CoChat
Sign Up
Cited by 259Sports Performance and TrainingCardiovascular and exercise physiologySport Psychology and Performance

The DOI matches its Crossref record; 62 of the 62 references it cites were found in a registry or an index.

The ‘Critical Power’ Concept: Applications to Sports Performance with a Focus on Intermittent High-Intensity Exercise

Open access
Jones, Andrew M., Vanhatalo, Anni·2017·Sports Medicine
DOI 10.1007/s40279-017-0688-0PMC PMC5371646
Open this paper in CoChat — free accountOpen PDF

Abstract

The curvilinear relationship between power output and the time for which it can be sustained is a fundamental and well-known feature of high-intensity exercise performance. This relationship 'levels off' at a 'critical power' (CP) that separates power outputs that can be sustained with stable values of, for example, muscle phosphocreatine, blood lactate, and pulmonary oxygen uptake ([Formula: see text]), from power outputs where these variables change continuously with time until their respective minimum and maximum values are reached and exercise intolerance occurs. The amount of work that can be done during exercise above CP (the so-called W') is constant but may be utilized at different rates depending on the proximity of the exercise power output to CP. Traditionally, this two-parameter CP model has been employed to provide insights into physiological responses, fatigue mechanisms, and performance capacity during continuous constant power output exercise in discrete exercise intensity domains. However, many team sports (e.g., basketball, football, hockey, rugby) involve frequent changes in exercise intensity and, even in endurance sports (e.g., cycling, running), intensity may vary considerably with environmental/course conditions and pacing strategy. In recent years, the appeal of the CP concept has been broadened through its application to intermittent high-intensity exercise. With the assumptions that W' is utilized during work intervals above CP and reconstituted during recovery intervals below CP, it can be shown that performance during intermittent exercise is related to four factors: the intensity and duration of the work intervals and the intensity and duration of the recovery intervals. However, while the utilization of W' may be assumed to be linear, studies indicate that the reconstitution of W' may be curvilinear with kinetics that are highly variable between individuals. This has led to the development of a new CP model for intermittent exercise in which the balance of W' remaining ([Formula: see text]) may be calculated with greater accuracy. Field trials of athletes performing stochastic exercise indicate that this [Formula: see text] model can accurately predict the time at which W' tends to zero and exhaustion is imminent. The [Formula: see text] model potentially has important applications in the real-time monitoring of athlete fatigue progression in endurance and team sports, which may inform tactics and influence pacing strategy.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/s40279-017-0688-0

