Field-Derived Power–Duration Variables to Predict Cycling Time-Trial Performance

in International Journal of Sports Physiology and Performance

Click name to view affiliation

Alfred Nimmerichter
Search for other papers by Alfred Nimmerichter in
Current site
Google Scholar
PubMed
Close
,
Bernhard Prinz
Search for other papers by Bernhard Prinz in
Current site
Google Scholar
PubMed
Close
,
Matthias Gumpenberger
Search for other papers by Matthias Gumpenberger in
Current site
Google Scholar
PubMed
Close
,
Sebastian Heider
Search for other papers by Sebastian Heider in
Current site
Google Scholar
PubMed
Close
, and
Klaus Wirth
Search for other papers by Klaus Wirth in
Current site
Google Scholar
PubMed
Close
Restricted access

Purpose: To evaluate the predictive validity of critical power (CP) and the work above CP (W′) on cycling performance (mean power during a 20-min time trial; TT20). Methods: On 3 separate days, 10 male cyclists completed a TT20 and 3 CP and W′ prediction trials of 1, 4, and 10 min and 2, 7, and 12 min in field conditions. CP and W′ were modeled across combinations of these prediction trials with the hyperbolic, linear work/time, and linear power inverse-time (INV) models. The agreement and the uncertainty between the predicted and actual TT20 were assessed with 95% limits of agreement and a probabilistic approach, respectively. Results: Differences between the predicted and actual TT20 were “trivial” for most of the models if the 1-min trial was not included. Including the 1-min trial in the INV and linear work/time models “possibly” to “very likely” overestimated TT20. The INV model provided the smallest total error (ie, best individual fit; 6%) for all cyclists (305 [33] W; 19.6 [3.6] kJ). TT20 predicted from the best individual fit-derived CP, and W′ was strongly correlated with actual TT20 (317 [33] W; r = .975; P < .001). The bias and 95% limits of agreement were 4 (7) W (−11 to 19 W). Conclusions: Field-derived CP and W′ accurately predicted cycling performance in the field. The INV model was most accurate to predict TT20 (1.3% [2.4%]). Adding a 1-min-prediction trial resulted in large total errors, so it should not be included in the models.

The authors are with Training and Sports Sciences, University of Applied Sciences Wiener Neustadt, Wiener Neustadt, Austria.

Nimmerichter (nimmerichter@fhwn.ac.at) is corresponding author.
  • Collapse
  • Expand
  • 1.

    Hill AV. The physiological basis of athletic records. Nature. 1925;116:544548. doi:10.1038/116544a0

  • 2.

    Monod H, Scherrer J. The work capacity of a synergic muscular group. Ergonomics. 1965;8:329338. doi:10.1080/00140136508930810

  • 3.

    Poole DC, Ward SA, Gardner GW, Whipp BJ. Metabolic and respiratory profile of the upper limit for prolonged exercise in man. Ergonomics. 1988;31(9):12651279. PubMed ID: 3191904 doi:10.1080/00140138808966766

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Jones AM, Wilkerson DP, DiMenna F, Fulford J, Poole DC. Muscle metabolic responses to exercise above and below the “critical power” assessed using 31P-MRS. Am J Physiol Regul Integr Comp Physiol. 2008;294(2):R585R593. PubMed ID: 18056980 doi:10.1152/ajpregu.00731.2007

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

    Black MI, Jones AM, Blackwell JR, et al. Muscle metabolic and neuromuscular determinants of fatigue during cycling in different exercise intensity domains. J Appl Physiol. 2017;122(3):446459. doi:10.1152/japplphysiol.00942.2016

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

    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):23202334. PubMed ID: 27031742 doi:10.1249/MSS.0000000000000939

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Vanhatalo A, Jones AM, Burnley M. Application of critical power in sport. Int J Sports Physiol Perform. 2011;6(1):128136. PubMed ID: 21487156 doi:10.1123/ijspp.6.1.128

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

    Bartram JC, Thewlis D, Martin DT, Norton KI. Predicting critical power in elite cyclists: questioning the validity of the 3-minute all-out test. Int J Sports Physiol Perform. 2017;12(6):783787. PubMed ID: 27834562 doi:10.1123/ijspp.2016-0376

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Nimmerichter A, Novak N, Triska C, Prinz B, Breese BC. Validity of treadmill-derived critical speed on predicting 5000-meter track-running performance. J Strength Cond Res. 2017;31(3):706714. PubMed ID: 27379951 doi:10.1519/JSC.0000000000001529

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Triska C, Tschan H, Tazreiter G, Nimmerichter A. Critical power in laboratory and field conditions using single-visit maximal effort trials. Int J Sports Med. 2015;36(13):10631068. PubMed ID: 26258826 doi:10.1055/s-0035-1549958

