Regulation of Pacing Strategy during Athletic
Competition
Jos J. de Koning1,2*, Carl Foster1,2, Arjan Bakkum1, Sil Kloppenburg1, Christian Thiel3, Trent Joseph2,
Jacob Cohen2, John P. Porcari2
1 Faculty of Human Movement Sciences, Research Institute MOVE, VU University Amsterdam, Amsterdam, The Netherlands, 2 Department of Exercise and Sport Science,
University of Wisconsin La Crosse, La Crosse, Wisconsin, United States of America, 3 Department of Sportmedicine, Goethe-Universita¨t, Frankfurt, Germany
Abstract
Background: Athletic competition has been a source of interest to the scientific community for many years, as a surrogate
of the limits of human ambulatory ability. One of the remarkable things about athletic competition is the observation that
some athletes suddenly reduce their pace in the mid-portion of the race and drop back from their competitors.
Alternatively, other athletes will perform great accelerations in mid-race (surges) or during the closing stages of the race (the
endspurt). This observation fits well with recent evidence that muscular power output is regulated in an anticipatory way,
designed to prevent unreasonably large homeostatic disturbances.
Principal Findings: Here we demonstrate that a simple index, the product of the momentary Rating of Perceived Exertion
(RPE) and the fraction of race distance remaining, the Hazard Score, defines the likelihood that athletes will change their
velocity during simulated competitions; and may effectively represent the language used to allow anticipatory regulation of
muscle power output.
Conclusions: These data support the concept that the muscular power output during high intensity exercise performance is
actively regulated in an anticipatory manner that accounts for both the momentary sensations the athlete is experiencing as
well as the relative amount of a competition to be completed.
Citation: de Koning JJ, Foster C, Bakkum A, Kloppenburg S, Thiel C, et al. (2011) Regulation of Pacing Strategy during Athletic Competition. PLoS ONE 6(1):
e15863. doi:10.1371/journal.pone.0015863
Editor: Alejandro Lucia, Universidad Europea de Madrid, Spain
Received August 19, 2010; Accepted November 25, 2010; Published January 20, 2011
Copyright:  2011 de Koning et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: These authors have no support or funding to report.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: j.dekoning@fbw.vu.nl
Introduction
The observation of changes in the pattern of velocity during
competition has led to interest in pacing strategy during athletic
competitions [1–6]. There have been at least three basic types of
pacing strategies identified (positive, negative and even pacing
strategy), which depend on the duration of the event and the
consequences of slowing with a loss in power output [2,7–9]. There
is some agreement that pacing strategy is organized in an
anticipatory way designed not only to optimize performance but
also to prevent unreasonably large homeostatic disturbances during
the exercise bout [5,6]. There is also some agreement that different
elements of the physiologic response to exercise are involved in
regulating pacing strategy. Just as the driver of a race car might
monitor different gauges during a race, and pay more attention to
one gauge during a short race and another during a longer race; it
appears that intramuscular substrate/metabolite changes [1,10–11]
are more likely to be determining of changes in muscular power
output during shorter (1–30 min) competitions, with body core (or
brain) temperature being more central during mid-duration (20–
120 min) events [12–17], and the availability of carbohydrate as an
oxidizable substrate being critical in longer (.90 min) events [18–
19]. While the effect of these different physiological regulators
doubtless overlaps, their net input appears to be integrated by the
conscious brain using the Rating of Perceived Exertion (RPE) [20–
23]. In a recently proposed model, Tucker (6) suggested that
changes in the homeostatic status, reflected by the momentary RPE,
allows alteration of pacing strategy (power output) in both an
anticipatory and responsive manner based on pre-exercise expec-
tations and peripheral feedback from different physiological sensors.
It has been shown that RPE increases in an approximately
linear manner as a function of the proportion of an event
completed [24–28], and has scalar characteristics when plotted
against percentage of the exercise task completed (time or
distance).
Together
these
data
suggest
that
the
athlete
is
continuously comparing how they feel at any moment in a
competition with how they expected to feel at that moment. If
their RPE is larger than expected for that point in the event, then
power output (e.g. running speed) will decrease, even if it means
giving up on the competition. If RPE is less than expected, then
power output will increase. The process of controlling muscular
power output via RPE apparently occurs continuously throughout
an exercise bout and almost certainly takes into account the
amount of distance remaining to be covered, as well as the
momentary value of RPE [6,23]. If an athlete approaches critical
levels of homeostatic disturbance (which can vary depending on
the length of a race; e.g. pH disturbances in a race of 2 min
duration, temperature increases in a race of 90 min duration, or
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limited availability of carbohydrate as an oxidizable substrate in a
race of 180 min duration) before nearing the end-point of a
competition, a progressive reduction in power output may take
place [8]. This protective mechanism is apparently quite effective
as it is very unusual to see an athlete continue until muscle
contractions entirely fail or to run to hyperthermic collapse.
