ArticlePDF AvailableLiterature Review

Periodization Paradigms in the 21st Century: Evidence-Led or Tradition-Driven?

Authors:

Abstract and Figures

The planning and organization of athletic training have historically been much discussed and debated in the coaching and sports science literature. Various influential periodization theorists have devised, promoted, and substantiated particular training-planning models based on interpretation of the scientific evidence and individual beliefs and experiences. Superficially, these proposed planning models appear to differ substantially. However, at a deeper level, it can be suggested that such models share a deep-rooted cultural heritage underpinned by a common set of historically pervasive planning beliefs and assumptions. A concern with certain of these formative assumptions is that, although no longer scientifically justifiable, their shaping influence remains deeply embedded. In recent years substantial evidence has emerged demonstrating that training responses vary extensively, depending upon multiple underlying factors. Such findings challenge the appropriateness of applying generic methodologies, founded in overly simplistic rule-based decision making, to the planning problems posed by inherently complex biological systems. The purpose of this review is not to suggest a whole-scale rejection of periodization theories but to promote a refined awareness of their various strengths and weaknesses. Eminent periodization theorists-and their variously proposed periodization models-have contributed substantially to the evolution of training-planning practice. However, there is a logical line of reasoning suggesting an urgent need for periodization theories to be realigned with contemporary elite practice and modern scientific conceptual models. In concluding, it is recommended that increased emphasis be placed on the design and implementation of sensitive and responsive training systems that facilitate the guided emergence of customized context-specific training-planning solutions.
Content may be subject to copyright.
242
International Journal of Sports Physiology and Performance, 2012, 7, 242-250
© 2012 Human Kinetics, Inc.
The author is with the Institute of Coaching and Performance,
University of Central Lancashire, Preston, UK.
Periodization Theory:
Origins and Legacy
Frederick Winslow Taylor is not a name often associated
with athletic training planning. To recap some history:
Taylor was the academically inclined factory supervisor
who became the founding father of “scientic manage-
ment,” the rst application of scientic principles to the
production industry. Taylor’s landmark 1911 publication
The Principles of Scientic Management1 combined the
scientic knowledge of the day, his pioneering time-and-
motion studies, and management’s historical prejudice
toward workers (“All we want of them is to obey the
orders we give them”) to construct the rst great planning
paradigm of the modern era.
Taylor’s approach was typied by the belief that
there was “one best way” to organize, manage, and plan
production and that this “best” template could be uncov-
ered through observation and analysis. Industrialists of
the day readily embraced the intuitively appealing logic
of Taylor’s regimented paradigm. Henry Ford famously
adapted Taylor’s methodology to the automobile industry.
In sociopolitical contexts, Taylor’s inuence was simi-
larly widespread. Most notably his writings are cited as
shaping the planning philosophies of Lenin, with many
parallels between scientic management doctrine and
later Soviet 5-year templates.2
This historical appeal can be attributed to a number
of factors. First, when Taylor’s methodology was applied
to machine-shop environments, productivity improved.
Second, the rigorous dissection and empiricization of the
production problem resonated with a society awaken-
ing to the explanatory power of the scientic method.
Third, the reduction of the planning problem to a set of
formulaic “rules” and automatized solutions satised the
deep-seated human attraction to simplicity and explana-
tory closure, tempering our innate aversion to uncertainty
and ambiguity.3,4
The purpose of this diversion is solely to highlight
that this historically pervasive ideology exerted a pro-
found shaping inuence on planning practice across
Periodization Paradigms in the 21st Century:
Evidence-Led or Tradition-Driven?
John Kiely
The planning and organization of athletic training have historically been much discussed and debated in the
coaching and sports science literature. Various inuential periodization theorists have devised, promoted, and
substantiated particular training-planning models based on interpretation of the scientic evidence and individual
beliefs and experiences. Supercially, these proposed planning models appear to differ substantially. However,
at a deeper level, it can be suggested that such models share a deep-rooted cultural heritage underpinned by
a common set of historically pervasive planning beliefs and assumptions. A concern with certain of these
formative assumptions is that, although no longer scientically justiable, their shaping inuence remains
deeply embedded. In recent years substantial evidence has emerged demonstrating that training responses
vary extensively, depending upon multiple underlying factors. Such ndings challenge the appropriateness
of applying generic methodologies, founded in overly simplistic rule-based decision making, to the planning
problems posed by inherently complex biological systems. The purpose of this review is not to suggest a
whole-scale rejection of periodization theories but to promote a rened awareness of their various strengths
and weaknesses. Eminent periodization theorists—and their variously proposed periodization models—have
contributed substantially to the evolution of training-planning practice. However, there is a logical line of
reasoning suggesting an urgent need for periodization theories to be realigned with contemporary elite prac-
tice and modern scientic conceptual models. In concluding, it is recommended that increased emphasis be
placed on the design and implementation of sensitive and responsive training systems that facilitate the guided
emergence of customized context-specic training-planning solutions.
Keywords: emergent, biological complexity, athletic training, planning solutions
Periodization Paradigms 243
domains. In relation to sports preparation this legacy
is evident when comparing commonalities between
industrial planning models and formative periodization
concepts, both approaches seeking to control future out-
comes through the decomposition of the overall process
to a series of distinctly focused sequential units and
subsequent arrangement of these units in a mathemati-
cally predetermined order. Thus, for example, when the
historically inuential Matveyev collated training records
from the 1940s and 1950s it was perfectly logical that
he interpreted these averaged data through the lens of
pervading scientic conceptual models and applied his
conclusions as per the generalized format of the culturally
dominant planning paradigm.
Taylor’s methodology enhanced productivity within
simplistic engineering contexts; however, within broader
industrial and sociopolitical domains the inefciencies
inherent when such logic was extrapolated to more com-
plicated problems gradually became apparent. Today,
governmental, military, and social planners are aware of
the dangers presented by wide-sweeping assumptions
and a failure to recognize the confounding far-reaching
effects that minor, difcult to quantify, events may present
to long-term project planning.
The question explored in this review is whether peri-
odization philosophies have sufciently evolved beyond
this culturally pervasive planning heritage to adequately
assimilate advances in scientic insight and conceptual
understanding. Are periodization philosophies best under-
stood as “the methodical, scientic procedures to help
athletes achieve high levels of training and performance”
previously asserted5(p150) or as the legacy of an outdated
and scientically naïve world view?
What Is Periodization?
Contemporary discussion is hampered by the absence of
a universally accepted formal denition of periodization.
