOOST 2, NP Nike prototype, F
vertical ground reaction force, BW body weight
Values presented are mean ±SD
Energetic Cost of Running Shoes 1017
use, distribution, and reproduction in any medium, provided you give
appropriate credit to the original author(s) and the source, provide a
link to the Creative Commons license, and indicate if changes were
1. Bascomb N. The perfect mile: three athletes, one goal, and less
than four minutes to achieve it. New York: Houghton Mifﬂin
2. Joyner MJ, Ruiz JR, Lucia A. The two-hour marathon: who and
when? J Appl Physiol. 2011;110:275–7.
3. Hoogkamer W, Kram R, Arellano CJ. How biomechanical
improvements in running economy could break the 2-hour
marathon barrier. Sports Med. 2017;47:1739–50.
4. Caesar E. Two hours: the quest to run the impossible marathon.
New York: Simon & Schuster; 2015.
5. Joyner MJ. Modeling: optimal marathon performance on the
basis of physiological factors. J Appl Physiol. 1991;70:683–7.
6. Di Prampero PE, Atchou G, Bru
¨ckner JC, et al. The energetics of
endurance running. Eur J Appl Physiol Occup Physiol.
7. Fletcher JR, Esau SP, MacIntosh BR. Economy of running:
beyond the measurement of oxygen uptake. J Appl Physiol.
8. Daniels J, Daniels N. Running economy of elite male and elite
female runners. Med Sci Sports Exerc. 1992;24:483–9.
9. Hoogkamer W, Kipp S, Spiering BA, et al. Altered running
economy directly translates to altered distance-running perfor-
mance. Med Sci Sports Exerc. 2016;48:2175–80.
10. Frederick EC, Daniels JT, Hayes JW. The effect of shoe weight
on the aerobic demands of running. In: Bachl N, Prokop L,
Suckert R, editors. Curr Top Sports Med Proc World Congr
Sports Med. Vienna: Urban and Schwarzenberg; 1984. p. 616–25.
11. Franz JR, Wierzbinski CM, Kram R. Metabolic cost of running
barefoot versus shod: is lighter better. Med Sci Sports Exerc.
12. Frederick EC, Clarke TE, Larsen JL, et al. The effects of shoe
cushioning on the oxygen demands of running. In: Nigg BM,
Kerr BA, editors. Biomechanical aspects of sports shoes and
playing surfaces. Calgary: The University of Calgary; 1983.
13. Tung KD, Franz JR, Kram R. A test of the metabolic cost of
cushioning hypothesis during unshod and shod running. Med Sci
Sports Exerc. 2014;46:324–9.
14. Kerdok AE, Biewener AA, McMahon TA, et al. Energetics and
mechanics of human running on surfaces of different stiffnesses.
J Appl Physiol. 2002;92:469–78.
15. McMahon TA, Valiant G, Frederick EC. Groucho running.
J Appl Physiol. 1987;62:2326–37.
16. Smith JA, McKerrow AD, Kohn TA. Metabolic cost of running is
greater on a treadmill with a stiffer running platform. J Sports Sci.
17. McMahon TA, Greene PR. Fast running tracks. Sci Am.
18. Shorten MR. The energetics of running and running shoes.
J Biomech. 1993;26:41–51.
19. Lejeune TM, Willems PA, Heglund NC. Mechanics and ener-
getics of human locomotion on sand. J Exp Biol.
20. Worobets JT, Wannop JW, Tomaras E, et al. Softer and more
resilient running shoe cushioning properties enhance running
economy. Footwear Sci. 2014;6:147–53.
21. Carrier DR, Heglund NC, Earls KD. Variable gearing during
locomotion in the human musculoskeletal system. Science.
22. Roy JP, Stefanyshyn DJ. Shoe midsole longitudinal bending
stiffness and running economy, joint energy, and EMG. Med Sci
Sports Exerc. 2006;38:562–9.
