Power Profiling in U23 Professional Cyclists During a Competitive Season

in International Journal of Sports Physiology and Performance
Peter Leo, James Spragg, Iñigo Mujika, Verena Menz, and Justin S. Lawley
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DOI:
https://doi.org/10.1123/ijspp.2020-0200
Keywords:
cycling; training; racing
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Ahead of Print
Pages:
1–9
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Purpose: The aim of this study was to investigate changes in the power profile of U23 professional cyclists during a competitive season based on maximal mean power output (MMP) and derived critical power (CP) and work capacity above CP (W′) obtained during training and racing. Methods: A total of 13 highly trained U23 professional cyclists (age = 21.1 [1.2] y, maximum oxygen consumption = 73.8 [1.9] mL·kg–1·min–1) participated in this study. The cycling season was split into pre-season and in-season. In-season was divided into early-, mid-, and late-season periods. During pre-season, a CP test was completed to derive CPtest and W′test. In addition, 2-, 5-, and 12-minute MMP during in-season were used to derive CPfield and W′field. Results: There were no significant differences in absolute 2-, 5-, and 12-minute MMP, CPfield, and W′field between in-season periods. Due to changes in body mass, relative 12-minute MMP was higher in late-season compared with early-season (P = .025), whereas relative CPfield was higher in mid- and late-season (P = .031 and P = .038, respectively) compared with early-season. There was a strong correlation (r = .77–.83) between CPtest and CPfield in early- and mid-season but not late-season. Bland–Altman plots and standard error of estimates showed good agreement between CPtest and in-season CPfield but not between W′test and W′field. Conclusion: These findings reveal that the power profile remains unchanged throughout the in-season, except for relative 12-minute MMP and CPfield in late-season. One pre-season and one in-season CP test are recommended to evaluate in-season CPfield and W′field.

Leo, Lawley, and Menz are with the Dept of Sport Science, University of Innsbruck, Innsbruck, Austria. Spragg is with Spragg Cycle Coaching in Exeter, United Kingdom. Mujika is with the Dept of Physiology, Faculty of Medicine and Nursing, University of the Basque Country, Basque Country, Spain; and the Exercise Science Laboratory, School of Kinesiology, Faculty of Medicine, Universidad Finis Terrae, Santiago, Chile.

Lawley (justin.lawley@uibk.ac.at) is corresponding author.

International Journal of Sports Physiology and Performance

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  • 1.

    Vanhatalo A, Jones AM, Burnley M. Application of critical power in sport. Int J Sports Physiol Perform. 2011;6(1):128–136. PubMed ID: 21487156 doi:
  • 2.

    Poole DC, Burnley M, Vanhatalo A, Rossiter HB, Jones AM. Critical power: an important fatigue threshold in exercise physiology. Med Sci Sports Exerc. 2016;48(11):2320–2334. PubMed ID: 27031742 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Quod MJ, Martin DT, Martin JC, Laursen PB. The power profile predicts road cycling MMP. Int J Sports Med. 2010;31(6):397–401. PubMed ID: 20301046 doi:
  • 4.

    Jones AM, Vanhatalo A. The ‘critical power’ concept: applications to sports performance with a focus on intermittent high-intensity exercise. Sports Med. 2017;47(suppl 1):65–78. PubMed ID: 28332113 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Karsten B, Jobson SA, Hopker J, Stevens L, Beedie C. Validity and reliability of critical power field testing. Eur J Appl Physiol. 2015;115(1):197–204. PubMed ID: 25260244 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Wahl P, Schütt S, Volmary P. Power Profiling als leistungsdiagnostisches Tool im Radsport—Identifizierung leistungsrelevanter physiologischer Zubringergrößen. In: BISp Jahrbuch Forschungsförderung 2016/17. SPORTVERLAG Strauß; 2018 :63–69.

    • Search Google Scholar
    • Export Citation
  • 7.

    Passfield L, Hopker JG, Jobson S, Friel D, Zabala M. Knowledge is power: issues of measuring training and performance in cycling. J Sports Sci. 2017;35(14):1426–1434. PubMed ID: 27686573 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Pinot J, Grappe F. The record power profile to assess performance in elite cyclists. Int J Sports Med. 2011;32(11):839–844. PubMed ID: 22052032 doi:
  • 9.

    Hill AV. Muscular movement in man: the factors governing speed and recovery from fatigue. J Chem Educ. 1927;5(1):100.
  • 10.

    Monod H, Scherrer J. The work capacity of a synergic muscular group. Ergonomics. 1965;8(3):329–338. doi:
  • 11.

    Morton RH. A 3-parameter critical power model. Ergonomics. 1996;39(4):611–619. PubMed ID: 8854981 doi:
  • 12.

    Garcia-Manso JM, Martin-Gonzalez JM, Vaamonde D, Silva-Grigoletto ME. The limitations of scaling laws in the prediction of performance in endurance events. J Theor Biol. 2012;300:324–329. PubMed ID: 22300800 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Peronnet F, Thibault G. Mathematical analysis of running performance and world running records. J Appl Physiol. 1989;67(1):453–465. PubMed ID: 2759974 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14.

