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A graphical model for interval training
By Guy Thibault
ABSTRACT
The author proposes a model of the dynamic link between the components of an
interval training session. It has several practical applications on a
pedagogical level and for planning sessions and developing training programmes
in aerobic sports, including cross country, middle and long distance running, in
which maximal aerobic power, aerobic endurance and anaerobic capacity are key
performance factors.
Introduction
It has often been demonstrated that greater improvements in key performance
factors (anaerobic capacity, maximal aerobic power [MAP] and aerobic endurance^{1})
in most of the so called 'aerobic' sports such as cross country, middle and long
distance running can be achieved through training programmes that include
intermittent sessions. In fact, as shown in Table 1, when doing continuous
exercise, one cannot sustain intensity in the optimal development zone of these
key performance factors for very long. It is exactly because it enables an
athlete to perform a greater amount of work at a given elevated relative
intensity that interval training is frequently preferred to continuous training.
(^{1} Not
to be confused with VO_{2} max or maximal aerobic power; aerobic
endurance means the ability to maintain a given relative power output far a long
period of time or to maintain, for a given length of time, on elevated relative
power output.)
number of repetitions
number of sets
duration or distance of work intervals
intensity of work intervals
duration or distance of recovery periods between more intense work intervals and between sets
intensity of recovery periods
The number of
repetitions used is normally between 3 and 30, and sometimes more, and work
intervals may last from a few seconds to several minutes. It is actually the
sequencing of these components that determines both the physiological quality
called upon (and therefore improved or maintained) and the level of difficulty
of the session.
While the number of possible training prescriptions is endless, once certain
elements have been decided upon the options for the remaining element(s) are
limited, if the session is to be of a reasonable level of difficulty.
To our knowledge, there are no simple models that describe the link between
the components of an interval training session and its level of difficulty.
Thus, many coaches and practically all athletes find it difficult to add variety
to their training programmes, or conveniently assess or monitor a workout's
level of difficulty.
Objective
The objective of this article is to present an empirical interval training
model that has been developed to help coaches and serious athletes assess how
each element of such a training session can vary at a given level of difficulty,
and to make it easier to plan workouts and develop training plans.
The model
The proposed empirical interval training model is depicted graphically
in Figure 1. It relates the elements of an infinite number of interval training
sessions, all of which are of the same level of difficulty.
Each point on the six curves of the graph represents an interval training
session (darker points represent sessions in which work intervals are multiples
of 0:30 min:s). The duration of work intervals is represented on the xaxis, and
the number of repetitions on the yaxis. The six curves correspond to 5%
increments of relative intensity, from 85 to 110% of MAP.
As indicated by the table within the graph, we arbitrarily chose to base the
three other elements of the session (number of sets, duration of recovery
between work intervals and between sets) on the total number of repetitions in
the session. We simply attempted to avoid excessively long sessions and to limit
the maximum number of repetitions in each set to eight: if there are many
repetitions, recovery time is shorter, and the total number of repetitions to be
completed will be divided into a greater number of sets. It is assumed that
recovery between repetitions and sets occurs at less than 60% of MAP, an easy
intensity.
For example, the session represented by point A on the graph consists of 4
sets of 7 to 8 work intervals (for a total of 30 repetitions) at 85% of MAP,
with 1:00 min:s of active recovery between repetitions and 3:00 min:s between
sets. The session represented by point B on the graph consists of 1 set of 4
work intervals at 85% of MAP, with an active recovery of 5:00 min:s between
repetitions.
Features of the sessions
Some of the features of interval training sessions developed from this model
can be described as follows.
The nature of the fatigue experienced by the athlete during or after the workout may vary if the session consists of repetitions that are relatively numerous, long or intense. However, the general impression of fatigue will be essentially the same for every session. In fact, all sessions based on the model are perceived as difficult, however, athletes who are very motivated are generally capable of completing them. A one or two day rest period (active or inactive) is commonly required before another "difficult" session.
The content of any session based on the model makes that session useful in terms of developing the key performance factors for a great number of sports. In fact, its intensity will lie between 85 and 110% of MAP  a range that is considered to have an optimum effect on the development of aerobic endurance, MAP and anaerobic capacity, as well as of technical efficiency. Optimising highintensity training time may also prove to be an important aspect of the motor and psychological preparation of cross country, middle and long distance runners who must compete at power levels that are often higher than those they would automatically use during continuous training sessions.
The characteristics of the training sessions based on the model may vary widely: intensity, total number of repetitions (3 to 30). duration of each work interval and total duration of training (15 to 90 minutes, excluding warmup and cool down); as a result, the graphic representation of the model may lead the coach or the athlete to consider unexplored forms of interval training, thus enabling them to develop innovative workouts.
