Relationship Between Various Training-Load Measures in Elite Cyclists During Training, Road Races, and Time Trials

in International Journal of Sports Physiology and Performance
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Purpose: The relationship between various training-load (TL) measures in professional cycling is not well explored. This study investigated the relationship between mechanical energy spent (in kilojoules), session rating of perceived exertion (sRPE), Lucia training impulse (LuTRIMP), and training stress score (TSS) in training, races, and time trials (TT). Methods: For 4 consecutive years, field data were collected from 21 professional cyclists and categorized as being collected in training, racing, or TTs. Kilojoules (kJ) spent, sRPE, LuTRIMP, and TSS were calculated, and the correlations between the various TLs were made. Results: 11,655 sessions were collected, from which 7596 sessions had heart-rate data and 5445 sessions had an RPE score available. The r between the various TLs during training was almost perfect. The r between the various TLs during racing was almost perfect or very large. The r between the various TLs during TTs was almost perfect or very large. For all relationships between TSS and 1 of the other measurements of TL (kJ spent, sRPE, and LuTRIMP), a significant different slope was found. Conclusion: kJ spent, sRPE, LuTRIMP, and TSS all have a large or almost perfect relationship with each other during training, racing, and TTs, but during racing, both sRPE and LuTRIMP have a weaker relationship with kJ spent and TSS. Furthermore, the significant different slope of TSS vs the other measurements of TL during training and racing has the effect that TSS collected in training and road races differs by 120%, whereas the other measurements of TL (kJ spent, sRPE, and LuTRIMP) differ by only 73%, 67%, and 68%, respectively.

The authors are with the Dept of Human Movement Sciences, Amsterdam Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands. Foster and de Koning are also with the Dept of Exercise and Sport Science, University of Wisconsin–La Crosse, La Crosse, WI.

de Koning (j.j.de.koning@vu.nl) is corresponding author.
  • 1.

    Foster C, Daines E, Hector L, Snyder AC, Welsh R. Athletic performance in relation to training load. Wis Med J. 1996;95:370–374. PubMed ID: 8693756

  • 2.

    Meeusen R, Duclos M, Foster C, et al. Prevention, diagnosis, and treatment of the overtraining syndrome: joint consensus statement of the European College of Sport Science and the American College of Sports Medicine. Med Sci Sports Exerc. 2013;45:186–205. PubMed ID: 23247672 doi:10.1249/MSS.0b013e318279a10a

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

    Hulin BT, Gabbett TJ, Blanch P, Chapman P, Bailey D, Orchard JW. Spikes in acute workload are associated with increased injury risk in elite cricket fast bowlers. Br J Sports Med. 2014;48:708–712. PubMed ID: 23962877 doi:10.1136/bjsports-2013-092524

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

    Morton RH, Fitz-Clarke JR, Banister EW. Modeling human performance in running. J Appl Physiol. 1990;69:1171–1177. PubMed ID: 2246166 doi:10.1152/jappl.1990.69.3.1171

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

    Fitz-Clarke JR, Morton RH, Banister EW. Optimizing athletic performance by influence curves. J Appl Physiol. 1991;71:1151–1158. PubMed ID: 1757312 doi:10.1152/jappl.1991.71.3.1151

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

    Mujika I. Intense training: the key to optimal performance before and during the taper. Scand J Med Sci Sports. 2010;20(suppl 2):24–31. PubMed ID: 20840559 doi:10.1111/j.1600-0838.2010.01189.x

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

    Viru A, Viru M. Nature of training effects. In: Viru A, Viru M, eds. Exercise and Sports Science. Philadelphia, PA: Lippincott Williams & Wilkins; 2000:67–95.

    • Search Google Scholar
    • Export Citation
  • 8.