The term was originally employed to describe programs
taking the form of predetermined sequential chains of
specically focused training periods. However, today the
term is frequently indiscriminately employed to describe
any form of training plan, regardless of structure. The
archetypal periodized model, exemplied by the writings
of Matveyev,6 was typied by a progressive segmented
transition from high to low volume, and low to high
intensity, accompanied by a simultaneous reduction in
training variation as competitive peak approached. Since
the rst English translation of Matveyev’s inuential
1981 Fundamentals of Sports Training,6 various authors
have proposed novel periodized designs—for example,
nonlinear,7 block,8 fractal,9 and conjugate sequence.10
Although these models differ in terms of structure and
supporting rationale, there is an evident common set of
shared assumptions underpinning such approaches:
• Establishedtime framesexistfor thedevelopment
and retention of specic tness adaptations.7,11,12
• Varioustness attributes are best developed in a
sequential hierarchy (eg, strength before power,
endurance before speed).7,8,12
• Idealizedtrainingstructures,timeframes,andpro-
gression schemes can be generalized across athletic
subgroups.7,8,11–14
Inevitably arising from these premises are 2 implicit
assumptions:
• Biologicaladaptationtoagiventrainingintervention
follows a predictable course.
• Appropriatefuturetrainingcanbeadequatelyfore-
cast.
Scientific Support
for Periodization Principles
The science of periodization is a frequently encountered
phrase in exercise-science and coaching domains, with
many studies commonly cited as evidencing periodiza-
tion’s superiority as a training organizational means. For
example, in review of 15 studies of meso-cycle length
(7–24 wk), 13 studies concluded that periodized training
provided statistically superior performance improvements
when compared with constant-repetition programs.15 A
similar review concluded that periodized strength training
led to enhanced outcomes, in a variety of performance
measures, in comparison with nonperiodized models.16 A
meta-analysis comparing periodized and nonperiodized
strength-training programs concluded that periodized
structures were more effective for males and females,
individuals of varying training backgrounds, and a range
of age groups.17 A rare study failing to support superior-
ity of periodized regimes found no difference in efcacy
between undulating-periodized and nonperiodized groups
when volume and intensity were equalized over a short-
term period.18 Similarly, a study employing elderly
untrained participants concluded that xed-repetition
strength training was as effective in developing strength
as a periodized program.19
Thus, the preponderance of published literature sug-
gests that periodized structures provide enhanced benets
when compared with nonperiodized counterparts. Occa-
sional studies have failed to demonstrate such superiority.
However, such investigations have been typied by
• Subjectsoflowinitialtness
• Shorttimeframesofinvestigation
When we reflect on these conclusions, there
appears a subtle point of interpretation that is frequently
overlooked. In essence, due to complicating logisti-
cal constraints, experimental designs have compared
interventions regularly varying training parameters with
interventions with minimal, or no, variation. Accordingly,
what such studies have demonstrated is that variation is
a critical aspect of effective training, not that periodiza-
tion methodologies are an optimal means of providing
244 Kiely
variation . This may seem a semantic distinction. How-
ever, as already noted, periodized approaches are char-
acterized by a set of shared assumptions, and although
the evidence does support the need for regular training
variation, other core tenets of periodization philosophy
are neither supported nor refuted. Accordingly, a legiti-
mate concern is that habitual mention of the science of
periodization, and habitual uncritical acceptance of such
studies as proof of the superiority of periodized structures,
creates the illusion that periodized methodologies have
been empirically validated. This is not the case.
Managing Training Variation
The presented evidence suggests that variation is a neces-
sary component of effective training planning. Supporting
this perspective, other research suggests that elevated
training monotony—which may be broadly perceived
as a lack of variation20—leads to increased incidence of
overtraining syndromes,21 poor performance, and fre-
quency of banal infections.22 Conversely, reductions in
monotony have been associated with increased incidence
of personal-best performances,22 and monotony indexes
have been advocated as benecial training-regulation
tools in elite rowing23 and sprinting.24
A cursory glance at this literature suggests that varia-
tion is always “good,” and the repetitive application of a
unidirectional training stressor is always “bad.” However,
there are obvious logical qualiers to be overlaid on such
conclusions. First, if stimuli are excessively varied—if
the performer’s adaptive energy is too thinly dispersed
among multiple training targets—then it seems sensible
to assume that progress will be very slow, or nonexistent.
Second, periodic reduction in variation, facilitating a
concentrated focus on a narrow band of training targets,
may serve to induce rapid development of these priori-
tized attributes.
Two related inferences emerge:
• Trainingvariationis acriticalcomponentoflong-
term planning, but if adaptive energy is too widely
distributed, gains may be excessively diluted.
• Repetitiveapplicationofaunidimensionaltraining
stress may induce rapid improvements in a limited
range of targets, but if such concentrated focus is
unduly prolonged the athlete will be exposed to the
negative effects of unremitting monotony.
In Summary
Over a given time course, there is an apparent dynamic
balance to be negotiated between (a) the variation and
novelty required to offset diminishing training returns
arising from excess training habituation and (b) the
concentrated focus required to progress already well-
developed tness attributes. Although all periodized
methodologies provide formats for modulating focus
and variation, there is no direct evidence enabling us to
discern between the worths of these various schemes.
Each eminent periodization theorist has proposed,
based on personal perspective and interpretation of the
available evidence, a “best” design scheme for providing
variation over a given time frame. Although each theorist
has robustly outlined a rational argument supporting his
individual stance (while occasionally criticizing those
of his peers),8,25,26 it should be recognized that the evi-
dence offered in support of such templates is sparse and
circumstantial. The scarcity of evidence, coupled with
an eagerness to formulize a coherent planning approach,
may have facilitated the overinterpretation of a very
limited evidence base.
A Realignment
With Biological Reality
Given the logistical difculties inherent when investigat-
ing such a multidimensional phenomenon, it would be
unfair to criticize periodization theories based solely on a
lack of specic evidence. However, there is another, less
commonly considered, line of reasoning questioning the
conceptual logic underpinning periodization philosophy.
A unifying thread resonating throughout the peri-
odization literature is the quintessentially mechanistic
logic employed to derive formulaic solutions to training-
planning problems. Periodization philosophy hinges
on the presumption that biological adaptation to future
training is largely predictable and follows a determinable
pattern. A logical extension of such a rationalization is
that appropriate interventions can be adequately planned
in advance through a straightforward process of deduction
and prediction. Although this perspective is understand-
able in the light of historical conceptual frameworks,
contemporary insights do not support such simplistic
modeling of biological function.
