Abstract
Purpose
To assess the validity of methods for quantifying training load, fitness and fatigue in endurance athletes using a mathematical model.
Methods
Seven trained runners (\(\dot{V}\)O2max: 51.7 ± 4.5 mL kg−1 min−1, age: 38.6 ± 9.4 years, mean ± SD) completed 15 weeks of endurance running training. Training sessions were assessed using a heart rate (HR), running pace and rating of perceived exertion (RPE). Training dose was calculated using the session-RPE method, Banisters TRIMP and the running training stress score (rTSS). Weekly running performance (1,500-m time trial), fitness (submaximal HR, resting HR) and fatigue [profile of mood states, heart rate variability (HRV)] were measured. A mathematical model was applied to the training data from each runner to provide individual estimates of performance, fitness and fatigue. Correlations assessed the relationships between the modelled and actual weekly performance, fitness and fatigue measures within each runner.
Results
Training resulted in 5.4 ± 2.6 % improvement in 1,500-m performance. Modelled performance was correlated with actual performance in each subject, with relationships being r = 0.70 ± 0.11, 0.60 ± 0.10 and 0.65 ± 0.13 for the rTSS, session-RPE and TRIMP input methods, respectively. There were moderate correlations between modelled and actual fitness (submaximal HR) for the session-RPE (−0.43 ± 0.37) and TRIMP (−0.48 ± 0.39) methods and moderate-to-large correlations between modelled and actual fatigue measured through HRV indices for both session-RPE (−0.48 ± 0.39) and TRIMP (−0.59 ± 0.31) methods.
Conclusions
These findings showed that each of the training load methods investigated are appropriate for quantifying endurance training dose and that submaximal HR and HRV may be useful for monitoring fitness and fatigue, respectively.
Similar content being viewed by others
References
Achten J, Jeukendrup AE (2003) Heart rate monitoring: applications and limitations. Sports Med 33(7):517–538
Allen H, Coggan A (2006) Training and racing with a power meter. Velo Press, Boulder
Aubert AE, Seps B, Beckers F (2003) Heart rate variability in athletes. Sports Med 33(12):889–919 (pii 33123)
Banister EW (1991) Modeling elite athletic performance. In: Green HJ, McDougal JD, Wenger HA (eds) Physiological testing of elite athletes. Human Kinetics, Champaign, pp 403–424
Banister EW, Calvert TW, Savage MV, Bach T (1975) A systems model of training for athletic performance. Aust J Sports Med Exerc Sci 7:57–61
Booth FW, Thomasson DB (1991) Molecular and cellular adaptations of muscle in response to exercise: perspectives of various models. Physiol Rev 71(2):541–585
Borg G (1973) Perceived exertion: a note on “history” and methods. Med Sci Sports 5(2):90–93
Borg GAV, Hassmen P, Langerstrom M (1985) Perceived exertion in relation to heart rate and blood lactate during arm and leg exercise. Eur J Appl Physiol 65:679–685
Borresen J, Lambert MI (2009) The quantification of training load, the training response and the effect on performance. Sports Med 39(9):779–795. doi:10.2165/11317780-000000000-00000
Buchheit M, Chivot A, Parouty J, Mercier D, Al Haddad H, Laursen PB, Ahmaidi S (2010) Monitoring endurance running performance using cardiac parasympathetic function. Eur J Appl Physiol 108(6):1153–1167. doi:10.1007/s00421-009-1317-x
Buchheit M, Simpson MB, Al Haddad H, Bourdon PC, Mendez-Villanueva A (2011) Monitoring changes in physical performance with heart rate measures in young soccer players. Eur J Appl Physiol. doi:10.1007/s00421-011-2014-0
Busso T (2003) Variable dose-response relationship between exercise training and performance. Med Sci Sports Exerc 35(7):1188–1195
