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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
Note. This article will be published in a forthcoming issue of the
International Journal of Sports Physiology and Performance. The
article appears here in its accepted, peer-reviewed form, as it was
provided by the submitting author. It has not been copyedited,
proofread, or formatted by the publisher.
Section: Brief Review
Article Title: The Effect of Periodisation and Training Intensity Distribution on Middle- and
Long-Distance Running Performance: A Systematic Review
Authors: Mark Kenneally1, Arturo Casado2, and Jordan Santos-Concejero1
Affiliations: 1Department of Physical Education and Sport. University of the Basque Country
UPV/EHU (SPAIN). 2Faculty of Health Sciences, Isabel I University (SPAIN).
Journal: International Journal of Sports Physiology and Performance
Acceptance Date: November 8, 2017
©2017 Human Kinetics, Inc.
DOI: https://doi.org/10.1123/ijspp.2017-0327
“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-
Distance Running Performance: A Systematic Review
Mark Kenneally1, Arturo Casado2, Jordan Santos-Concejero1
1Department of Physical Education and Sport. University of the Basque Country UPV/EHU
(SPAIN)
2Faculty of Health Sciences, Isabel I University (SPAIN)
Contact details:
Dr. Jordan Santos-Concejero, Department of Physical Education and Sport, Faculty of Physical
Activity and Sport Sciences, University of the Basque Country UPV/EHU. Portal de Lasarte
71; 01007, Vitoria-Gasteiz, SPAIN.
E-mail: jordan.santos@ehu.eus Tel: +34 945013538
ORCID: 0000-0001-9467-525X
Preferred running head: Training intensity distribution in distance runners
Word Count (excluding references): 4213
Abstract Word Count: 226
References: 35
Number of figures and tables: 6 (4 Figures and 2 Tables)
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
ABSTRACT
This review aimed to examine the current evidence for three primary training intensity
distribution types; 1) Pyramidal Training, 2) Polarised Training and 3) Threshold Training.
Where possible, we calculated training intensity zones relative to the goal race pace, rather than
physiological or subjective variables. We searched 3 electronic databases in May 2017
(PubMed, Scopus, and Web of Science) for original research articles. After analysing 493
resultant original articles, studies were included if they met the following criteria: a)
participants were middle- or long-distance runners; b) studies analysed training intensity
distribution in the form of observational reports, case studies or interventions; c) studies were
published in peer-reviewed journals and d) studies analysed training programs with a duration
of 4 weeks or longer. Sixteen studies met the inclusion criteria, which included 6 observational
reports, 3 case studies, 6 interventions and 1 review. According to the results of this analysis,
pyramidal and polarised training are more effective than threshold training, although the latest
is used by some of the best marathon runners in the world. Despite this apparent contradictory
findings, this review presents evidence for the organisation of training into zones based on a
percentage of goal race pace which allow for different periodisation types to be compatible.
This approach requires further development to assess whether specific percentages above and
below race pace are key to inducing optimal changes.
KEY WORDS: Polarised training, pyramidal training, threshold training, race pace, training
program
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
INTRODUCTION
Endurance training involves manipulation of intensity, duration and frequency of
training sessions1. The precise detail of this “manipulation”, however, remains an area of debate
across the literature. To further guide understanding of this area, different training intensity
zones have been described, determined by either physiological factors: i.e. lactate threshold
(LT), ventilatory thresholds (VT), percentage of the maximum oxygen uptake (%VO2max),
percentage of the maximum heart rate (%HR) or subjective factors: i.e. session goal or session
rate of perceived exertion (RPE-Borg Scale)2.
Three training intensity zones of endurance athletes are most commonly used in the
literature1,3, and are considered similar regardless of the method used to determine them.
However, up to seven can be also used to describe the Training Intensity Distribution (TID)4.
Both TID and periodisation of training volume and intensity are traditionally considered to be
important factors in the design of a training program for endurance running performance5.