Consider the ndings of the Heritage Family Study,
a large-population multicenter trial resulting in over 120
separate publications, investigating the role of genotype
in mediating exercise response. As an example, training-
induced changes to maximal oxygen uptake (VO2max)
were established to vary extensively in response to
identical exercise prescriptions. The average increase in
VO2max was 19%. However, 5% of participants had little
or no change in VO2max, and 5% had an increase of 40%
to >50%, despite all being subjected to a similar training
stimulus.27
Similar diversity of interindividual responses has
been reported after strength-focused interventions. For
example, when 585 young men and women strength-
trained for 12 weeks the average strength gain was 54%.
However, the magnitudes of individual gains were distrib-
uted between 0 and 250%, with changes to cross-sectional
area of targeted muscles ranging from –2% to 59%.28
Furthermore, evidence suggests that initial status, acute
response, and chronic development of trained attributes
Periodization Paradigms 245
are regulated by differing molecular pathways and gene
networks, implying that preexisting levels of strength
and/or endurance are not reliably indicative of how either
attribute will respond to future training.28,29
Other evidence supports extensive interindividual
variation among elite athletes. For example, an investi-
gation employing professional rugby players established
that a standard weight-training session resulted in a range
of differing hormonal responses among a homogeneous
group of players.30 In a related study, individual testos-
terone responses to 4 different weight-training protocols
were determined. Players then trained for 3 weeks using
the protocol that elicited either their maximum or their
minimum response before crossing over to the opposing
protocol for a subsequent 3 weeks. All players demon-
strated signicant gains in strength measures subsequent
to the protocol that elicited their maximum testosterone
response. In contrast, when they trained using the protocol
that induced their minimal response, either no change or a
signicant decline in strength measures resulted,31 hence
suggesting that had all players performed any arbitrarily
selected session some would have beneted substantially
whereas others executing the same protocol would have
made little or no gains.
As further complication, consider the variety of
factors demonstrated to affect release characteristics of
a single member of the family of interacting androgenic
hormones. Testosterone release has been noted to modu-
late in response to time of day, week, and month; cycles
of light and dark32,33; ratings of work satisfaction; motiva-
tional and assertiveness levels34; and training stress.35 In
addition, consider the inuence exerted by environmental
and lifestyle factors on biological responses. For example,
a wide range of imposed stressors—emotional, dietary,
social, sleep, academic—have been demonstrated to vari-
ously down-regulate the immune system, dampen adap-
tive response, and negatively affect motor coordination,
cognitive performance, mood, metabolism, and hormonal
health,36–40 consequently reducing performance41 and
elevating injury risk.42
Integration of these various evidence-led strands sug-
gests that the adaptive response to imposed interventions
emerges consequent to the complex interactions between
a broad spectrum of inherited predispositions and chroni-
cally and acutely varying biopsychosocial factors. This
includes, as suggested by the presented evidence,
• Training-loadingparameters
• Epigeneticpredispositions
• Legacyofpreviousstressexposures(includingtrain-
ing history)
• Transientbiological,psychological,andemotional
states
• Transientsocialandenvironmentalvariables
Byextension,wemayconcludethat
• Individualathletes willrespond differently,to one
another, to identical training sessions.
• Identicalsessions performedbyanindividualwill
always elicit a unique training response, for that
athlete, depending on transient functional states of
component subsystems.
• Group-based patterns and observations may be
highly misleading when generalized to individuals.
• Itishighlyimprobablethatthereare“best”patterns,
time frames, or progression and/or loading schemes
validly applicable across training contexts.
Mechanistic Modeling
of a Complex Reality
Critically, it should be acknowledged that many of our
historical training conceptions are founded on the prem-
ise that responses are substantially predictable, in other
words, that a known training input leads to an expected
adaptive output. This may be the case when considering
the “averaged” responses of a specic population to a
given intervention. However, as illustrated, individual
variation typically oscillates widely about such group-
based means, thereby suggesting a growing disconnect
between periodization ideologies that assume predictabil-
ity and stability of time frames and progression schemes
and the evidenced reality of biological complexity.43,44
The functioning of complex biological systems is
characterized by deeply entangled interdependencies
between component subsystems, by sensitive depen-
dence to initial conditions and subsequently introduced
“noise,” and by the inherently unpredictable chain of
consequences that may be initiated by any imposed
action. Applied perturbations may be absorbed, distrib-
uted, and dissipated, for little or no discernible change in
Figure 1 —RelationshipbetweenbaselinemaximalO2 uptake
(VO2max) and change (Delta) in VO2max in 633 subjects in the
Heritage Family Study. ©American Physiological Society.
Reproduced with permission from Skinner JS et al. J Appl
Physiol. 2001;90:1770–1776.
246 Kiely
system functioning. Alternatively, when system states are
delicately poised, nely balanced between stability and
dysfunction, then a single minor event, or the ripples of
seemingly innocuous interacting events, may reverberate
through system components, being progressively ampli-
ed until eventually manifesting as major behavioral
bifurcation.
As we cannot adequately assess the transient
functional states of component subsystems or unravel
the dynamically changing relationships between these
subsystems, a dening characteristic of biological sys-
tems is that future behavior is impossible to accurately
predict,44,45 and the consequences of future training
interventions, impossible to reliably project.
In the face of such complexity, the available training-
organizational studies must be recognized as inevitably
simplistic and capable of providing only the most rudi-
mentary of insights. Although empirical studies investi-
gating the effects of various training interventions are an
invaluable necessity—in terms of unraveling generalized
responses to specic interventions—the limitations inher-
ent when such isolated context-specic ndings are used
to substantiate elite planning philosophies should be
acknowledged. Eminent periodization theorists have con-
structed rational, logical arguments supporting personal
perspectives. However, when the task is multifaceted and
inherently complex, when discerning evidence is sparse,
when sensitive comparison between training structures
is not logistically feasible, then multiple coherent narra-
tives rationalizing any given set of observations can be
readily constructed.
As illustration, peer-reviewed publications have
been cited as demonstrating the superiority of block
periodization over more traditional designs.46 Consider:
Eleven days of high-intensity intervals are interjected into
regulartrainingpatterns.Result:Theexperimentalgroup
improves tested parameters more than the control group
continuing habituated training.47 Conclusion: Principles
ofblockperiodizationaresupported.Butissuchinter-
pretation a logical inference or a conclusion violating the
principle of parsimony, the fundamental scientic dictate
urging the acceptance of only the most frugal explanation
best tting factual observations? Is the most economical
rationalization of these results that (a) block periodiza-
tion represents a superior planning methodology or (b)
interjecting training novelty into habituated patterns may
lead to sudden performance improvements? Certainly,
(b) appears a more prudent conclusion. Furthermore, (b)
beingtruedoesnotentailthat(a)istrue.Regularvariation
and/or periods of high-intensity training are not unique
to any particular periodization philosophy and appear to
be a hallmark of elite programs regardless of the stated
methodology employed.