Busso T, Thomas L (2006) Using mathematical modeling in training planning. Int J Sports Physiol Perform 1(4):400–405
Busso T, Carasso C, Lacour JR (1991) Adequacy of a systems structure in the modeling of training effects on performance. J Appl Physiol 71(5):2044–2049
Calvert TW, Banister EW, Savage MV, Bach T (1976) A systems model of the effects of training on physical performance. IEEE Trans Syst Man Cybern 6:94–102
Carter JB, Banister EW, Blaber AP (2003) Effect of endurance exercise on autonomic control of heart rate. Sports Med 33(1):33–46
Covertino VA (1991) Blood volume: its adaption to endurance training. Med Sci Sports Exerc 23:1338–1448
Foster C, Hector LL, Welsh R, Schrager M, Green MA, Snyder AC (1995) Effects of specific versus cross-training on running performance. Eur J Appl Physiol 70(4):367–372
Fry RW, Morton AR, Garcia-Webb P, Crawford GP, Keast D (1992) Biological responses to overload training in endurance sports. Eur J Appl Physiol 64(4):335–344
Hautala AJ, Karjalainen J, Kiviniemi AM, Kinnunen H, Makikallio TH, Huikuri HV, Tulppo MP (2010) Physical activity and heart rate variability measured simultaneously during waking hours. Am J Physiol Heart Circ Physiol 298(3):H874–H880. doi:10.1152/ajpheart.00856.2009
Hooper SL, Mackinnon LT (1995) Monitoring overtraining in athletes: recommendations. Sports Med 20(5):321–327
Hooper SL, Mackinnon LT, Hanrahan S (1997) Mood states as an indication of staleness and recovery. Int J Sports Psychol 28(1):1–12
Huikuri HV, Seppanen T, Koistinen MJ, Airaksinen J, Ikaheimo MJ, Castellanos A, Myerburg RJ (1996) Abnormalities in beat-to-beat dynamics of heart rate before the spontaneous onset of life-threatening ventricular tachyarrhythmias in patients with prior myocardial infarction. Circulation 93(10):1836–1844
Impellizzeri FM, Rampinini E, Marcora SM (2005) Physiological assessment of aerobic training in soccer. J Sports Sci 23(6):583–592
Jeukendrup AE, Saris WHM, Brouns F, Kester ADM (1996) A new validated endurance performance test. Med Sci Sports Exerc 28(2):266–270
Jobson SA, Passfield L, Atkinson G, Barton G, Scarf P (2009) The analysis and utilization of cycling training data. Sports Med 39(10):833–844. doi:10.2165/11317840-000000000-00000
Kellmann M, Kallus KW (1993) The recovery-stress-questionnaire: a potential tool to predict performance in sports. In: Nitsch JR, Seiler R (eds) Movement and sport: psychological foundations and effects. Academia, Sankt Augustin, pp 242–247
Kiviniemi AM, Hautala AJ, Kinnunen H, Tulppo MP (2007) Endurance training guided individually by daily heart rate variability measurements. Eur J Appl Physiol 101(6):743–751. doi:10.1007/s00421-007-0552-2
Kiviniemi AM, Hautala AJ, Kinnunen H, Nissila J, Virtanen P, Karjalainen J, Tulppo MP (2009) Daily exercise prescription based on heart rate variability among men and women. Med Sci Sports Exerc. doi:10.1249/MSS.0b013e3181cd5f39
Lambert MI, Borresen J (2006) A theoretical basis of monitoring fatigue: a practical approach for coaches. Int J Sports Sci Coach 1(4):371–387
Liederbach M, Gleim GW, Nicholas JA (1992) Monitoring training status in professional ballet dancers. J Sports Med Phys Fit 32(2):187–195
MacLeod H, Sunderland C (2009) Fluid balance and hydration habits of elite female field hockey players during consecutive international matches. J Strength Cond Res 23(4):1245–1251. doi:10.1519/JSC.0b013e318192b77a
Main LC, Grove JR (2009) A multi-component assessment model for monitoring training distress among athletes. Eur J Sport Sci 9(4):195–202
Manzi V, Iellamo F, Impellizzeri F, D’Ottavio S, Castagna C (2009) Relation between individualized training impulses and performance in distance runners. Med Sci Sports Exerc 41(11):2090–2096. doi:10.1249/MSS.0b013e3181a6a959