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Karsten B, Jobson SA, Hopker J, Jimenez A, Beedie C. High agreement between laboratory and field estimates of critical power in cycling. Int J Sports Med. 2014;35(4):298303. PubMed ID: 24022574

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Galbraith A, Hopker J, Lelliott S, Diddams L, Passfield L. A single-visit field test of critical speed. Int J Sports Physiol Perform. 2014;9(6):931935. PubMed ID: 24622815 doi:10.1123/ijspp.2013-0507

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

    Jones AM, Burnley M, Black MI, Poole DC, Vanhatalo A. The maximal metabolic steady state: redefining the ‘gold standard.’ Physiol Rep. 2019;7(10):e14098. PubMed ID: 31124324 doi:10.14814/phy2.14098

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

    Bishop D, Jenkins DG, Howard A. The critical power function is dependent on the duration of the predictive exercise tests chosen. Int J Sports Med. 1998;19(2):125129. PubMed ID: 9562222 doi:10.1055/s-2007-971894

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

    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):742747. PubMed ID: 29203319 doi:10.1016/j.jsams.2017.11.015

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

    di Prampero PE. The concept of critical velocity: a brief analysis. Eur J Appl Physiol Occup Physiol. 1999;80(2):162164. PubMed ID: 10408329 doi:10.1007/s004210050574

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Caputo F, Denadai BS. The highest intensity and the shortest duration permitting attainment of maximal oxygen uptake during cycling: effects of different methods and aerobic fitness level. Eur J Appl Physiol. 2008;103(1):4757. PubMed ID: 18196264 doi:10.1007/s00421-008-0670-5

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

    Hill DW, Poole DC, Smith JC. The relationship between power and the time to achieve VO2max. Med Sci Sports Exerc. 2002;34(4):709714. PubMed ID: 11932583

    • PubMed
    • 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):14201425. PubMed ID: 27531664 doi:10.1080/02640414.2016.1215500

    • Search Google Scholar
    • Export Citation
  • 20.

    Nimmerichter A, Williams CA, Bachl N, Eston RG. Evaluation of a field test to assess performance in elite cyclists. Int J Sports Med. 2010;31(3):160166. PubMed ID: 20221996 doi:10.1055/s-0029-1243222

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21.

    Borszcz FK, Tramontin AF, Bossi AH, Carminatti LJ, Costa VP. Functional threshold power in cyclists: validity of the concept and physiological responses. Int J Sports Med. 2018;39(10):737742. PubMed ID: 29801189 doi:10.1055/s-0044-101546

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

    Allen H, Coggan AR. Training and Racing With a Power Meter. 2nd ed. Boulder, CO: VeloPress; 2006.

  • 23.

    Morgan PT, Black MI, Bailey SJ, Jones AM, Vanhatalo A. Road cycle TT performance: relationship to the power-duration model and association with FTP. J Sports Sci. 2019;37(8):902910. PubMed ID: 30387374 doi:10.1080/02640414.2018.1535772

    • Search Google Scholar
    • Export Citation
  • 24.

    Black MI, Durant J, Jones AM, Vanhatalo A. Critical power derived from a 3-min all-out test predicts 16.1-km road time-trial performance. Eur J Sport Sci. 2014;14(3):217223. PubMed ID: 23802599 doi:10.1080/17461391.2013.810306

    • 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):137144. doi:10.1007/BF02844014

    • Search Google Scholar
    • Export Citation
  • 26.

    Whipp BJ, Huntsman DJ, Stoner N, Lamarra N, Wasserman KA. A constant which determines the duration of tolerance to high-intensity work. Fed Proc. 1982;41:1591.

    • Search Google Scholar
    • Export Citation
  • 27.

    Hill DW, Smith JC. 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):2337. PubMed ID: 7934008

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28.

    Black MI, Jones AM, Bailey SJ, Vanhatalo A. Self-pacing increases critical power and improves performance during severe-intensity exercise. Appl Physiol Nutr Metab. 2015;40(7):662670. PubMed ID: 26088158 doi:10.1139/apnm-2014-0442

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

    Batterham AM, Hopkins WG. Making meaningful inferences about magnitudes. Sportscience. 2005;9:613.

  • 30.

    Skiba PF, Clarke D, Vanhatalo A, Jones AM. Validation of a novel intermittent W′ model for cycling using field data. Int J Sports Physiol Perform. 2014;9(6):900904. PubMed ID: 24509723 doi:10.1123/ijspp.2013-0471

    • PubMed
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 24 24 5
Full Text Views 3 3 1
PDF Downloads 6 6 1