The presented evidence illustrates the extreme
context specicity arising when individual biological
systems, each with unique genetic predispositions and
“stress” histories, interact with unique training, psy-
chosocial, and environmental variables. Such extreme
context specicity highlights 2 logical fallacies evident
in the periodization literature:
• The assumption that averaged group-based trends
accurately reect likely individual responses
• The assumption that planning methodologies of
celebrated high achievers—by denition extreme
outliers—can be generalized and extrapolated to
other elite individuals
Emergent Solutions
to Complex Problems
Although the assumption of training generalizability is
alluring, in the light of biological complexity this allure is
revealed as illusory. More appropriately, the preparation
process may be conceptualized as a guided exploration
through an unknown and constantly shifting terrain.
Each “preparation terrain” presents a unique navigational
challenge, thus requiring a unique route map to optimally
guide toward program objectives. When moving through
unknown territory, having a map may provide the illusion
of certainty and control. However, while having a map
may be reassuring, previously used maps, inevitably of
differing terrains, are inherently inaccurate. A more reli-
able and direct means of arriving at your destination is
consistent triangulation between expectations, outcomes,
and objectives.
Such reasoning suggests a shift from the historical
ideal of preordained “best” training structures toward
a philosophy characterized by an adaptive readiness to
respond to emerging “information.” From this perspec-
tive, effective planning may be perceived as the imple-
mentation of sensitive and responsive learning systems
designed to enable the early detection of emerging threats
and opportunities.
How such systems are designed and implemented
sensibly depends on context-specic parameters such as
coaching preferences, experience of the athlete, logistical
limitations, and applicability of available technologies
and metrics. There are certain impositions constraining
the boundaries of the preparation plan: the competitive
schedule, performance needs analysis, and long- and
short-term goal setting. Sensibly, a broad framework
should be outlined and starting points, checkpoints, and
endpoints agreed on. However, within this sparse plan-
ning skeleton, training evolution may be most produc-
tively driven by emerging information continually con-
textualized against program constraints and objectives.
Many assessment and monitoring tools—both objec-
tive and subjective—are available and represented in
the literature, with many sure to follow as technological
innovation continues to drive improvements in capabili-
ties and accessibility.
The hallmarks of such information-driven learning
processes may sensibly include
Periodization Paradigms 247
• Development,andongoingrenement,oflong-term
sensitive monitoring and tracking systems
• Cultivation of performer-generated feedback and
feed-forward contribution
• Trendanalysisofcollateddata
• Criticalevaluationofprojectionsagainstoutcomes
• Regularreview,renement,andredirection
Critically, the quality of planning decision making
is founded on 2 cornerstones:
• A conceptual model—against which experiences,
observations, data, and decisions are contextual-
ized—that is optimally reective of the complex
nature of the preparation task
• Theeffectivemanagementofemerginginformation
This line of reasoning is not intended as an assault
on the historical value of periodization philosophy or
the substantial contributions made by eminent theorists.
However, in light of the converging evidence, I suggest
that periodization dictates are understood as hypothetical
tradition-driven assumptions rather than, as commonly
presented, evidence-led constructs. This does not imply
that plans are unimportant but that our perception of
what constitutes effective planning should be reevalu-
ated. Similarly, the presented rationale should not be
interpreted as suggesting a false dichotomy, an either/
or choice between preformed periodized structures and
more emergent information-driven training systems.
Ultimately, there is a dynamic tension to be negotiated
between structural rigidity and responsive adaptability.
The need for “exibility,” necessary deviation from the
chosen path, is often noted in the periodization literature
but is not discussed in any depth. This lack of attention,
in the midst of a heavy focus on predetermined training
structures, imparts the impression that deviation is some-
times necessary but generally unwelcome. Conversely,
the perspective materializing from this reframing sug-
gests that
• Deviation from the preplanned path is desirable,
should be actively sought, and the training manage-
ment system designed to facilitate, rather than sup-
press, consistent modulation.
• Acrucialcomponentofeffectivetrainingprocesses
is the systematic capture and review of pertinent data
that are then employed to drive future direction.
Many, perhaps most, elite coaches already integrate
aspects of this approach in their practical work. However,
there remains an evident dissonance between the reality
of elite practice, the reality of contemporary biological
models, and the theoretical positions habitually forwarded
in the periodization literature.
Moving Forward
Einstein once remarked that everything should be made
as simple as possible, but not simpler. Periodization
philosophies have reduced the complexity of the plan-
ning task through the assembly of supercially logical
Figure 2 — Sources of training decision-making “information.
248 Kiely
sets of assumptions, rules, and guidelines to construct
formulaic solutions to training-organizational tasks.
From this perspective, periodization templates offer a
useful service. However, this usefulness comes at a cost.
The downside emerges when such oversimplications
become enshrined in practice, elevated to the status of
unquestioned dogma, and are perceived as validated truths
rather than grossly generalized, frequently misleading
approximations. The result is a belief-based planning
paradigm gradually becoming ever more disconnected
from contemporary science and elite practice.
Arguments against such a reframing are immediately
obvious. Why depart from planning paradigms that have
clearly worked in the past? Such criticism is understand-
able but awed. Within performance environments a
commonly forwarded argument, opposing innovation, is
an appeal to the weight of history, to point to celebrated
champions who scaled great heights using conventionally
pervasive methodologies. However, despite its persuasive
power, such a rationale presents a damaging logical
inconsistency. An unbiased evaluation of the worth of
any training scheme requires that both successes and
“failures” be factored into analysis. As such, the high-
lighting of isolated high-achieving exemplars to conrm
the superiority of any planning scheme while neglecting
to consider those who conformed to a similar framework
yet “failed” is a fundamentally lopsided, albeit attractive,
argument. Furthermore, the training plan is but one facet
of the multidimensional “performance” phenomenon.
Did the planning methodology contribute to, or detract
from, the exceptional performances of an exceptional
performer? Would a different plan have led to greater
achievement, a longer career, less injury or illness? Our
inability to run counterfactual alternative-reality itera-
tions originating from common initial conditions renders
such arguments irresolvable. Instead, we must rely on
critical reection, informed by evidence, contextual-
ized against conceptual understanding, and cleared of
presumption. Ultimately, historical prevalence is not
supporting evidence.
Appeals to coaching experience are similarly
instinctively persuasive. However, in complex environ-
ments, an appreciation of the uniquely tangled web of
circumstances underpinning observable behaviors should
caution against the presumption that previously success-
ful strategies will prove similarly successful in the future.