Martin DT, Andersen MB, Gates W (2000) Using profile of mood states (POMS) to monitor high-intensity training in cyclists: group versus case studies. Sport Psychol 14:138–156
McGregor SJ, Weese RK, Ratz IK (2009) Performance modeling in an Olympic 1500-m finalist: a practical approach. J Strength Cond Res 23(9):2515–2523. doi:10.1519/JSC.0b013e3181bf88be
McNair DM, Lorr M, Droppleman LF (1971) EITS profile for mood states. Educational and Industrial Testing Service, San Diego
Melanson EL, Freedson PS (2001) The effect of endurance training on resting heart rate variability in sedentary adult males. Eur J Appl Physiol 85(5):442–449
Morton RH, Fitz-Clarke JR, Banister EW (1990) Modeling human performance in running. J Appl Physiol 69(3):1171–1177
Noble BJ, Robertson RJ (1996) Perceived exertion. Human Kinetics, Champaign
Rushall BS (1990) A tool for measuring stress tolerance in elite athletes. J Appl Sport Psychol 2(1):51–66
Scott TJ, Black CR, Quinn J, Coutts AJ (2013) Validity and reliability of the session-RPE method for quantifying training in Australian football: a comparison of the CR10 and CR100 scales. J Strength Cond Res 27(1):270–276. doi:10.1519/JSC.0b013e3182541d2e
Skiba PF (2006) Calculation of power output and quantification of training stress in distance runners: the development of the GOVSS algorithm. http://www.physfarm.com/govss.pdf. Accessed 5 May 2011
Smith ML, Hudson DL, Graitzer HM, Raven PB (1989) Exercise training bradycardia: the role of autonomic balance. Med Sci Sports Exerc 21(1):40–44
Swaine IL, Linden RJ, Mary DA (1994) Loss of exercise training-induced bradycardia with continued improvement in fitness. J Sports Sci 12(5):477–481
Taha T, Thomas SG (2003) Systems modelling of the relationship between training and performance. Sports Med 33(14):1061–1073
Tulppo MP, Makikallio TH, Takala TE, Seppanen T, Huikuri HV (1996) Quantitative beat-to-beat analysis of heart rate dynamics during exercise. Am J Physiol 271(1 Pt 2):H244–H252
Uusitalo AL, Uusitalo AJ, Rusko HK (1998) Exhaustive endurance training for 6–9 weeks did not induce changes in intrinsic heart rate and cardiac autonomic modulation in female athletes. Int J Sports Med 19(8):532–540
Viru A, Viru M (2000) Nature of training effects. In: Garret WE Jr, Kirkendall DT (eds) Exercise and sport science. Lippincott Williams Wilkins, Philadelphia, pp 67–95
Wallace LK, Impellizzeri FM, Slattery KM, Coutts AJ (2013) Establishing the criterion validity and reliability of common methods for quantifying training load. J Strength Cond Res (in press)
Wilmore JH, Stanforth PR, Gagnon J, Rice T, Mandel S, Leon AS, Rao DC, Skinner JS, Bouchard C (2001) Heart rate and blood pressure changes with endurance training: the HERITAGE Family Study. Med Sci Sports Exerc 33(1):107–116
Wood RE, Hayter S, Rowbottom D, Stewart I (2005) Applying a mathematical model to training adaptation in a distance runner. Eur J Appl Physiol 94:310–316
Zavorsky GS (2000) Evidence and possible mechanisms of altered maximum heart rate with endurance training and tapering. Sports Med 29(1):13–26
Acknowledgments
The authors would like to thank Dr. Chris Barnes from the Australian Institute of Sport for his expertise in developing the customised modelling spreadsheets used in this study.
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by William J. Kraemer.
Rights and permissions
About this article
Cite this article
Wallace, L.K., Slattery, K.M. & Coutts, A.J. A comparison of methods for quantifying training load: relationships between modelled and actual training responses. Eur J Appl Physiol 114, 11–20 (2014). https://doi.org/10.1007/s00421-013-2745-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00421-013-2745-1