There appears to be longstanding consensus in the literature regarding factors that limit
such performance, namely vVO2max35, VO2max6, LT6,7 and running economy8, and on how these
factors could be improved by using different training intensity procedures. However, a
disparate number of TIDs are employed in practice9. Three primary TIDs are recognised in this
review; (1) the traditional Pyramidal approach, in which decreasing volume of running is
performed in zones 1, 2 and 3 respectively. Typically32 this has been described as comprising
80% in Zone 1, with the remaining 20% split between zones 2 and 3, decreasing respectively;
(2) Polarised Training, in which relatively high volumes of training are performed in zone
1(~80%) and zone 3 (20%), with little or none in zone 232 and (3) Threshold Training, in which
higher volumes (>20%) of running are performed in zone 2 than other models32. Previous
research has identified pyramidal training as the primary TID employed by well-trained and
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
elite endurance athletes, noting that “some world-class athletes adopt a so-called ‘polarized’
TID during certain phases of the season ”3.
This observation has been supported by an observational review10 detailing the training
of international level distance runners, which notes the emphasis on relatively high volume-
low intensity in the training of athletes specialising in distances from 1500m to marathon.
However, a training manual published by the International Athletics Federation (IAAF) based
on the work of Renato Canova (the coach of some of the fastest Kenyan marathon runners in
recent times, including World Record holders) has demonstrated a tendency towards a
threshold-oriented TID11. Seiler & Tonnessen1 argue the case for an 80:20 distribution ratio
between high-intensity and low-intensity work based on observational reports describing the
training of elite endurance athletes. These authors recognise both pyramidal and polarised
models of TID as being most common in these athletes1.
It is against this apparently contradictory background that this review intends to
examine the current literature specifically for endurance running, and subsequently to analyse
the available data, where possible, by determining intensity zones relative to the goal race pace
in different distances, rather than physiological or subjective variables.
METHODS
Experimental Approach to the Problem
A literature search was conducted on May 6, 2017. The following databases were
searched: PubMed, Scopus, and Web of Science. Databases were searched from inception up
to May 2017, with no language limitation. Citations from scientific conferences were excluded.
Literature Search
In each database the title, abstract and keywords search fields were searched. The
following keywords, combined with Boolean operators (AND, OR) were used: “training
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
intensity distribution running”, “periodisation running”, “training intensity distribution
endurance”, “periodisation endurance”, “polarised training running”, “pyramidal training
running”, and “threshold training running”. No additional filters or search limitations were
used.
Inclusion Criteria
Studies were eligible for further analysis if the following inclusion criteria were met; a)
participants were middle- or long-distance runners (studies with triathletes or any other kind of
athletes were excluded); b) studies analysed training intensity distribution and/or periodisation
in the form of observational reports, case studies or interventions; c) studies were published in
peer-reviewed journals and d) studies analysed training programs with a duration of 4 weeks
or longer.
Two independent observers reviewed the studies and then individually decided whether
inclusion was appropriate. In the event of a disagreement, a third observer was consulted to
determine the inclusion of the study. A flow chart of the search strategy and study selection is
shown in Figure 1.
Quality assessment
Oxford’s level of evidence12 and the Physiotherapy Evidence Database (PEDro) scale13
were used by 2 independent observers in order to assess the methodological quality of the
articles included in the review. Oxford’s level of evidence ranges from 1a to 5, with 1a being
systematic reviews of high-quality randomised controlled trials (RCT) and 5 being expert
opinions. The PEDro scale consists of 11 different items related to scientific rigor. The items
include random allocation; concealment of allocation; comparability of groups at baseline;
blinding of subjects, researchers and assessors; analysis by intention to treat; and adequacy of
follow-up. Items 2-11 can be rated with 0 or 1, so the highest rate in the PEDro scale is 10, and
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
the lowest, 0. Zero points are awarded to a study that fails to satisfy any of the included items,
and 10 points to a study that satisfies all the included items.