The history of every complex planning domain—medical,
political, military, nancial—is replete with examples of
experts who assumed that previous success bestowed an
ability to forecast the future consequences of imposed
actions—a condence directly contravening a substantial
evidence base.3,4,45,49
A more legitimate concern relates to the lack of
perceptive, validated monitoring tools. It should be
acknowledged that no single assessment, or battery of
assessments, is likely to be universally applicable across
domains or groups of individuals (as previously noted50).
In the absence of ready-made solutions, the design of an
efcient training process may be considered an explor-
atory, slowly evolving, meticulously documented, single-
subject trial-and-error experiment.
An appreciation of both the philosophical origins
underpinning cultural planning convention and the nature
of biological complexity may caution against reliance on
generalized rule-based planning and automatized training
decision making—a reliance that ultimately constrains
our vision of available training strategies, impedes critical
thinking, and suppresses coaching creativity.
References
1. Taylor FW. The Principles of Scientic Management. New
York,NY:HarperandBrothers;1911.
2. Hindle T. Guide to Management Ideas and Gurus. London,
UK:ProleBooks;2008.
3. Tetlock P. Expert Political Judgment: How Good Is It?
How Can We Know?Princeton,NJ:PrincetonUniversity
Press; 2005.
Table 1 Sample Information Capture and
Tracking Options
Quantifying training
stress Sample metrics
Pretraining readiness Perceived readiness rating
Objective readiness measure
(using habituated exercise track-
ing)
Psychomotor speed
Heart-rate variability
In-training variables Empirical descriptors (load,
sets, reps, recoveries, etc)
Intensity rating (rating of per-
ceived exertion per effort, set, or
session)
Technical execution (quality
rating)
Assessing accumulative
stress
Recovery-StressQuestionnaire
for Athletes
Prole of Mood State
Recovery-cue
Daily Analysis of Life Demands
for Athletes48
Heart-rate variability
Monotony (weekly average
load/SD)
Strain (mean weekly load/
monotony)
Residualmuscle-fatiguerating
Training load (rating of per-
ceived exertion × training time)
TotalQualityRecovery
CategoryRatioPainScale
Periodization Paradigms 249
4. Gilovich T, Grifn D. Introduction—heuristics and biases:
then and now. In: Gilovich T, Grifn D, Kahneman D, eds.
Heuristics and Biases: The Psychology of Intuitive Judge-
ment. New York: Cambridge University Press; 2002:1–18.
5. BompaTO.Periodization Training: Theory and Methodol-
ogy. 4th ed. Champaign, IL: Human Kinetics; 1999.
6. Matveyev LP. Fundamentals of Sport Training. Moscow:
Progress Publishers; 1981.
7. BrownLE.Nonlinearversuslinearperiodizationmodels.
Nat Strength Cond Assoc. 2001;23(1):42–44.
8. Issurin VB. New horizons for the methodology and
physiology of training periodization. Sports Med.
2010;40(3):189–206. PubMed doi:10.2165/11319770-
000000000-00000
9. BrownLE,Greenwood M.Periodization essentialsand
innovations in resistance training protocols. Strength Cond
J. 2005;27(4):80–85.
10. Siff MC, Verkhoshansky YV. Supertraining. 4th ed.
Denver, CO: Supertraining International. 1999.
11. Viru A. Adaptation in Sports Training.BocaRaton,FL:
CRCPress;1995.
12. Zatsiorsky VM. Science and Practice of Strength Training.
Champaign, IL: Human Kinetics; 1995.
13. Verchoshansky V. Organisation of the training process.
New Stud Athl. 1998;13(3)21–31.
14. Tschiene P. The Priority of the Biological Aspect in the
“Theory of Training. Adelaide, Australia: South Austra-
lian Sports Institute; 1992.
15. StoneMH,O’BryantHS,SchillingBK,etal.Periodiza-
tion part 2: effects of manipulating volume and intensity.
Strength Cond J. 1999;21(3):54–60.
16. GrahamJ.Periodization:researchandanexampleapplica-
tion. Strength Cond J. 2002;24(6):62–70.
17. RheaMR,AldermanBL.Ameta-analysis ofperiodized
versus nonperiodized strength and power training pro-
grams. Res Q Exerc Sport. 2004;75(4):413–422. PubMed
18. BakerD,WilsonG,CarlyonR.Periodization:theeffecton
strength of manipulating volume and intensity. J Strength
Cond Res. 1994;8(4):235–242.
19. DeBeliso M,Harris C,Spitzer-Gibson T,AdamsKJ.A
comparison of periodised and xed repetition training
protocol on strength in older adults. J Sci Med Sport.
2005;8(2):190–199. PubMed doi:10.1016/S1440-
2440(05)80010-6
20. Foster C. Monitoring training in athletes with refer-
ence to overtraining syndrome. Med Sci Sports Exerc.
1998;30:1164–1168. PubMed doi:10.1097/00005768-
199807000-00023
21. Smith DJ. A frameworkfor understanding the train-
ing process leading to elite performance. Sports Med.
2003;33:1103–1126. PubMed doi:10.2165/00007256-
200333150-00003
22. Kellmann M, ed. Enhancing Recovery: Preventing Under-
performance in Athletes. Champaign, IL: Human Kinetics;
2002.
23. Suzuki S, Sato T, Takahasi Y. Diagnosis of training pro-
gramforaJapaneserowerbyusingtheindexofmonotony.
Can J Appl Physiol. 2003;28(Suppl):105–106.
24. Suzuki S, Sato T, Maeda A, Takahasi Y. Program design
based on a mathematical model using rating of perceived
exertion for an elite Japanese sprinter: a case study. J
Strength Cond Res. 2006;20(1):36–42. PubMed
25. Verhoshansky Y. The end of ‘periodization’ in the
training of high-performance sport. Mod Athl Coach.
1999;37(2):14–18.
26. Tschiene P. A necessary direction in training: the inte-
gration of biological adaptation in the training program.
Coach Sport Sci J. 1995;1:2–14.
27. SkinnerJS,JaskólskiA,KrasnoffJ,etal.Age,sex,race,
initialtness, andresponseto training:theHERITAGE
Family Study. J Appl Physiol. 2001;90(5):1770–1776.
PubMed
28. Hubal MJ, Gordish-Dressman H, Thompson PD, et al.
Variability in muscle size and strength gain after unilateral
resistance training. Med Sci Sports Exerc. 2005;37:964–
972. PubMed doi:10.1097/00005768-200505001-00881
29. Timmons JA.Variability in training-induced skeletal
muscle adaptation. J Appl Physiol. 2011;110(3):846–853.
30. Beavan CM, Gill ND, Cook CJ. Salivary testosterone
and cortisol responses in professional rugby players after
four resistance exercise protocols. J Strength Cond Res.
2008;22(2):426–431.