    Hopkins WG. Quantification of training in competitive sports. Methods and applications. Sports Med. 1991;12:161–183. PubMed ID: 1784872 doi:10.2165/00007256-199112030-00003

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

    Banister EW, Carter JB, Zarkadas PC. Training theory and taper: validation in triathlon athletes. Eur J Appl Physiol Occup Physiol. 1999;79:182–191. PubMed ID: 10029340 doi:10.1007/s004210050493

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

    Borresen J, Lambert MI. Quantifying training load: a comparison of subjective and objective methods. Int J Sports Physiol Perform. 2008;3:16–30. PubMed ID: 19193951 doi:10.1123/ijspp.3.1.16

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

    Sanders D, Abt G, Hesselink MK, Myers T, Akubat I. Methods of monitoring training load and their relationships to changes in fitness and performance in competitive road cyclists. Int J Sports Physiol Perform. 2017;12(5):668–675. PubMed ID: 28095061 doi:10.1123/ijspp.2016-0454

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

    Lucia A, Hoyos J, Chicharro JL. Physiology of professional road cycling. Sports Med. 2001;31:325–337. PubMed ID: 11347684 doi:10.2165/00007256-200131050-00004

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

    Lucia A, Hoyos J, Santalla A, Earnest C, Chicharro JL. Tour de France versus Vuelta a Espana: which is harder? Med Sci Sports Exerc. 2003;35:872–878. PubMed ID: 12750600 doi:10.1249/01.MSS.0000064999.82036.B4

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

    Borresen J, Lambert MI. The quantification of training load, the training response and the effect on performance. Sports Med. 2009;39:779–795. PubMed ID: 19691366 doi:10.2165/11317780-000000000-00000

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

    Lambert MI, Mbambo ZH, St Clair Gibson A. Heart rate during training and competition for long-distance running. J Sports Sci. 1998;16(suppl):85–90. PubMed ID: 22587721 doi:10.1080/026404198366713

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

    Bagger M, Petersen PH, Pedersen PK. Biological variation in variables associated with exercise training. Int J Sports Med. 2003;24:433–440. PubMed ID: 12905092 doi:10.1055/s-2003-41180

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

    Foster C, Hector LL, Welsh R, Schrager M, Green MA, Snyder AC. Effects of specific versus cross-training on running performance. Eur J Appl Physiol Occup Physiol. 1995;70:367–372. PubMed ID: 7649149 doi:10.1007/BF00865035

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

    Borg G. Perceived exertion as an indicator of somatic stress. Scand J Rehabil Med. 1970;2:92–98. PubMed ID: 5523831

  • 19.

    Herman L, Foster C, Maher MA, Mikat RP, Porcari JP. Validity and reliability of the session RPE method for monitoring exercise training intensity. South Afr J Sports Med. 2006;18:4. doi:10.17159/2078-516X/2006/v18i1a245

    • Search Google Scholar
    • Export Citation
  • 20.

    Rodriguez-Marroyo JA, Villa G, Garcia-Lopez J, Foster C. Comparison of heart rate and session rating of perceived exertion methods of defining exercise load in cyclists. J Strength Cond Res. 2012;26:2249–2257. PubMed ID: 21997452 doi:10.1519/JSC.0b013e31823a4233

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

    Christen J, Foster C, Porcari JP, Mikat RP. Temporal robustness of the session rating of perceived exertion. Int J Sports Physiol Perform. 2016;11:1088–1093. PubMed ID: 26999454 doi:10.1123/ijspp.2015-0438

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

    Crowcroft S, Duffield R, McCleave E, Slattery K, Wallace LK, Coutts AJ. Monitoring training to assess changes in fitness and fatigue: the effects of training in heat and hypoxia. Scand J Med Sci Sports. 2015;25(suppl 1):287–295. PubMed ID: 25943680 doi:10.1111/sms.12364

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

    Logan-Sprenger HM, Heigenhauser GJ, Jones GL, Spriet LL. The effect of dehydration on muscle metabolism and time trial performance during prolonged cycling in males. Physiol Rep. 2015;3:e12483. PubMed ID: 26296770 doi:10.14814/phy2.12483

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

    Hunter A, Coggan A. Training and Racing With a Power Meter. 2nd ed. Boulder, CO: Velopress; 2010.

  • 25.