STATISTICAL ANALYSIS
All values are expressed as mean ± standard deviation (SD). In studies with sufficient
data, TID determined by traditional physiological parameters was compared to a race-pace
based TID using a Cohen d14. Training zones for the race-pace approach were determined as
following; zone 1: volume performed at <95% of goal race pace, zone 2; volume performed
between 95% and 105% of goal race pace, and zone 3; volume performed at >105% of goal
race pace. The magnitude of differences, or effect size (ES) of this comparison was interpreted
as small (>0.2 and <0.6), moderate (>0.2 and <0.6), moderate (≥0.6 and <1.2), large (≥1.2 and
<2) and very large (≥2.0) according to the scale proposed by Hopkins et al.15
RESULTS
Studies Selected
The search strategy yielded 493 total citations as presented in Figure 1. After removing
163 duplicates and reviewing the resultant 330 full-text articles, 16 studies met the inclusion
criteria. Excluded studies had at least one of the following characteristics: participants were not
middle- or long-distance runners, intervention/observation period lasted less than 4 weeks. The
overall sample included 6 observational reports, 3 case studies and 6 interventions. 1 review
was also included (Table 1)
Level of Evidence and Quality of the Studies
Four of the 16 included studies had a level of evidence 1c (high-quality RCT). The 12
remaining studies had a level of evidence of 2c or less as participants were not randomly
allocated into the intervention or control groups. Also, mean score in the PEDro scale was 3.75
± 1.9, with values ranging from 1 to 6 (Table 2).
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
Characteristics of the Participants
Participants were characterised as recreational or high-level athletes, with delineation
defined by whether the athletes competed internationally. A summary of participants’
characteristics is presented in Table 1. The total number of participants was 215 (194 men and
21 women) with an age ranging from 17 to 51 years.
Evidence for a Pyramidal Training Intensity Distribution
Four interventional studies exist which support the use of a pyramidal TID; Esteve-
Lanao et al.16, Clemente-Suarez & Gonzalez-Rave17, Manzi et al.18, and Clemente-Suarez et
al.19. Similarly, 4 observational reports4,20,21,22 and 2 case studies23,24 confirm the use of
pyramidal training in elite and well-trained runners
Esteve-Lanao et al.16 examined the effect of decreasing volume of training performed
at threshold intensity on running performance in 12 male sub-elite endurance runners, while
maintaining equal volumes of high-intensity work between 2 groups (Threshold & Pyramidal
training groups; Figure 2). Running performance was assessed by a simulated 10.4-km XC race
assessed before and after the 5 month intervention period. The Pyramidal group displayed a
significantly better improvement in performance than the Threshold group. The TID in both
Threshold (Figure 2A) and Pyramidal groups (Figure 2B) was different from a race-pace based
TID (Figure 2; ES>2.0, very large effect). It should be noted that zone 3 can only be considered
a sub-set of zone 2 in this analysis as details of the zone 3 training are not provided but are
equal between groups.
Clemente-Suarez and Gonzalez-Rave17, examined the effect of applying a pyramidal
TID over a 4 week time period to 30 recreational athletes. One group (constant) maintained a
constant weekly training load in terms of volume and intensity, while another group had an
increasing proportion of higher intensity work, week by week over the 4 weeks. A final group
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
were free to train as they wished. Total training volume for the 4 weeks was recorded by time
(minutes). The constant group completed 1051 11 minutes, the increasing group completed
1105 1.3 minutes and the free group completed 1512 67.6 minutes. The stated goal of the
4 week time period was to develop “aerobic endurance”. No race distance or performance was
specified, rather the changes were measured via laboratory testing. No significant performance
differences existed between groups post-study, although the groups did exhibit different
physiological changes over the 4 weeks. Clemente-Suarez et al.19, using data from the
aforementioned study, found that the group with increasing intensity over the 4 weeks had a
significantly better running velocity at 8 mmol·L-1 at mid- and post-condition. No time-trial or
race performance data for the groups were provided so it was not possible to examine the TIDs
in this method.