31. BeavanCM,CookCJ,GillND.Signicantstrengthgains
observed in rugby players after specic resistance exer-
cise protocols based on individual salivary testosterone
responses. J Strength Cond Res. 2008;22(2):419–425.
32. Bird SP,Tarpenning KM. Inuence of circadian time
structure on acute hormonal responses to a single bout of
heavy-resistance exercise in weight-trained men. Chrono-
biol Int. 2004;21(1):131–146.
33. Hirschenhauser K, Frigerio D, Grammer K, Magnusson
MS. Monthly patterns of testosterone and behaviour in
prospective fathers. Horm Behav. 2002;42(2):172–181.
34. Schultheiss OC, Rohde W.Implicit power motivation
predicts men’s testosterone changes and implicit learning
in a contest situation. Horm Behav. 2002;41(2):195–202.
35. FilaireE,LacG,PequignotJ.Biological,hormonal,and
psychological parameters in professional soccer players
throughout a competitive season. Percept Mot Skills.
2003;97:1061–1072.
36. RogersNL,SzubaMP,StaabJP,etal.Neuroimmunologic
aspects of sleep and sleep loss. Semin Clin Neuropsychia-
try. 2001;6(4):295–307.
37. Aubert A. Psychosocial stress, emotions and cyto-
kine-related disorders. Recent Pat Inflamm Allergy
Drug Discov. 2008;2(2):139–148. PubMed
doi:10.2174/187221308784543647
38. Stranahan AM, Khalil D, Gould E. Social isolation delays
the positive effects of running on adult neurogenesis. Nat
Neurosci. 2006;9:526–533. PubMed doi:10.1038/nn1668
39. SavtchoukI,LiuSJ.RemodelingofsynapticAMPArecep-
tor subtype alters the probability and pattern of action
potential ring. J Neurosci. 2011;31(2):501–511. PubMed
doi:10.1523/JNEUROSCI.2608-10.2011
40. CarlDL,TyreeB,StrasserS.Effectofenvironmentand
training on mood states of competitive swimmers. Med
Sci Sports Exerc. 2001;33(5):Suppl abst 1252.
250 Kiely
41. Paulus MP, Potterat EG, Taylor MK, et al. A neurosci-
ence approach to optimizing brain resources for human
performance in extreme environments. Neurosci Biobehav
Rev. 2009;33(7):1080–1088. PubMed doi:10.1016/j.neu-
biorev.2009.05.003
42.Kelman BB. Occupational hazards in female ballet
dancers: advocate for a forgotten population. AAOHN J.
2000;48(9):430–434.
43. Glass L. Review article: synchronization and rhythmic
processes in physiology. Nature. 2001;410:277–284.
PubMed doi:10.1038/35065745
44. Van Regenmortel MHV. The rational design of bio-
logical complexity: a deceptive metaphor. Proteomics.
2007;7:965–975. PubMed doi:10.1002/pmic.200600407
45. Gell-Mann M. The simple and the complex. In: Alberts
DS,CzerwinskiTJ,eds.Complexity, Global Politics, and
National Security. Washington, DC: National Defense
University; 1997:2–18.
46. Issurin V. New horizons for the methodology and physi-
ology of training periodization: block periodization: new
horizon or a false dawn? Sports Med. 2010;40(9):805–807.
doi:10.2165/11535120-000000000-00000
47. Breil FA,WeberSN, Koller S, et al. Block training
periodization in alpine skiing: effects of 11-day HIT
on VO2max and performance. Eur J Appl Physiol.
2010;109(6):1077–1086. PubMed doi:10.1007/s00421-
010-1455-1
48. KielyJ.Planningforphysicalperformance:theindividual
perspective. planning, periodization, prediction; and why
thefutureain’twhatitusedtobe!In:CollinsD,Button
A,RichardsH,eds.Performance Psychology for Physi-
cal Environments: A Practitioner’s Guide. Oxford, UK:
Elsevier; 2011:139–160.
49. PatelVL,KaufmanDR.Conceptualandproceduralerrors
in medical decision-making. In: Proceedings of the Cogni-
tive Society Conference. Erlbaum;2000.
50. Borresen J, Lambert MI. The quantication of train-
ing load, the training response and the effect on per-
formance. Sports Med. 2009;39(9):779–795. PubMed
doi:10.2165/11317780-000000000-00000
... Whilst athlete response measures aim to quantify the response to a range of factors, many of which are relatively uncontrollable in team sport settings (e.g., playing and travel schedule, social influences), practitioners also control many elements which affect athlete responses. Indeed, it has been suggested that more emphasis should be placed on the design and implementation of sensitive and responsive training systems, in order to optimize individualization and develop context-specific training-planning solutions [10]. This requires practitioners to respond to emerging information [10], such as athlete response measures assessed regularly throughout the season [12]. ...
... This process involves identifying measurable components and their role within the training process, thereby allowing practitioners to better understand what to measure and why these components may be important [12]. This approach leads to an improved understanding that reflects the challenging nature of the environment, and these conceptual frameworks can act as a reference operational guide in practical settings [12], against which experience, observations, data and decisions can be contextualized [10]. Therefore, the aim of this work is to determine associations between short-(i.e., 3-day) and medium-term (i.e., 10-day) cumulative training load, short-and medium-term travel demands, recovery days, and individual factors (e.g., fatigue, soreness, age) with AROMs and CMJ measures over the course of a professional basketball season. ...
... However, this is not an exhaustive monitoring battery and practitioners should consider what context-specific measures may best inform training periodization for their environment. Ultimately, by enhancing our understanding of the relationships between external load (e.g., training load and travel), recovery, training effects and sports performance outcomes, we support the development of sensitive and responsive training systems [10] and inform best-practice models for athlete care and performance in professional basketball [1]. ...
Article
Full-text available
This study examined associations between cumulative training load, travel demands and recovery days with athlete-reported outcome measures (AROMs) and countermovement jump (CMJ) performance in professional basketball. Retrospective analysis was performed on data collected from 23 players (mean±SD: age = 24.7±2.5 years, height = 198.3±7.6 cm, body mass = 98.1±9.0 kg, wingspan = 206.8±8.4 cm) from 2018–2020 in the National Basketball Association G-League. Linear mixed models were used to describe variation in AROMs and CMJ data in relation to cumulative training load (previous 3- and 10-days), hours travelled (previous 3- and 10-day), days away from the team’s home city, recovery days (i.e., no travel/minimal on-court activity) and individual factors (e.g., age, fatigue, soreness). Cumulative 3-day training load had negative associations with fatigue, soreness, and sleep, while increased recovery days were associated with improved soreness scores. Increases in hours travelled and days spent away from home over 10 days were associated with increased sleep quality and duration. Cumulative training load over 3 and 10 days, hours travelled and days away from home city were all associated with changes in CMJ performance during the eccentric phase. The interaction of on-court and travel related stressors combined with individual factors is complex, meaning that multiple athletes response measures are needed to understand fatigue and recovery cycles. Our findings support the utility of the response measures presented (i.e., CMJ and AROMs), but this is not an exhaustive battery and practitioners should consider what measures may best inform training periodization within the context of their environment/sport.