Indeed,
perhaps
the
only
time
the
regulatory
mechanism
completely fails is in pathological conditions such as those typified
by neuromuscular diseases (e.g. myasthenia gravis, McArdle
disease), musculoskeletal disease (acute muscle or tendon ruptures),
cardiovascular disease (e.g. ventricular arrhythmia, myocardial
infarction triggered by exertion, exertion related congestive heart
failure, peripheral vascular disease) or respiratory disease (exer-
tional
bronchospasm).
Likewise,
as
the
distance
remaining
becomes sufficiently small, the athlete may choose to use their
remaining energetic reserves in an endspurt, regardless of the level
of homeostatic disturbance. Effectively the exerciser must compute
the hazard (e.g. danger of a competitively decisive competitive
collapse or health related collapse) if a certain pace is maintained
during the early or mid-portion part of an event versus the ability
to achieve their competitive goal.
On a conceptual level it can be hypothesized that an athlete
performing an event in a fast start manner compared to an even
paced race will have higher RPE values throughout the entire race
(Figure 1 A, E). The higher RPE will be the result of the sub-conscious
detection of, for instance, a higher heart rate [29], a faster depletion of
glycogen stores [30] and/or an earlier rise in core temperature [17]
(Figure 1B-D). The higher RPE in the fast start event will result in a
higher ‘hazard of catastrophic collapse’, compared to the ‘even’ or
‘normal’ paced trial. This ‘hazard’ could be seen as something that
could be dangerous for the physiological system. However, the
‘hazard’ must also be understood from the perspective of the amount
of the event remaining. Accordingly we conceptualized a measure for
the ‘hazard’ as the product of the momentary RPE with the fraction
of the remaining distance; the ‘Hazard Score’ (Figure 1F). Our
hypothesis is that the value of the Hazard Score is associated with the
ability to accelerate during the race or to the need to reduce the speed
to values at which the homeostatic disturbances stay within
acceptable limits (Figure 1G). We sought to determine whether
simple integration of the momentary RPE by the percentage of
distance remaining (e.g. Hazard Score) could adequately explain
within event variations in velocity by competitive athletes.
Figure 1. Relation between the Hazard Score and the change in pace. Schematic pace (A), heart rate (HRmax%) (B), muscle glycogen store
(C), core temperature (D), Rating of Perceived Exertion (RPE) (E) and Hazard Score (F) as a function of percent distance completed of a hypothetical
athlete performing a race with a fast start strategy and with an even strategy and the resulting relation between the Hazard Score and the change in
pace during the race (G).
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Methods
To accomplish this, we integrated the velocity and RPE data of
9 separate experiments, in which either cyclists or runners
completed competitive simulations in the laboratory, in events
that required from 4 to 60 minutes. The individual studies were
approved by the Institutional Review Board for the Protection of
Human Subjects of the University of Wisconsin-La Crosse, and
each
subject
provided
written
informed
consent
prior
to
participation. Some of the original data have previously been
published [24] but are analyzed with a different purpose here, and
some represent previously unpublished data. All of the individual
exercise studies involved closed loop time trials, with the subjects
instructed to finish the complete test in the smallest possible time.
Some of the studies were performed on a racing cycle with
computerized
measurement
of
power
output,
velocity
and
distance. Others were performed on a motor driven treadmill.
During these competitive simulations, all of the subjects were well-
trained sub-elite athletes who were task habituated to the test
event. In some of the events, the subjects were free to self pace
their effort, with the intent of minimizing the time to complete the
event. In others we imposed, for experimental reasons, either a
starting strategy that was more aggressive than normally chosen by
the athlete or which included a mid-race increase in pace, or
environmental challenges. In all studies, the Rating of Perceived
Exertion was measured using the Category Ratio version of the
RPE scale [31]. We integrated the mean value for each series of
experiments (10–12 subjects in each series) with reference to
predicting changes in velocity during the event in terms of the
‘Hazard Score’, calculated as the product of the momentary RPE
and the fraction of the event remaining at the same point. As a
general principle, measures of RPE were obtained at approxi-
mately 10% of full distance increments during each competitive
simulation.
Results
Serial changes in velocity, RPE and the computed Hazard
Score in all nine experiments are presented in Figure 2. The
growth of RPE in relation to the proportional distance matched
previous observations [6,24,26,28]. The value for the Hazard
Score reached peak values usually during the first half of each
event, with the exception of experiments during which mid-race
surges were performed. Since the computation of the Hazard
Score necessarily includes a zero value for percent of distance
remaining at the end of the race, the score necessarily decreases to
zero at the conclusion of the event.