23. Willwacher S, Ko
¨nig M, Braunstein B, et al. The gearing function
of running shoe longitudinal bending stiffness. Gait Posture.
24. Oh K, Park S. The bending stiffness of shoes is beneﬁcial to
running energetics if it does not disturb the natural MTP joint
ﬂexion. J Biomech. 2017;53:127–35.
25. ASTM F1976-06. Standard test method for impact attenuation
properties of athletic shoes using an impact test. West Con-
shohocken: ASTM International; 2006.
26. Beck ON, Taboga P, Grabowski AM. Characterizing the
mechanical properties of running-speciﬁc prostheses. PLoS One.
27. McMahon TA, Cheng GC. The mechanics of running: how does
stiffness couple with speed? J Biomech. 1990;23(Suppl 1):65–78.
28. Heck H, Mader A, Hess G, et al. Justiﬁcation of the 4-mmol/l
lactate threshold. Int J Sports Med. 1985;6:117–30.
29. Kram R, Grifﬁn TM, Donelan JM, et al. Force treadmill for
measuring vertical and horizontal ground reaction forces. J Appl
30. Brockway JM. Derivation of formulae used to calculate energy
expenditure in man. Hum Nutr Clin Nutr. 1987;41:463–71.
31. Ferris DP, Liang K, Farley CT. Runners adjust leg stiffness for
their ﬁrst step on a new running surface. J Biomech.
32. Daniels JT. Daniels’ running formula. Champaign: Human
Kinetics; 2013. p. 276–7.
33. Taylor HL, Buskirk E, Henschel A. Maximal oxygen intake as an
objective measure of cardio-respiratory performance. J Appl
34. Tam E, Rossi H, Moia C, et al. Energetics of running in top-level
marathon runners from Kenya. Eur J Appl Physiol.
35. Fuller JT, Bellenger CR, Thewlis D, Tsiros MD, Buckley JD. The
effect of footwear on running performance and running economy
in distance runners. Sports Med. 2015;45:411–22.
36. Frederick EC, Howley ET, Powers SK. Lower O
running in air-cushion type shoes. Med Sci Sports Exerc.
37. Biewener AA. Scaling body support in mammals: limb posture
and muscle mechanics. Science. 1989;245:45–8.
38. Ker RF, Bennett MB, Bibby SR, et al. The spring in the arch of
the human foot. Nature. 1987;325:147–9.
39. Alexander RM, Bennet-Clark HC. Storage of elastic strain energy
in muscle and other tissues. Nature. 1977;265:114–7.
40. Magnusson SP, Narici MV, Maganaris CN, et al. Human tendon
behaviour and adaptation, in vivo. J Physiol. 2008;586:71–81.
41. Smith NP, Barclay JP, Loiselle DS. The efﬁciency of muscle
contraction. Prog Biophys Mol Biol. 2005;88:1–58.
42. Jones AM. The physiology of the world record holder for the
women’s marathon. Int J Sports Sci Coach. 2006;1:101–16.
43. Morgan DW, Bransford DR, Costill DL, et al. Variation in the
aerobic demand of running among trained and untrained subjects.
Med Sci Sports Exerc. 1995;27:404–9.
44. Lucia A, Esteve-Lanao J, Oliva
´n J, et al. Physiological charac-
teristics of the best Eritrean runners—exceptional running econ-
omy. Appl Physiol Nutr Metab. 2006;31:530–40.
45. Lacour JR, Bourdin M. Factors affecting the energy cost of level
running at submaximal speed. Eur J Appl Physiol.
1018 W. Hoogkamer et al.
46. Jones AM, Poole DC, Grassi B, et al. The slow component of
kinetics: mechanistic bases and practical applications. Med
Sci Sports Exerc. 2011;43:2046–62.
47. Hikida RS, Staron RS, Hagerman FC, et al. Muscle ﬁber necrosis
associated with human marathon runners. J Neurol Sci.
Energetic Cost of Running Shoes 1019
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