... Further, employing the "two-point method" , the load-velocity relationship enables an athlete's 1RM prediction without applying maximum loads. Compared to traditional 1RM-based strength training with large within subject day-to-day variability (Kiely, 2012;Jovanović and Flanagan, 2014), this relationship has been reported to be load-and exercise-specific (Beck et al., 2020), but robust over long-term training progress (González-Badillo and Sánchez-Medina, 2010). ...
Article
Full-text available
This network meta-analysis aimed at evaluating the effectiveness of different velocity-based (VBT) and traditional 1RM-based resistance training (TRT) interventions on strength and power indices in healthy participants. The research was conducted until December 2021 using the online electronic databases PubMed, Web of Science, PsycNet, and SPORTDiscus for studies with the following inclusion criteria: 1) controlled VBT trials, 2) strength and/or jump and/or sprint parameters as outcomes (c), participants aged between 18 and 40 years, and 4) peer-reviewed and published in English. Standardized mean differences (SMD) using a random effects models were calculated. Fourteen studies with 311 healthy participants were selected and 3 networks (strength, jump, and sprint) were achieved. VBT, TRT, repetitions in reserve (RIR), low velocity loss (lowVL), and high velocity loss (highVL) were ranked for each network. Based on P-score rankings, lowVL (P-score ≥ 0.59; SMD ≥ 0.33) and highVL (P-score ≥ 0.50; SMD ≥ 0.12) revealed favorable effects on strength, jump, and sprint performance compared to VBT (P-score ≤ 0.47; SMD ≤0.01), TRT (P-score ≤0.46; SMD ≤ 0.00), and RIR (P-score ≤ 0.46; SMD ≤ 0.12). In conclusion, lowVL and highVL showed notable effects on strength, jump, and sprint performance. In particular for jump performance, lowVL induced favorable improvements compared to all other resistance training approaches.
... Thermovision can easily analyse the changes taking place in the body and thus can contribute to the appropriate selection of exercises for the athlete. Thermovision can also be helpful in preventing the phenomenon of overtraining [13][14][15][16][17]. Thermovision has been used both to assess the level of physical fitness [18,19] and the effectiveness of the warm-up in many sports disciplines [20][21][22]. ...
Article
Full-text available
In the presented research, we characterised the temperature profiles and the degree of preparation for exercise of individual muscle groups of athletes We hypothesise that by means of thermal imaging studies, the effectiveness of the warm-up can be monitored to determine whether the effort of individual muscles is equal and symmetrical, which can help to avoid a potential injury. In the study, thermographic imaging was performed on a group of athletes exercising on a rowing ergometer involving almost 80% of the muscle parts of the human body for intense and symmetrical exercise. Thermovision studies have confirmed, based on the increased temperature of the muscle areas, that the rowing ergometer involves many muscle groups in training. Moreover, based on the shape of the temperature function obtained from individual body regions of interest, it was shown that conventional exercise on a rowing ergometer causes almost symmetrical work of the right and left sides of the body. Obtained temperature changes in most of the studied muscle areas showed minimum temperature reached the beginning of training—mostly phases 1 and 2. During the subsequent phases, the temperature increase was monitored, stopping at resting temperature. Significantly, temperature variations did not exceed 0.5 °C in all post-training phases. Statistical analyses did not show any significant differences in the symmetry of right and left muscle areas corresponding to the muscle location temperature. Thermal imaging may be an innovative wholly non-invasive and safe method, because checking induces adaptation processes, which may become indicators of an athlete’s efficiency. The imaging can be continuously repeated, and automatic comparison of average temperature or temperature difference may provide some clues that protect athletes from overtraining or serious injuries.
... A carga de treino da maioria dos tipos de periodização é norteada pela síndrome de adaptação geral (efeito agudo) e pela teoria da supercompensação (efeito crônico) (Marques Junior, 2021), mas esse conteúdo vem sendo muito criticado pelos pesquisadores do treino esportivo (Kiely, 2012;Kiely, 2018;Marques Junior, 2017c). Sabendo disso, Marques Junior (2018) elaborou a carga de treino da periodização específica para o voleibol totalmente diferente das outras concepções de periodização. ...
Article
Full-text available
The objective of the review was how structure subjectively the session load before of the training and how to determine the training load of the ball work with the specific periodization for the volleyball. Based on the literature of the specific periodization for the volleyball the training load content was better explained in this paper. The training load of the specific periodization for the volleyball with ball session is subjectively established by the coach based on three interconnected contents (defined sequence of the volleyball, volleyball skill effort, and level of volleyball skill injuries) before of the athletes practiced the training of each technical training exercise and of the game situation training and according to the objective of the session. Game situation training uses only the defined sequence of volleyball defined in the session. The creator this periodization elaborated the ball training classification graphic with the objective of facilitate the volleyball coach in structure the training load subjectively before of the technical training and of the game situation training. After volleyball players practice ball training, the coach presents the scales to the athletes to determine the training load by mathematical calculations. In conclusion, this is the only periodization created for volleyball teams, but it deserves scientific studies to detect if the structuring of the training load through the three interconnected contents provides a better performance of volleyball players during the match.
... Auf der Grundlage dieser Annahmen über den kontinuierlichen Planungs-, Durchführungs-und Re exionsprozess von Coaching kann es keine festgelegte und starre Planungsstrategie für Einsatztrainer*innen geben. Eine Planungsstrategie muss vielmehr kontinuierlich, dynamisch und anpassungsfähig sein und den Coach befähigen, auf Veränderungen bei den Lernenden und in der Umgebung zu reagieren Kiely 2012). ...
Chapter
Der vorliegende Beitrag beantwortet die Frage danach, was Einsatztrainer*innen im Rahmen ihrer professionellen Praxis tun. In diesem Zusammenhang konzeptionalisieren wir Coaching als einen komplexen Prozess, der virtuos unterschiedliche Wissensbereiche miteinander kombiniert, um in der Trainingspraxis auftauchende Probleme zu lösen. Mit dem Professionellen Coaching-Modell stellen wir eine Struktur vor, die in sechs Dimensionen die benötigten Wissensstrukturen einer professionellen Praxis im Einsatztraining aufweist und so Anhaltspunkte für Entwicklung von Einsatztrainer*innen liefert.