Manzi et al.18 assessed the TID of 7 recreational marathon runners in the preparation
phase of a marathon training cycle. Interestingly, when their training (which was pyramidal in
nature according to their baseline physiological testing) was assessed against their eventual
race pace, it appeared to be a polarised type TID (Figure 3; ES>2.0, very large effect).
Robinson et al.20 analysed 13 national ranked male New Zealand distance runners’
training during the “build-up” phase of their season and identified 2 training zones according
to blood lactacte: above LT (4 mmol·L-1) or below LT. Training during this period was
described as 96% below LT and 4% above LT.
Tjelta and Enoksen21 described the training of a group of 4 top-level male Junior cross-
country (XC) runners over the course of a season. Five training zones based on HR and blood
lactate were used to describe the TID and training was divided into 3 seasons; Base, Track and
XC. The training in this study can be described as traditionally pyramidal in distribution, with
78%, 81%, and 78% of the training volume having been carried out in the low-intensity zone
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
1 in Base, Track and XC seasons, respectively. Race intensity for these athletes across the
whole season was zone 3 (10-km and 3-km), with some zone 4 (1500 m) races during the Track
season. Training intensification (training phases closer to competition) is characterised by an
increase in the volume just below, up to and over race pace (zones 3 and 4). In this study, when
TID was calculated according to race pace, the volume of training performed above race pace
was similar to other studies using either pyramidal or polarised methods4,24,18,27.
Enoksen et al.4 analysed 6 top international Norwegian marathon and track distance
runners’ training in a subsequent study. 7 training zones were identified and used the determine
TIDs. The marathon runners performed a relatively high proportion of their training at zone 2
(equivalent of marathon pace) and zone 4 (10-km pace) in their Base and Pre-competition phase
with nothing at zone 3 (half-marathon pace), and then in competition phase, nothing at zone 4
and an increase in the volume at zone 3, while maintaining a relatively high proportion at zone
2. The track runners (who competed over 5-km) completed relatively high volumes at zones 2
and 3 in all phases. However, the volume in zone 3 dropped in the competition phase and zone
5 (3-km and 5-km race pace) volume increased. They had minimal volume in zone 4 (10-km
pace) across all phases.
Esteve-Lanao et al.22 described the training of 8 regional and National class Spanish
runners, using 3 intensity zones; up to VT1, between VT1 and VT2, and above VT2, and
similarly described a pyramidal distribution (71% in zone 1, 21% in zone 2, 8% in zone 3).
Tjelta23 analysed the training of the 2012 European 1500m champion over 4 years, and
noted a pyramidal distribution over the time period, at all times of the season despite some
variation corresponding to the periodisation of the athletes training. Five intensity zones were
described relative to blood lactate, %HRmax, and intended physiological adaptation, and during
all phases of training the maintenance of a relatively high volume in zone 2 (threshold training)
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
was observed. This does reduce closer to competitive season but still constitutes a larger
proportion of training than zone 3, 4, or 5 at all time-points.
Similarly, the training of 9 times New York marathon winner Grete Waitz was also
reported as pyramidal at all time points across a 2 year time period24. The periodisation
identified 7 intensity zones and a decreasing volume of work done at increasing intensity levels
was observed.
Evidence for a Polarised Training Intensity Distribution
Two interventional studies exist which support the use of a polarised TID: Muñoz et
al.25, and Stoggl & Sperlich3. Both studies defined 3 intensity zones relative to physiological
characteristics. Similarly, 3 observational reports26,27,28 and 1 case study29 confirm the use of
polarised training in elite, well-trained and recreational athletes.
Muñoz et al.25 quantified the impact of TID on 10-km race performance in 30
recreational athletes. Two groups, emphasising polarised or threshold type training were
examined. Both groups improved over a 10-week intervention period; although the Polarised
group exhibited a better improvement over 10-km race distance than the Threshold group
(5.0% vs. 3.6%, non-significant). Both groups completed an 8-week standard training program
prior to the study, which was pyramidal in TID. In this study, both groups spent the same
absolute amount of time in zone 3 with the polarised group zone 1 (Figure 4A) and the threshold
group emphasising zone 2 (Figure 4B). The actual completed training of the polarised group
was not a truly polarised TID as the authors intended that this group would complete only 5.0%
of the training in Zone 2, rather than the 13.5% finally completed. The TID in both Polarised
(Figure 4A) and Threshold groups (Figure 4B) was different from a race-pace based TID
(Figure 4; ES>2.0, very large effect).