    Sanders D, Heijboer M, Hesselink MKC, Myers T, Akubat I. Analysing a cycling grand tour: can we monitor fatigue with intensity or load ratios? J Sports Sci. 2018. 36(12):1385–1391. PubMed ID: 29016241 doi:10.1080/02640414.2017.1388669

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Green JM, McLester JR, Crews TR, Wickwire PJ, Pritchett RC, Lomax RG. RPE association with lactate and heart rate during high-intensity interval cycling. Med Sci Sports Exerc. 2006;38:167–172. PubMed ID: 16394970 doi:10.1249/01.mss.0000180359.98241.a2

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

    Seiler S, Sylta O. How does interval-training prescription affect physiological and perceptual responses? Int J Sports Physiol Perform. 2017;12:S280–S286. PubMed ID: 28051345 doi:10.1123/ijspp.2016-0464

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

    Foster C, Florhaug JA, Franklin J, et al. A new approach to monitoring exercise training. J Strength Cond Res. 2001;15:109–115. PubMed ID: 11708692

  • 29.

    Seiler ST, Tønnessen E. Intervals, thresholds, and long slow distance: the role of intensity and duration in endurance training. Sportscience. 2009;30:32–53.

    • Search Google Scholar
    • Export Citation
  • 30.

    Seiler S. What is best practice for training intensity and duration distribution in endurance athletes? Int J Sports Physiol Perform. 2010;5:276–291. PubMed ID: 20861519 doi:10.1123/ijspp.5.3.276

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

    Hopkins WG. A new view of statistics. 2002. http://www.sportsci.org/resource/stats/sscorr.html. Accessed October 1, 2016.

  • 32.

    Padilla S, Mujika I, Santisteban J, Impellizzeri FM, Goiriena JJ. Exercise intensity and load during uphill cycling in professional 3-week races. Eur J Appl Physiol. 2008;102:431–438. PubMed ID: 17978835 doi:10.1007/s00421-007-0602-9

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

    Earnest CP, Foster C, Hoyos J, Muniesa CA, Santalla A, Lucia A. Time trial exertion traits of cycling’s grand tours. Int J Sports Med. 2009;30:240–244. PubMed ID: 19199205 doi:10.1055/s-0028-1105948

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

    Nimmerichter A, Williams C, Bachl N, Eston R. Evaluation of a field test to assess performance in elite cyclists. Int J Sports Med. 2010;31:160–166. PubMed ID: 20221996 doi:10.1055/s-0029-1243222

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

    Wallace LK, Slattery KM, Impellizzeri FM, Coutts AJ. Establishing the criterion validity and reliability of common methods for quantifying training load. J Strength Cond Res. 2014;28:2330–2337. PubMed ID: 24662229 doi:10.1519/JSC.0000000000000416

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

    Halson SL, Bridge MW, Meeusen R, et al. Time course of performance changes and fatigue markers during intensified training in trained cyclists. J Appl Physiol. 2002;93:947–956. PubMed ID: 12183490 doi:10.1152/japplphysiol.01164.2001

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

    Rodriguez-Marroyo JA, Garcia-Lopez J, Juneau CE, Villa JG. Workload demands in professional multi-stage cycling races of varying duration. Br J Sports Med. 2009;43:180–185. PubMed ID: 18065442 doi:10.1136/bjsm.2007.043125

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38.

    Rodriguez-Marroyo JA, Villa JG, Pernia 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:10.1123/ijspp.2016-0294

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 39.

    Achten J, Jeukendrup AE. Heart rate monitoring: applications and limitations. Sports Med. 2003;33:517–538. PubMed ID: 12762827 doi:10.2165/00007256-200333070-00004

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40.

    Arney BE, Glover R, Fusco A, Cortis C, et al. Comparison of rating of perceived exertion scales during incremental and interval exercise. Kinesiology. In Press.

    • Search Google Scholar
    • Export Citation
  • 41.

    Yeo WK, Lessard SJ, Chen ZP, et al. Fat adaptation followed by carbohydrate restoration increases AMPK activity in skeletal muscle from trained humans. J Appl Physiol. 2008;105:1519–1526. PubMed ID: 18801964 doi:10.1152/japplphysiol.90540.2008

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42.

    Hansen AK, Fischer CP, Plomgaard P, Andersen JL, Saltin B, Pedersen BK. Skeletal muscle adaptation: training twice every second day vs. training once daily. J Appl Physiol. 2005;98:93–99. PubMed ID: 15361516 doi:10.1152/japplphysiol.00163.2004

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
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