Cites

62 of 62 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig. 1 a Hyperbolic relationship between power output (x-axis) and time (y-axis), where the critical power is indicated by the power-asymptote and the W′ is the curvature constant; b linearized two-parameter critical power model where total work done is plotted against time. In this permutation, the critical power is given by the slope of the regression and the W′ is the y-intercept. CP critical power, P power, T time, W′ curvature constant of power–time relationship
Fig. 1 a Hyperbolic relationship between power output (x-axis) and time (y-axis), where the critical power is indicated by the power-asymptote and the W′ is the curvature constant; b linearized two-parameter critical power model where total work done is plotted against time. In this permutation, the critical power is given by the slope of the regression and the W′ is the y-intercept. CP critical power, P power, T time, W′ curvature constant of power–time relationshipCC BY · PubMed Central
Fig. 2 An example of the estimation of critical speed and D′ in Haile Gebrselassie, using the linear distance–time model. The distances modelled ranged from 2 km (4:56.1) to 15 km (41:38). Critical speed was 5.91 m s−1 and D′ was 351 m. CS critical speed, D′ curvature constant of speed–time relationship, R 2 coefficient of determination
Fig. 2 An example of the estimation of critical speed and D′ in Haile Gebrselassie, using the linear distance–time model. The distances modelled ranged from 2 km (4:56.1) to 15 km (41:38). Critical speed was 5.91 m s−1 and D′ was 351 m. CS critical speed, D′ curvature constant of speed–time relationship, R 2 coefficient of determinationCC BY · PubMed Central
Fig. 3 Muscle phosphocreatine responses to constant power output severe-intensity exercise immediately followed by passive recovery (black circles), exercise <CP (white circles) or exercise >CP (white triangles). a End-recovery muscle [PCr] was lower in >CP and <CP recovery conditions compared with rest (p < 0.05). b End-recovery muscle [PCr] was significantly lower for >CP condition compared with rest and <CP recovery (p < 0.05). Figure has been re-drawn based on data from Chidnok et al. [44]. CP critical power, EXH exhaustion, [Pcr] phosphocreatine concentration
Fig. 3 Muscle phosphocreatine responses to constant power output severe-intensity exercise immediately followed by passive recovery (black circles), exercise <CP (white circles) or exercise >CP (white triangles). a End-recovery muscle [PCr] was lower in >CP and <CP recovery conditions compared with rest (p < 0.05). b End-recovery muscle [PCr] was significantly lower for >CP condition compared with rest and <CP recovery (p < 0.05). Figure has been re-drawn based on data from Chidnok et al. [44]. CP critical power, EXH exhaustion, [Pcr] phosphocreatine concentrationCC BY · PubMed Central
Fig. 4 Relationships between W′ depletion and reconstitution with different recovery intensities during intermittent exercise: severe–heavy (dotted line), severe–moderate (dashed line), and severe–light (solid line). Figure has been re-drawn based on data from Chidnok et al. [48]. W′ curvature constant of power–time relationship
Fig. 4 Relationships between W′ depletion and reconstitution with different recovery intensities during intermittent exercise: severe–heavy (dotted line), severe–moderate (dashed line), and severe–light (solid line). Figure has been re-drawn based on data from Chidnok et al. [48]. W′ curvature constant of power–time relationshipCC BY · PubMed Central
Fig. 5 V˙O2 and EMG responses during severe constant power output (S-CPO) exercise and intermittent severe-intensity exercise with recovery power output (S-CWR) at severe (a), heavy (b), moderate (c), or light intensity (d). Open symbols represent responses during constant power output severe-intensity exercise and closed symbols represent responses when severe-intensity exercise is interspersed with recovery intervals in the severe (S–S), heavy (S–H), or moderate (S–M) domains and for light (20 W) exercise (S–L). *Time to exhaustion differed significantly from S-CWR (p < 0.05). # End-exercise V˙O2 and EMG was significantly lower than S–M and S–L (p < 0.05). Figure has been re-drawn based on data from Chidnok et al. [48]. EMG electromyogram, MVC maximal voluntary contraction, V˙O2 oxygen uptake
Fig. 5 V˙O2 and EMG responses during severe constant power output (S-CPO) exercise and intermittent severe-intensity exercise with recovery power output (S-CWR) at severe (a), heavy (b), moderate (c), or light intensity (d). Open symbols represent responses during constant power output severe-intensity exercise and closed symbols represent responses when severe-intensity exercise is interspersed with recovery intervals in the severe (S–S), heavy (S–H), or moderate (S–M) domains and for light (20 W) exercise (S–L). *Time to exhaustion differed significantly from S-CWR (p < 0.05). # End-exercise V˙O2 and EMG was significantly lower than S–M and S–L (p < 0.05). Figure has been re-drawn based on data from Chidnok et al. [48]. EMG electromyogram, MVC maximal voluntary contraction, V˙O2 oxygen uptakeCC BY · PubMed Central
Fig. 6 The influence of different work and recovery intervals during intermittent severe-intensity exercise on the time constant (τ) for W′ reconstitution. The mean ± standard deviation W′ recovery time constant tended to become shorter as the recovery duration separating 20-s work bouts was increased from 5 to 20 s. Conversely, the W′ recovery became progressively slower as the recovery duration was kept constant at 30 s, whereas the work duration was increased from 20 to 60 s. Figure re-drawn based on data from Skiba et al. [58]
Fig. 6 The influence of different work and recovery intervals during intermittent severe-intensity exercise on the time constant (τ) for W′ reconstitution. The mean ± standard deviation W′ recovery time constant tended to become shorter as the recovery duration separating 20-s work bouts was increased from 5 to 20 s. Conversely, the W′ recovery became progressively slower as the recovery duration was kept constant at 30 s, whereas the work duration was increased from 20 to 60 s. Figure re-drawn based on data from Skiba et al. [58]CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 62 references

Cited by

Sorted by citations

Related

See all

Metadata

Authors
Jones, A. M., & Vanhatalo, A.
Affiliations
University of Exeter (GB)
Corresponding author
Jones, Andrew M.
ORCID
Venue
Sports Medicine
Publisher
Springer Science and Business Media LLC
Published
2017-03
Volume
47
Issue
S1
Pages
65-78
ISSN
  • 0112-1642 (ISSN-L)
  • 1179-2035
DOI
10.1007/s40279-017-0688-0
PMC
PMC5371646
OpenAlex
W2598090454
Cited by
259
References
62
Citations by year
2026: 24 · 2025: 36 · 2024: 32 · 2023: 26 · 2022: 36 · 2021: 37 · 2020: 36 · 2019: 15 · 2018: 15 · 2017: 2
FWCI
3.35
Type
journal article
Language
en
Open access
Licence
Locations
  • Sports Medicine (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • PepsiCo
  • Gran Sasso Science Institute
Topics
  • Health Sciences › Medicine › Orthopedics and Sports Medicine › Sports Performance and Training
  • Health Sciences › Medicine › Physiology (medical) › Cardiovascular and exercise physiology
  • Social Sciences › Psychology › Developmental and Educational Psychology › Sport Psychology and Performance
Keywords
critical power, high-intensity intermittent exercise, work capacity, team sports, endurance sports, pacing strategy, fatigue monitoring, exercise intolerance, phosphocreatine, blood lactate, pulmonary oxygen uptake
MeSH terms
Exercise Test, Humans, Oxygen Consumption, Physical Endurance, Exercise, Athletic Performance

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review