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
Stoggl & Sperlich3 examined 48 athletes, 21 of whom were national-level runners, in
their RCT comparing 4 different TIDs over a 9 week period. The TIDs were: High-Volume,
Threshold, High Intensity Interval Training and Polarised. Polarised training resulted in the
greatest improvement of the variables examined (VO2max, peak velocity and time to exhaustion
on a ramp protocol). A time-trial or race performance was not performed to allow analysis of
race-pace zones based on this.
Billat et al.26 compared top class male Portuguese and French marathon runners to their
“high-level” counterparts (as defined by a marathon time of 2:12). They described high-
volumes of polarised training. Their zones were defined, however, by marathon race pace. zone
1 was described as <marathon pace (MP), zone 2 = MP, zone 3 >MP, a definition not replicated
anywhere else in the literature and no specification of the tolerance around marathon pace for
each zone is provided. The same authors also described the training of Kenyan distance runners
(10-km specialists), and described 2 main TID types27: high-volume low-intensity and low-
volume high-intensity. In the group studied there were 13 males (6 high-intensity type and 7
low-intensity type) and 7 females (6 high-intensity type and 1 high-intensity type). The lower
volume athletes in this study tended to perform more of their training in zones 4 and 5 (4.3 and
5.0% respectively) than their high-volume counterparts, who only performed 1.4% of their
volume in zones 4 and 5 combined, with 14.4% in zone 3.
Stellingwerff28 described the training of 3 Canadian international marathon runners
over a 16 week period before a marathon race. The intensity zones were defined subjectively
by RPE as: zone 1 (easy to somewhat hard); zone 2 (“Threshold”); and zone 3 (very hard to
maximal). A polarised distribution was described in which 74%, 11% and 15% of training
sessions were performed in Zones 1, 2, and 3, respectively.
Ingham29 presented the case study of an international 1500m runner, who improved his
personal best from 3:38.9 to 3:32.4 over a 2 two year period. The analysis of his training
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
showed a reduction in training volume performed between 80-90% VO2max from 42% to 20%
and between 90-100% from 20 to 10%. At the same time, low-intensity training volume (<80%
VO2max increased from 20% to 55% and training volume at 100-130% VO2max increased from
7% to 10%, thus emphasising a shift towards a more polarised TID. Note that these numbers
are approximate as the information is only provided graphically in the article, and that 1500m
race falls at approximately 110% VO2max.
DISCUSSION
According to the results of this review, there is a clear dichotomous evidence base with
regard to TID in the literature. The overwhelming evidence describes 2 main strands: Pyramidal
and Polarised training.
Contemporary endurance training has developed, from a historical perspective from
coaches such as Arthur Lydiard, who used pyramidal TIDs to coach successful athletes10. The
more recent move towards Polarised type TIDs has emerged as scientific evaluation of
endurance performance has identified key determinants of endurance performance, and
methods by which to improve these determinants30. However, the precise nature of the
interaction of these determinants and the effect of that interaction remains elusive.
For example, although LT is recognised as one of the key determinants of endurance
performance7, threshold type training is considered to be more demanding than other TIDs (i.e.
pyramidal and polarised), potentially because of effects on the autonomic and endocrine
systems, or on the lactate/power profile25. When threshold training has been compared in this
regard in the literature, it consistently proves to be less effective in the studies available. Yet,
there is anecdotal evidence, at the very highest level, of the use of threshold training to great
effect in structuring world best marathon performance.