Sessions consisting of a large number of repetitions at a given intensity will result in a high total training volume at target intensity, while sessions consisting of fewer repetitions will teach the athlete to maintain the target intensity for a longer period of time before recovery. For example, the session represented by point B consists of a total of 24 minutes at 85% of MAP, while the session represented by point A consists of 45 minutes at the same intensity, or almost twice as much time. Therefore, it could be stated that sessions at a given intensity and consisting of a large number of repetitions emphasize quantity (the total volume of work and therefore the amount of high intensity physiological stimulation are high), while those with few repetitions emphasize quality (the athlete "learns" to maintain the high intensity for a longer period of time, as he or she will be required to do in competition).
Pedagogical applications of the model
When we presented this model to coaches of high performance
athletes, we noted that it facilitates the comprehension of the dynamic link
between the various components of an interval training session. As a matter of
fact, the model makes it possible to illustrate how to vary one or more of these
components to suit the objective, while maintaining a constant level of
difficulty. For example, one can use the model to calculate the number of
repetitions that must be done at an intensity equal to 95% of MAP, depending on
whether the work intervals are 1:00 min:s or 3:30 min:s in length (24 and 3
repetitions, respectively).
Also, it is easy to pinpoint the range in the duration of
work intervals for "appropriate" workouts at a given intensity. For example,
according to the model, it would not be productive to train at 85% of MAP during
work intervals of under 1:30 min:s (the number of repetitions would have to be
over 30), or over 6:30 min:s (the number of repetitions would be fewer than 3).
The model can also be used to determine the change that must
be made in the number of work intervals of a certain duration when intensity
changes. For example, the level of difficulty is exactly the same whether one
completes 4 repetitions of 2:00 min:s at 105% of MAP, 14 repetitions at 90% of
MAP or 21 repetitions at 85% of MAP.
Using the model to plan training sessions
Coaches and athletes can use the model to design as many
different sessions as they wish, at any intensity between 85 and 110% of MAP. As
indicated in the figure representing the model, for work intervals that are
multiples of 30 seconds alone, there are 35 different possible workouts at
intensities of 85,90,95, 100, 105 and 110% of MAP.
By scheduling part of one session based on the model after
part of another, sessions can also be developed in which the duration of
work intervals and intensity will vary from set to set. For example, based on
sessions A and B, the following training session could be developed: 2 sets of 7
or 8 work intervals of 1:30 min:s at 85% of MAP, with respectively 1 :00 and
3:00 min:s of recovery, between repetitions and sets, followed by a set of 2
work intervals of 6:00 min:s at 85% of MAP with 5:00 min:s of recovery between
repetitions. In this training session, the athlete will have completed half of
session A and half of session B.
The coach and the athlete can also use the model to control
the level of difficulty of training sessions. A session in which an athlete only
completes a fraction of the number of repetitions called for by the model has a
level of difficulty below the "maximum" level. For example, completing 5, 6, 7,
8 or 9 work intervals that can be repeated 10 times according to the model
corresponds to a 50, 60, 70, 80 or 90% level of difficulty, respectively.
However, this is only possible when having a decent measure of the actual power
output during work intervals. Such is the case when training on a track, knowing
that the O_{2} cost of running is approximately 3.5 times the velocity
in km/h. For example, running at a 4:00 min/km pace (15 km/h) corresponds to
52.5 mL O_{2}/kg/min (15 x 3.5), which is 85% of the MAP of a runner who
reaches his V0_{2} max at 17.6 km/h (61.8 mL O_{2}/kg/min).
It is interesting to note that when experienced athletes are
asked to complete a session based on the model without necessarily being told
the target intensity (only the "pattern" of the session, i.e. the number of
"work" intervals and the duration of recovery periods between repetitions and
between sets), they usually adopt the target intensity automatically. As a
matter of fact. those who perform the first work intervals of the session at an
intensity that is higher than required by the model will tend to reduce the
intensity as they realise that they will not be able to maintain the effort
until the end of the session. Conversely, those who start the workout at an
intensity that is too low will tend to adjust by increasing the intensity of
their work intervals when they realize that the session is not sufficiently
taxing. Therefore, during the session, the runner will end up training at an
average intensity that is very close to the intensity targeted by the session
pattern. Therefore, we only need to mention the session pattern to the runner,
without necessarily including the precise target intensity. This can be very
helpful, particularly in many sport activities, such as cross country running,
in which it is difficult to conveyor assess intensity of work.
For all practical purposes, the desired physiological demand
will likely be achieved by specifying only the session pattern because the
athlete will train at an intensity that will not differ markedly from the target
intensity.
It should be noted that target heart rate cannot be used as a
convenient way of conveying or monitoring intensity of work intervals. This is
clearly true in the case of all sessions at supramaximal intensity, i.e. above
100% of MAP. Even in sessions requiring effort at submaximal intensity (less
than 100% of MAP), heart rate does not reach a plateau quickly enough for this
parameter to really help the athlete achieve the desired intensity of work.