When changes in velocity within each event were analyzed in
terms of the Hazard Score, there was, as hypothesized, a regular
relationship, with low values of the Hazard Score being associated
with increases in running or cycling velocity (a positive value for
change
in
pace),
and
high
values
being
associated
with
decelerations (a negative value for change in pace) (Figure 3).
There was a significant likelihood that the change in velocity
would be positive (acceleration) when the Hazard Score was less
than 1.5, negative when the Hazard Score was greater than 3 and
unchanged when the Hazard Score was between 1–3.
Discussion
In this analysis, we have demonstrated that the tendency of
athletes to change pace during competitive simulations is related
both to how they feel momentarily (RPE) and to how much of the
event remains. The calculation of a simple index combining these
two predictors (the Hazard Score), which represents the hazard of
Figure 2. Velolcity, RPE and the Hazard Score. Changes in velocity
(A), Rate of Perceived Exertion (RPE) (B) and the Hazard Score (C) in 9
competitive simulations in running or cycling events that required from
4 to 60 minutes.
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a competitively catastrophic collapse faced by the athlete, allows a
remarkably accurate prediction of subsequent behavior. Although
athletes rarely completely collapse during competition, there are
enough examples (e.g. the collapse of Englishman Jim Peters
during the Commonwealth Games marathon in 1954) to support
the concept that there is a ‘limit’ to which humans can push
themselves which can cause catastrophic collapse even in a highly
trained athlete. Although this type of analysis should be tested
during actual competition, the clarity of results presented here
suggests a very simple explanation of how the decision making
process regarding distribution of effort during competition (e.g.
very heavy exercise) is made.
Until experimental tests of this hypothesis can be made, it may
be instructive to evaluate data from high level competitions to
Figure 3. The acceleration/deceleration of athletes as function of the Hazard score.
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Figure 4. Velocity of the winner (bold) and the runners successively 5 places further back (e.g., 5th, 10th, 15th) from the Beijing
Olympic men’s 10 km race.
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provide a real-world test of this concept. In Figure 4 we present
publicly available (www.iaaf.org) data from the Beijing Olympic
men’s 10 km race, with the running velocity of the winner plotted
(bold) and runners successively 5 places further back noted. First, it
is evident that the overall pace slowed prior to 2 km (when we
would have predicted high hazard scores to emerge). Second, it is
evident that many of the runners dropped off the pace (e.g. ran
slower than the eventual winner) at approximately the mid-point
of the event and just at the moment the eventual winner began a
series of accelerations (e.g. increasing RPE and thus the hazard
score). Third, it is evident that during the endspurt, a period of low
hazard score because of the small distance remaining, the winner
simply ran faster than the remaining competitors. From this, it
appears that runners who drop off in the middle portions of the
race must have been confronted with an unacceptably large
hazard score (e.g homeostatic disturbance) and, faced with the
choice of slowing their pace or not finishing, chose to reduce their
pace. Similarly, the actions of the eventual winner beginning at
approximately mid race, at a time when the hazard score might be
expected to be declining, was to increase velocity, which would
have increased the hazard score of his competitors to the point
where they dropped out of contention for winning the race. A
limitation of the Olympic 10 km data is that we have no RPE or
physiological variables of the athletes during their race. However,
a typical example of a subject running multiple 10 km races on a
treadmill in the laboratory illustrates the line of our reasoning
(Figure 5). To mimic a real race the subject was forced to run at a
set velocity for the first 4 km, as if he was running ’in the pack’.
After 4 km he was free to vary his pace. Velocity, RPE and blood
lactate concentration were measured and consequently the
Hazard Score was computed. During his run on a ‘bad day’
(broken line), compared with a better performance (solid line), the
RPE and lactate were running high early in the race as was the
Hazard Score. The predictor of the slowdown at 4 km is the high
Hazard Score in the 3–4 km interval, which reflects larger
homeostatic disturbances.
The results of this study, in which the likelihood of changing
velocity during a competitive simulation are related to a simple
index of the momentary RPE and the percentage of the event
remaining suggest the fundamental strategy by which athletes
regulate their effort during competition. This suggests the
possibility of correlative studies where the magnitude of homeo-
static disturbances that contribute to the RPE can be understood
as they change during the course of the race.
Author Contributions
Conceived and designed the experiments: JJdK CF. Performed the
experiments: JJdK CF AB SK CT TJ JC JPP. Analyzed the data: JJdK CF
AB SK CT TJ JC JPP. Wrote the paper: JJdK CF AB SK.
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Regulation of pacing strategy during athletic competition.
de Koning, Jos J,Foster, Carl,Bakkum, Arjan,Kloppenburg, Sil,Thiel, Christian,Joseph, Trent,Cohen, Jacob,Porcari, John P