Article
The Argentine Rugby Union is a top-tier rugby nation (ranked 8th according to World Rugby), with the Buenos Aires Rugby Union being the largest competitive league. To date, the training practices of Argentinian rugby strength and conditioning coaches have not yet been documented and analyzed. We used an online survey to characterize the training and testing strategies commonly implemented by Argentinian rugby strength and conditioning coaches, which could serve as a guideline for coaching education programs. Thirty-five rugby strength and conditioning coaches (age: 42.0 ±8.9 years; professional experience: 16.8 ±8.3 years) working across 35 clubs (from a total of 40 clubs) participated in the study. The survey consisted of eight sections: 1) background information; 2) strength-power development; 3) speed training; 4) plyometrics; 5) flexibility training; 6) physical testing; 7) technology use; and 8) programing. Overall, Argentinian strength and conditioning coaches did not frequently use periodization strategies to structure programs, reported a progressive reduction in training loads across the season, and prescribed primarily Olympic weightlifting and squat exercises as resistance exercises during different training periods. The analyses of speed training revealed high utilization of form running, plyometrics, and sport-specific movements. Our results also indicated that physical testing and technology may be affected by the economic difficulties of Argentinian clubs. This study presents new information regarding the training methods adopted by Argentinian rugby strength and conditioning coaches while providing them with new insights to improve their professional practices. Practitioners from different countries working in competitive rugby leagues can use the information provided here to examine their own practices and implement evidence-based programs for elite rugby players.
Article
In order to thrive, organizations need to build and maintain an ability to meet unexpected external challenges. Yet many organizations are sluggish: their capabilities can only undergo incremental changes over time. What are the stochastic processes governing “routinely occurring” challenges that best prepare a sluggish organization for unexpected challenges? We address this question with a stylized principal-agent model. The “agent” represents a sluggish organization that can only change its capability by one unit at a time, and the “principal” represents the organization’s head or its competitive environment. The principal commits ex ante to a Markov process over challenge levels. We characterize the process that maximizes long-run capability for both myopic and arbitrarily patient agents. We show how stochastic, time-varying challenges dramatically improve a sluggish organization’s preparedness for sudden challenges. This paper was accepted by Joshua Gans, business strategy.
Article
Full-text available
In dit artikel blikken wij terug op onze wielercarriere. Met veel extra kennis en ervaring op zak beschrijven wij (Laurens ten Dam, Frank Kwanten, Maarten van Kooij en ikzelf) onze trainingsmethodes van destijds en wat we nu anders zouden aanpakken. Een interessant verhaal met een inhoudelijke weergave van de nieuwe inzichten die de afgelopen jaren zijn ontstaan die wordt gebruikt voor een praktische vertaalslag.
Article
Training sollte bestimmten Prinzipien folgen. Die Wissenschaft zeigt, dass sie auch in nicht-leistungssportlichen Settings, wie der klinischen Bewegungstherapie, relevant sind und zunehmend gefordert werden. Die Sportwissenschaftler Lars Donath und Oliver Faude haben die wichtigsten Prinzipien einem aktuellen Prüfstand unterzogen.
Article
Full-text available
Background Reverse periodization is commonly touted as a salient planning strategy to improve sport performance in athletes, but benefits have not been clearly described. Objectives We sought to identify the main characteristics of reverse periodization, and the influence of training volume and periodization models on enhancing physiological measures and sports performance. Design Systematic review. Methods The electronic databases Scopus, PubMed and Web of Science were searched using a comprehensive list of relevant terms. Results A total of 925 studies were identified, and after removal of duplicates and studies based on title and abstract screening, 17 studies remained, and 11 finally included in the systematic review. There was a total of 200 athletes in the included studies. Reverse periodization does not provide superior performance improvements in swimming, running, muscular endurance, maximum strength, or maximal oxygen uptake, compared to traditional or block periodization. The quality of evidence levels for the reverse periodization studies was 1b (individual randomized controlled trial) for two investigations, 2b (individual cohort study) for the remaining studies and a mean of 4.9 points in the PEDro scale (range 0–7). Conclusions It appears that reverse periodization is no more effective than other forms of periodization in improving sports performance. More comparative studies on this alternative version of periodization are required to verify its effectiveness and utility across a range of endurance sports.
Book
Founded on an analysis of scientific literature and backed by an abundance of references, this timely new book examines problems related to sports training, as well as the concept that training-induced changes are founded on adaptive protein synthesis. Discussions include: Alterations in the organism's adaptivity during exercise training Intracellular control of protein synthesis points on molecular mechanisms in exercise training Endocrine mechanisms with regard to acute adaptation during exercise, as well as amplification and post-translation control of the adaptive protein synthesis Practical benefits of the adaptation process in training.
Article
Complex bodily rhythms are ubiquitous in living organisms. These rhythms arise from stochastic, nonlinear biological mechanisms interacting with a fluctuating environment. Disease often leads to alterations from normal to pathological rhythm. Fundamental questions concerning the dynamics of these rhythmic processes abound. For example, what is the origin of physiological rhythms? How do the rhythms interact with each other and the external environment? Can we decode the fluctuations in physiological rhythms to better diagnose human disease? And can we develop better methods to control pathological rhythms? Mathematical and physical techniques combined with physiological and medical studies are addressing these questions and are transforming our understanding of the rhythms of life.
Article
The intelligence failures surrounding the invasion of Iraq dramatically illustrate the necessity of developing standards for evaluating expert opinion. This book fills that need. Here, Philip E. Tetlock explores what constitutes good judgment in predicting future events, and looks at why experts are often wrong in their forecasts. Tetlock first discusses arguments about whether the world is too complex for people to find the tools to understand political phenomena, let alone predict the future. He evaluates predictions from experts in different fields, comparing them to predictions by well-informed laity or those based on simple extrapolation from current trends. He goes on to analyze which styles of thinking are more successful in forecasting. Classifying thinking styles using Isaiah Berlin's prototypes of the fox and the hedgehog, Tetlock contends that the fox--the thinker who knows many little things, draws from an eclectic array of traditions, and is better able to improvise in response to changing events--is more successful in predicting the future than the hedgehog, who knows one big thing, toils devotedly within one tradition, and imposes formulaic solutions on ill-defined problems. He notes a perversely inverse relationship between the best scientific indicators of good judgement and the qualities that the media most prizes in pundits--the single-minded determination required to prevail in ideological combat. Clearly written and impeccably researched, the book fills a huge void in the literature on evaluating expert opinion. It will appeal across many academic disciplines as well as to corporations seeking to develop standards for judging expert decision-making.