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
The coach of a number of world class Kenyan athletes has written a marathon training
manual for the International Athletics Federation (IAAF)11, and has made publicly available
the training programmes of his athletes. These programmes repeatedly show the use of high
volumes (i.e. differeing from the traditional 80:20 approach) of training in the threshold zone
(as defined by %VO2max, assuming 100% of VO2max corresponds to approximately 3000m
pace). The coach (Renato Canova) describes this training as specific race pace.
The periodisation employed, however, demonstrates an initial block of polarised
training, emphasising high and low intensity, leading into a specific preparatory phase, which
is threshold-oriented, thereby employing both of the main TIDs described at different phases
of training, according to the intended goal of the phase11. So in the specific example, marathon
pace lies in the threshold zone, so a relatively large volume of training is performed in this
physiological zone as the date of a specific race approaches. The volume of training performed
around race pace seems to be dictated by the distance of the impending race, with shorter races,
requiring faster paces, seeing less volume, and longer races requiring increasing volumes in
around race pace.
Thus, the dichotomous approach described above may be flawed in its inception. It may
prove more valuable in future studies to examine the precise physiological characteristics
associated with optimal race performance, and how these physiological characteristics change
with different TID approaches. Similarly, different approaches may prove valuable at different
phases and for approaching different races25. In this way, the training may be organised in the
early parts according to physiological characteristics such as HR or lactate profile, but as the
race date approaches, becomes more pragmatic and focuses on running at and around specific
race pace, regardless of what is happening to physiological measurables21,24. This represents a
way of incorporating the scientific principles which are fairly well established as being
important for specific race distance performance, while also being cognisant of the fact that the
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
literature is deficient in describing an optimal TID and periodisation strategy, based on good
evidence10.
It is well established that from races as short as 1500m, the aerobic system is the main
contributor of energy (85%)31 so the TIDs seen reflect that, as no matter what TID is examined
zone 1 is always the highest proportion. However, when comparing physiological-based
intensity zones and race pace-based intensity zones it seems from the data assessed in this
review that race pace may be a larger factor in the design of training programmes than
physiological variables. This may be a coaching flaw, but the interesting similarity in the TIDs
when analysed by a race pace based approach at least warrants some attention as these are data
from successful athletes. As discussed above, no optimal TID has been well established, and
similarly no optimal numbers for the physiological determinants (vVO2max, VO2max, Running
economy and LT) of middle and long distance running to predict performance exist2. The
interaction between these variables is the key to endurance running and it may be possible that
race pace based training provides the perfect stimulus for their concurrent development. As
already described above, training aimed at improving threshold seems to limit the development
of VO2max3. However, as Coyle & Krauenbuhl6 showed, large variation in laboratory endurance
performance is explained by the %VO2max which can be utilised at threshold so this limitation
may not be a hindrance to performance. The specificity of intention may be more important.
Race pace based zones may also reflect the fact that races in endurance running
competition are directly comparable because of the similarity of courses and the validity of
time comparison on different courses. Other endurance sports, such as road cycling, rowing or
XC skiing, which have been examined in the literature on TID32,33 do not share this same
capacity for direct competition to competition comparison of speed, because of the nature of
different courses characteristics (i.e. profile, altitude...). Training organised, therefore, based
on physiological characteristics for these sports is the norm. No study in these sports, to the
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
authors’ best knowledge, has reported a polarised TID based on zones that are externally
defined (i.e. power or speed).
This dichotomy between measuring and monitoring workload internally
(physiologically guided) vs. externally (e.g. pace guided) has been explored in 2 recent reviews:
Foster et al.34 and Mujika30. Foster et al.34 outline the practical difficulties of accurately
monitoring internal workload/physiological parameters, which they note are lessening.
Nonetheless such practical difficulties should not affect the development of theoretical
principles based on physiological measures (e.g. Running economy, VO2max and LT) should an
integrated approach to their concurrent development become evident.