    Mattioni Maturana F, Fontana FY, Pogliaghi S, Passfield L, Murias JM. Critical power: how different protocols and models affect its determination. J Sci Med Sport. 2018;21(7):742–747. PubMed ID: 29203319 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15.

    Vanhatalo A, Fulford J, DiMenna FJ, Jones AM. Influence of hyperoxia on muscle metabolic responses and the power–duration relationship during severe-intensity exercise in humans: a 31P magnetic resonance spectroscopy study. Exp Physiol. 2010;95(4):528–540. PubMed ID: 20028850 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Burnley M, Jones AM. Oxygen uptake kinetics as a determinant of sports performance. Eur J Sport Sci. 2007;7(2):63–79. doi:
  • 17.

    Skiba PF, Chidnok W, Vanhatalo A, Jones AM. Modeling the expenditure and reconstitution of work capacity above critical power. Med Sci Sports Exerc. 2012;44(8):1526–1532. PubMed ID: 22382171 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Jones AM, Vanhatalo A, Burnley M, Morton RH, Poole DC. Critical power: implications for determination of VO2max and exercise tolerance. Med Sci Sports Exerc. 2010;42(10):1876–1890. PubMed ID: 20195180 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 19.

    Karsten B, Hopker J, Jobson SA, et al. Comparison of inter-trial recovery times for the determination of critical power and W’ in cycling. J Sports Sci. 2017;35(14):1420–1425. PubMed ID: 27531664 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Pinot J, Grappe F. Determination of maximal aerobic power on the field in cycling. J Sci Cycl. 2014;3(1):26–31.
  • 21.

    Mujika I, Padilla S. Physiological and performance characteristics of male professional road cyclists. Sports Med. 2001;31(7):479–487. PubMed ID: 11428685 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Ebert TR, Martin DT, Stephens B, Withers RT. Power output during a professional men’s road-cycling tour. Int J Sports Physiol Perform. 2006;1(4):324–335. PubMed ID: 19124890 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Hopker J, Coleman D, Passfield L. Changes in cycling efficiency during a competitive season. Med Sci Sports Exerc. 2009;41(4):912–919. PubMed ID: 19276841 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24.

    Kuipers H, Verstappen FT, Keizer HA, Geurten P, van Kranenburg G. Variability of aerobic performance in the laboratory and its physiologic correlates. Int J Sports Med. 1985;6(4):197–201. PubMed ID: 4044103 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Wooles A, Robinson A, Keen P. A static method for obtaining a calibration factor for SRM bicycle power cranks. Sports Eng. 2005;8(3):137–144. doi:
  • 26.

    Norman G. Likert scales, levels of measurement and the “laws” of statistics. Adv Health Sci Educ Theory Pract. 2010;15(5):625–632. PubMed ID: 20146096 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 27.

    Hopkins WG. A scale of magnitudes for effect statistics. 2002. http://www.sportsci.org/resource/stats/effectmag.html.
  • 28.

    De Pauw K, Roelands B, Cheung S, De Geus B, Rietjens G, Meeusen R. Guidelines to classify subject groups in sport-science research. Int J Sports Physiol Perform. 2013;8(2):111–122. PubMed ID: 23428482 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 29.

    Muros JJ, Sanchez-Munoz C, Hoyos J, Zabala M. Nutritional intake and body composition changes in a UCI world tour cycling team during the tour of Spain. Eur J Sport Sci. 2019;19(1):86–94. PubMed ID: 30016187 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 30.

    Padilla S, Mujika I, Cuesta G, Goiriena JJ. Level ground and uphill cycling ability in professional road cycling. Med Sci Sports Exerc. 1999;31(6):878–885. PubMed ID: 10378916 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31.

    Swain DP. The influence of body mass in endurance bicycling. Med Sci Sports Exerc. 1994;26(1):58–63. PubMed ID: 8133740
  • 32.

    Miura A, Sato H, Sato H, Whipp BJ, Fukuba Y. The effect of glycogen depletion on the curvature constant parameter of the power-duration curve for cycle ergometry. Ergonomics. 2000;43(1):133–141. PubMed ID: 10661696 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 33.

    Hill D, Smith J. A method to ensure the accuracy of estimates of anaerobic capacity derived using the critical power concept. J Sports Med Phys Fitness. 1994;34(1):23–37. PubMed ID: 7934008

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34.

    Jobson SA, Nevill AM, Palmer GS, Jeukendrup AE, Doherty M, Atkinson G. The ecological validity of laboratory cycling: does body size explain the difference between laboratory- and field-based cycling performance? J Sports Sci. 2007;25(1):3–9. PubMed ID: 17127577 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35.

    van Erp T, Hoozemans M, Foster C, de Koning JJ. Case report: load, intensity, and performance characteristics in multiple grand tours. Med Sci Sports Exerc. 2020;52(4):868–875. PubMed ID: 31688657 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 36.

    Rodríguez-Marroyo JA, Villa JG, Pernía R, Foster C. Decrement in professional cyclists’ performance after a grand tour. Int J Sports Physiol Perform. 2017;12(10):1348–1355. PubMed ID: 28338363 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37.

    Jobson S, Woodside J, Passfield L, Nevill A. Allometric scaling of uphill cycling performance. Int J Sports Med. 2008;29(9):753–757. PubMed ID: 18213539 doi:
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