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# Modeling the Benefits of Cooperative Drafting: Is There an Optimal Strategy to Facilitate a Sub-2-Hour Marathon Performance?

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Background During a race, competing cyclists often cooperate by alternating between leading and drafting positions. This approach allows them to maximize velocity by using the energy saved while drafting, a technique to reduce the overall drag by exploiting the leader’s slipstream. We have argued that a similar cooperative drafting approach could benefit elite marathon runners in their quest for the sub-2-hour marathon. Objective Our aim was to model the effects of various cooperative drafting scenarios on marathon performance by applying the critical velocity concept for intermittent high-intensity running. Methods We used the physiological characteristics of the world’s most elite long-distance runners and mathematically simulated the depletion and recovery of their distance capacity when running above and below their critical velocity throughout a marathon. Results Our simulations showed that with four of the most elite runners in the world, a 2:00:48 (h:min:s) marathon is possible, a whopping 2 min faster than the current world record. We also explored the possibility of a sub-2-hour marathon using multiple runners with the physiological characteristics of Eliud Kipchoge, arguably the best marathon runner of our time. We found that a team of eight Kipchoge-like runners could break the sub-2-hour marathon barrier. Conclusion In the context of cooperative drafting, we show that the best team strategy for improving marathon performance time can be optimized using a mathematical model that is based on the physiological characteristics of each athlete.
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Vol.:(0123456789)
Sports Medicine (2018) 48:2859–2867
https://doi.org/10.1007/s40279-018-0991-4
ORIGINAL RESEARCH ARTICLE
Modeling theBenets ofCooperative Drafting: Is There anOptimal
Strategy toFacilitate aSub‑2‑Hour Marathon Performance?
WouterHoogkamer1 · KristineL.Snyder2· ChristopherJ.Arellano3
Published online: 8 October 2018
© Springer Nature Switzerland AG 2018
Abstract
Background During a race, competing cyclists often cooperate by alternating between leading and drafting positions. This
approach allows them to maximize velocity by using the energy saved while drafting, a technique to reduce the overall drag
by exploiting the leader’s slipstream. We have argued that a similar cooperative drafting approach could beneﬁt elite marathon
runners in their quest for the sub-2-hour marathon.
Objective Our aim was to model the eﬀects of various cooperative drafting scenarios on marathon performance by applying
the critical velocity concept for intermittent high-intensity running.
Methods We used the physiological characteristics of the world’s most elite long-distance runners and mathematically simu-
lated the depletion and recovery of their distance capacity when running above and below their critical velocity throughout
a marathon.
Results Our simulations showed that with four of the most elite runners in the world, a 2:00:48 (h:min:s) marathon is pos-
sible, a whopping 2min faster than the current world record. We also explored the possibility of a sub-2-hour marathon
using multiple runners with the physiological characteristics of Eliud Kipchoge, arguably the best marathon runner of our
time. We found that a team of eight Kipchoge-like runners could break the sub-2-hour marathon barrier.
Conclusion In the context of cooperative drafting, we show that the best team strategy for improving marathon performance
time can be optimized using a mathematical model that is based on the physiological characteristics of each athlete.
Key Points
We revisit the possibility of a sub-2-hour marathon by
incorporating the critical velocity concept to model the
eﬀects of intermittent high-intensity running on mara-
thon performance.
With a cooperative drafting approach, four of the most
elite runners in the world could run a 2:00:48 (h:min:s)
marathon, 2min faster than the current world record.
We explored the possibility of a sub-2-hour marathon
using more runners and our model simulations predict
that a team of eight runners with the physiological char-
acteristics of Eliud Kipchoge could break the sub-2-hour
marathon barrier.
Electronic supplementary material The online version of this
article (https ://doi.org/10.1007/s4027 9-018-0991-4) contains
supplementary material, which is available to authorized users.
* Wouter Hoogkamer
1 Locomotion Lab, Department ofIntegrative Physiology,
University ofColorado, Boulder, 354 UCB, Boulder,
CO80309-0354, USA
2 Department ofMathematics andStatistics, Swenson College
ofScience andEngineering, University ofMinnesota,
Duluth, 104 Solon Campus Center, Duluth, MN55812, USA
3 Department ofHealth andHuman Performance, University
ofHouston, 3875 Holman St, Houston, TX77204-6015,
USA
... Emerging technologies that enable the real-time monitoring of athletes in training and competition have fostered interest in methods to predict and optimize athlete performance. Predictive models for how much an athlete "has left in the tank" enable the investigation of pacing strategies (Behncke, 1997;Sundström et al., 2014;de Jong et al., 2017) and to dynamically adjust strategies to optimize the outcome of a competition (Hoogkamer et al., 2018). They can be described as a digital athlete, i.e., a computer-based model for enhancing training programming or strategy optimization. ...
... Since the first publication by Skiba et al. (2012), an updated form of W bal was introduced by Skiba et al. (2015) and another alternative form was proposed by Bartram et al. (2018). W bal models have been used to search for optimal drafting strategies in running (Hoogkamer et al., 2018) or to predict phases of perceived exhaustion during cycling exercise (Skiba et al., 2014). ...
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... Emerging technologies that enable the real-time monitoring of athletes in training and competition have fostered interest in methods to predict and optimize athlete performance. Predictive models for how much an athlete "has left in the tank" enable the investigation of pacing strategies (Behncke, 1997;Sundström et al., 2014;de Jong et al., 2017) and to dynamically adjust strategies to optimize the outcome of a competition (Hoogkamer et al., 2018). They can be described as a digital athlete, i.e., a computer-based model for enhancing training programming or strategy optimization. ...
... Since the first publication by Skiba et al. (2012), an updated form of W bal was introduced by Skiba et al. (2015) and another alternative form was proposed by Bartram et al. (2018). W bal models have been used to search for optimal drafting strategies in running (Hoogkamer et al., 2018) or to predict phases of perceived exhaustion during cycling exercise (Skiba et al., 2014). ...
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... Our data imply that an additional 10 km of optimal drafting could result in a \$1 min faster marathon time. This might be achieved with creative drafting strategies such as a rotating paceline, which is common in cycling (22). Furthermore, we also analyzed the female marathon world record holder, Brigid Kosgei (50 kg, 1.70 m, 2:14:04) and recreational marathoners running 3, 4, or 5 h [using mean body mass (65.6 kg) and height (1.75 m) for a 3-h (23)]. ...
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... INEOS 1:59 Challenge, Nike Breaking2 ), increasing research efforts were directed to minimize drag for a main runner in formations. Hoogkamer et al. (2018) used a reduced-order model to establish a sustainable velocity of 5.93 m s −1 using cooperative drafting in a four-runner team. Polidori et al. (2020) applied CFD to compute the drag and power savings of Kenenisa Bekele, while running the Berlin marathon and using cooperative drafting. ...
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... INEOS 1:59 Challenge, Nike Breaking2 ), increasing research efforts were directed to minimize drag for a main runner in formations. Hoogkamer et al. (2018) used a reduced-order model to establish a sustainable velocity of 5.93 m s −1 using cooperative drafting in a four-runner team. Polidori et al. (2020) applied CFD to compute the drag and power savings of Kenenisa Bekele, while running the Berlin marathon and using cooperative drafting. ...
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