Further studies looking at the behaviour of physiological characteristics such as HR
response, top speed and lactate profile at different phases of a season, and also how they
change, in the short and medium term in response to training are thus warranted. Comparison
of these measures to race performance, along with physiological profiling compared to
performance, may also allow better understanding of the interactions between physiological
characteristics, and the impact of these interactions on performance. This may allow for better
individualised planning and prescription of training, which is founded on evidence rather than
anecdote/tradition.
Conclusions
Current evidence describes pyramidal and polarised training as more effective than
threshold training, although the latest is used by some of the best marathon and distance runners
in the world. Despite the apparent contradictory evidence on TID and periodisation, an
approach based on race pace has been suggested in this review which may allow for different
TID types to be compatible. It is suggested that this may be unique to endurance running
because of the standardisation of race distances and courses. A race pace based TID recognises
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
the traditional high volume of low intensity training associated with endurance training, but
presents evidence (when analysed retrospectively) for the organisation of high intensity
training into zones based on a percentage of race pace, rather than physiological zones, which
appears to be relatively consistent across distances. A training session at a given percentage of
race pace for a longer event is naturally going to be slower, in absolute terms, than a session at
the same percentage of race pace for a middle distance event. Therefore these 2 sessions may
fall into completely different physiological zones yet may serve the same purpose from a
session intention perspective. The requirement to sustain a particular pace obviously also
differs by race distance, and in this way the volume of these sessions will also differ-longer
races requiring longer sessions etc, which may also affect analysis via a physiological-only
approach. Tjelta et al.21,24 recognise the relationship between race pace and physiology and
display race pace alongside physiological zones as a secondary zone target. This approach
requires further development to assess whether specific percentages above and below race pace
are key to inducing optimal changes, and whether, as has been questioned above, the potential
concurrent development of relevant physiological characteristics is indeed a factor. Such an
approach throws more questions about the nature of endurance running performance, but may
help to guide experimental enquiries into this performance along a slightly different path than
currently being tread.
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
17. Clemente-Suarez VJ, Gonzalez-Rave JM. Four weeks of training with different
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18. Manzi V, Bovanzi A, Castagna C, Sinibaldi Salimei P, Volterrani M, Iellamo F.
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
32. Seiler S. What is best practice for training intensity and duration distribution in
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
Figure 1. Flow chart of search strategy and selection of articles.
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
Figure 2. Training Intensity Distribution comparison between a physiological and a race pace
based approached in a Threshold periodisation (A) and a Pyramidal periodisation (B) groups.
Data from Esteve-Lanao et al. (2007).
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
Figure 3. Training Intensity Distribution comparison between a physiological and a race pace
based approached in a Pyramidal periodisation group. Training zones for the physiological
approach were described as following: Zone 1) <2 mmol·L-1 of lactate; Zone 2) between 2 and
4 mmol·L-1 of lactate; Zone 3) > 4mmol·L-1 of lactate. Data from Manzi et al. (2015).
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A
Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
Figure 4. Training Intensity Distribution comparison between a physiological and a race pace
based approach in a Polarised periodisation (A) and a Threshold periodisation (B) groups.
Training zones for the physiological approach were described as following: Zone 1)
<Ventilatory threhold (VT); Zone 2) between VT and the Respiratory Compensation Point
(RCP); Zone 3) > RCP. Data from Muñoz et al. (2014).
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International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
Table 1: Characteristics of the studies and the participants.