Using the model to plan the training programme
The model does not impose an approach to the
development of a longterm training programme, but it enables the coach or the
athlete to develop a personal approach. One can set a progression to follow
during a phase of the training programme by "numbering" the sessions in the
order in which they are to be completed. The possibilities are endless, but
Table 2 shows three progression modes that coaches (who were asked to complete
exercises on applications of the model) suggested on their own.
Thus, coaches or athletes can establish progressions based on
their individual approaches, while controlling the level of difficulty of
sessions throughout the entire season. Of course, a progression in the level of
difficulty of the sessions can also be set up, as previously described, by
having athletes complete a number of repetitions that is a fraction of the
"maximum" number of repetitions called for by the model.
Table 2
Validity and limitations of the model
Any approach to the planning of training is difficult to
validate because it requires, the rigorous monitoring of parameters that are
subject to fluctuation within a large sample group of athletes at various
levels. The model presented here is no exception.
Nevertheless, to assess its validity, we asked an athlete to
complete, in the laboratory, 31 sessions based on the model. He noted that while
the nature of the fatigue experienced during and after each session varied
according to the content of the workout, the general and subjective impression
of overall fatigue was essentially the same for every session.
Therefore, no systematic bias was identified. Whether the
session was short or long, whether it was completed at a high or very high
intensity, and whether the total number of repetitions was large or small, the
athlete always needed strong motivation in order to complete any of the 31
training sessions derived from the model. He stated that, in every case, the one
or two day period of active or inactive rest that he was given seemed necessary
in order for him to be able to complete the next "difficult" session. During the
three months of the experiment, the MAP of this athlete rose by 20 watts per
month (during which time he completed approximately ten sessions based on the
model, with one to three days of active rest between each session), increasing
from 380 to 440 watts, which represent equivalent VO_{2} max values of
60 and 68 mL O_{2}/kg/min, respectively.
Although a single case is not a statistically valid sample,
it is interesting to note that the athlete did not consider anyone type of
session to be more difficult than another.
Although the model has not actually been validated, comments
by coaches and athletes who use it indicate that it has useful pedagogical and
practical applications in terms of organising sessions and developing long term
training plans.
This version of the model cannot be used to assess the effect
of changing the duration of recovery between repetitions and sets. How ever,
experienced coaches know that if duration and intensity of recovery vary within
a reasonable range  for example, plus or minus 20%  the number of repetitions
that can be completed before a given level of fatigue is reached remains
relatively constant.
The model does not apply to training sessions that consist of
work intervals of under 30 seconds; this is a significant shortcoming, which may
be corrected in a subsequent version. As a matter of fact, it is well known that
shortinterval training has a marked effect on the development of MAP and
anaerobic capacity. Whether or not it is possible to generate "reasonable"
session content by developing projections of the model's formulas for
intensities above 110% of MAP and durations shorter than 30 seconds remains to
be tested.
Conclusion In conclusion, while empirically based and Dot
rigorously validated, the proposed model of the dynamic link between the
components of an interval training session see ills to have practical
applications on a pedagogical level and in terms of planning sessions and
developing training programmes in many sports, such as cross country, middle and
long distance running, in which MAP, aerobic endurance and anaerobic capacity
are key performance factors.
References
PERONNET, F.; THIBAULT, G.: Mathematical analysis of running performance and
world running records, J. Applied Physiol. (Modeling Methodology Forum), 67:
1989, pp 453465.
PERONNET, F.; THIBAULT, G.; lEDOUX, M.; BRISSON G.: Le marathon: equilibre
energetique, alimentation et entrainement du coureur sur route; 2nd edition,
Montreal: Decarie and Paris: Vi got, 1991,438pp.
TABATA, I. et al.: Effects of moderate intensity endurance and highintensity
interval training on anaerobic capacity and VO2 max, Med. Sci. Sports Exerc.,
28:1996, pp. 13271330.
THIBAULT, G.; MARION A.: A model of interval training prescription, (abstract),
Med. Sci. Sports Exerc., 30(5): 1998, pp. S108.
THIBAULT, G.: Un modele pratique de d'entrainement intermittent, Les Cahiers de
f'INSEp, vol. 33. la charge de travail en sport de haut niveau, Actes des
Entretiens de I'INSEP, 9, 10 et 11 octobre 2001, D. lEHENAFF et P. FlEURANCE
(sous la dir. de), INSEPPublications, 2002, p. 6174.
Guy Thibault, Ph.
D. is an exercise physiologist, a full time research advisor to the Secretariat
au Loisir et au Sport (Sport and Leisure Secretariat] of the Government of
Quebec, and a scientific advisor to the national training centres for several
individual sports in Canada. He is the former coach of Jacqueline Gareau (CAN),
winner of the Boston Marathon in 1980.
FROM: IAAF "NEW STUDIES IN ATHLETICS" 3:2003
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