Participants
Study
Study
Number (M/F)
Age
Level
Main Outcome
Robinson et al. (1991)
13 (13/0)
26.1 ± 4.7
Elite
TID
Billat et al. (2001)
20 (10/10)
-
Elite
Physiology
Billat et al. (2003)
20 (13/7)
-
Elite
TID
Esteve-Lanao et al. (2005)
8 (8/0)
23 ± 2
Well-trained
TID
Esteve-Lanao et al. (2007)
20 (20/0)
27 ± 2
Well-trained
Race Performance
Tjelta & Enoksen (2010)
4 (4/0)
17.8 ± 1
Elite
TID & Race Performance
Enoksen et al. (2011)
6 (3/3)
Not
specified
Elite
TID & Race Performance
Stellingwerff (2012)
3 (3/0)
28.3 ± 2.3
Elite
TID
Ingham (2012)
1 (M)
26
Elite
TID & Race Performance
Tjelta (2013)
1 (M)
20-21
Elite
TID & Race Performance
Stoggl & Sperlich (2014)
21 (not specified)
31 ± 6
Well-trained
Physiology
Muñoz et al. (2014)
30 (not specified)
34 ± 9
Recreational
Race Performance
Tjelta et al. (2014)
1 (F)
25/26
Elite
TID
Clemente-Suarez & Gonzalez-Rave (2014)
30 (30/0)
38.7 ± 9.8
Well-trained
Aerobic Performance
Manzi et al. (2015)
7 (7/0)
36.5 ± 3.8
Recreational
TID & Race Performance
Clemente-Suarez et al. (2016)
30 (30/0)
38.7 ± 9.8
Recreational
Physiology & performance
Tjelta (2016)
56 (34/22)
Not
specified
Elite
TID
M/F = male/female; TID, training intensity distribution.
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“The Effect of Periodisation and Training Intensity Distribution on Middle- and Long-Distance Running Performance: A Systematic Review” by Kenneally M, Casado A, Santos-Concejero J
International Journal of Sports Physiology and Performance
© 2017 Human Kinetics, Inc.
Table 2: Physiotherapy Evidence Database (PEDro) ratings and Oxford evidence levels of the included studies.
PEDro ratings*
Study
1
2
3
4
5
6
7
8
9
10
11
Total
Evidence
level
Robinson et al. (1991)
No
0
0
0
0
0
0
1
0
0
0
1
4
Billat et al. (2001)
Yes
0
0
1
0
0
0
1
1
0
1
4
4
Billat et al. (2003)
Yes
0
0
1
0
0
0
1
1
1
1
5
4
Esteve-Lanao et al. (2007)
Yes
1
0
1
0
0
0
1
1
1
1
6
4
Tjelta & Enoksen (2010)
No
0
0
0
0
0
0
0
1
1
0
2
4
Enoksen et al. (2011)
No
0
0
1
0
0
0
0
0
0
0
1
4
Stellingwerff (2012)
No
0
0
1
0
0
0
0
0
1
1
3
4
Ingham (2012)
No
0
0
1
0
0
0
0
0
1
1
3
3b
Tjelta (2013)
No
0
0
0
0
0
0
0
1
1
0
2
4
Stoggl & Sperlich (2014)
Yes
1
0
1
0
0
0
1
1
1
1
6
1c
Muñoz et al. (2014)
Yes
1
0
1
0
0
0
1
1
1
1
6
1c
Tjelta et al. (2014)
No
0
0
0
0
0
0
0
1
1
0
2
4
Clemente-Suarez & Gonzalez-Rave (2014)
Yes
1
0
1
0
0
0
1
1
1
1
6
1c
Manzi et al. (2015)
Yes
0
0
1
0
0
0
1
1
1
1
5
2c
Clemente-Suarez et al. (2016)
Yes
1
0
1
0
0
0
1
1
1
1
6
1c
Tjelta (2016)
No
0
0
0
0
0
0
0
1
1
0
2
3a
Items in the PEDro scale: 1 = eligibility criteria were specified; 2 = subjects were randomly allocated to groups; 3 = allocation was concealed; 4 = the groups were similar at
baseline regarding the most important prognostic indicators; 5 = blinding of all subjects; 6 = blinding of all therapists who administered the therapy; 7 = blinding of all assessors
who measured at least 1 key outcome; 8 = measures of 1 key outcome were obtained from 85% of subjects initially allocated to groups; 9 = all subjects for whom outcome
measures were available received the treatment or control condition as allocated or, where this was not the case, data for at least 1 key outcome were analyzed by “intention to
treat”; 10 = the results of between-group statistical comparisons are reported for at least 1 key outcome; 11 = the study provides both point measures and measures of variability
for at least 1 key outcome.
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