Maximum heart rate predicted by formulas versus values obtained in graded exercise tests in Brazilian jiu-jitsu athletes

  • Braulio Henrique Magnani BrancoEmail author
  • Fabiano de Oliveira Mendes
  • Gabriel Fassina Ladeia
  • Sônia Maria Marques Gomes Bertolini
  • Pablo Valdés Badilla
  • Leonardo Vidal Andreato
Original Article



Aerobic training can be conducted using the maximum heart rate (HRmax) target zone. This type of training is relevant to improving aerobic fitness and can help Brazilian jiu-jitsu athletes maintain optimal performance during and between matches. However, due to the lack of specificity of the generic equations in systematizing the training, the values can be overestimated, because athletes show specific morphophysiological adjustments.


The aim was to investigate the relationship between HRmax as estimated by means of formulas and HRmax as reached in graded exercise tests (GTX) in both the laboratory and the field.


13 male Brazilian jiu-jitsu athletes had their HRmax determined in GTX on the treadmill and in the field, and the HRmax was calculated based on FOX and TANAKA equations.


The HRmax value by the means equation FOX-HRmax (189 ± 6 bpm) was greater in comparison with the GTX (on treadmill: 183 ± 7 bpm; field test: 180 ± 10 bpm; p < 0.05). The equation TANAKA-HRmax (185 ± 4 bpm) showed higher values when compared to the field test (180 ± 10 bpm; p < 0.05). No differences were observed between TANAKA-HRmax and GTX on the treadmill (p > 0.05). The correlation observed was between FOX-HRmax and TANAKA-HRmax: (r = 0.99; p < 0.01).


FOX-HRmax and TANAKA-HRmax tend to overestimate the results compared to GTX. Thus, HRmax equations should be used and analyzed with caution. Conducting GTX is recommended to establish accurate values of HR.


Athletic performance Martial arts Exercise test 


Compliance with ethical standards

Conflict of interest

The authors declare that there are no conflicts of interests.

Ethical approval

The research was approved by the University Center of Maringa (UNICESUMAR) Ethics Committee under the number 2,091,883/2017.

Informed consent

All athletes signed the informed consent form (ICF) to participate of this study.


  1. 1.
    Mann T, Lamberts RP, Lambert ML (2013) Methods of prescribing relative exercise intensity: physiological and practical considerations. Sports Med 43(7):613–625. CrossRefPubMedGoogle Scholar
  2. 2.
    Nikolaidis PT, Rosemann T, Knechtle B (2018) Age-predicted maximal heart rate in recreational marathon runners: a cross-sectional study on fox’s and tanaka’s equations. Front Physiol 15(9):226. CrossRefGoogle Scholar
  3. 3.
    Cleary MA, Hetzler RK, Wages JJ, Lentz MA, Stickley CD, Kimura IF (2011) Comparisons of age-predicted maximum heart rate equations in college-aged subjects. J Strength Cond Res 25(9):2591–2597. CrossRefPubMedGoogle Scholar
  4. 4.
    Nikolaidis PT (2015) Maximal heart rate in soccer players: measured versus age predicted. Biomed J 38:84–89CrossRefPubMedGoogle Scholar
  5. 5.
    Nikolaidis PT (2014) Age-predicted vs. measured maximal heart rate in young team sport athletes. Niger Med J 55(4):314–320CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    College of Sports Medicine (2018) Guidelines for exercise testing and prescription, 10th edn. Wolters Kluwer Health, PhiladelphiaGoogle Scholar
  7. 7.
    McArdle WD, Katch FL, Katch VL (2014) Exercise physiology: nutrition, energy, and human performance, 8th edn. Wolters Kluwer Health, BaltimoreGoogle Scholar
  8. 8.
    Robergs RA, Landwehr R (2002) The surprising history of the “HRmax = 220-age” equation. JEP Online 5:1–10Google Scholar
  9. 9.
    Branco FC, Vianna JM, Lima JRP (2004) Frequência cardíaca na prescrição de treinamento de corredores de fundo. RBCM 12(2):75–79Google Scholar
  10. 10.
    Andreato LV, Branco BHM (2016) Different sports, but the same physical and physiological profiles? Sports Med 46(12):1963–1965. CrossRefPubMedGoogle Scholar
  11. 11.
    Øvretveit K (2019) Aerobic interval training improves maximal oxygen uptake and reduces body fat in grapplers. J Sports Med Phys Fit. (epub ahead of print) CrossRefGoogle Scholar
  12. 12.
    Andreato LV, Lara FJD, Andrade A, Branco BHM (2017) Physical and physiological profiles of brazilian jiu-jitsu athletes: a systematic review. Sports Med Open 3(1):3–9. CrossRefGoogle Scholar
  13. 13.
    Andreato LV, Julio UF, Panissa VL, Esteves JV, Hardt F, De Moraes SM, De Souza CO, Franchini E (2015) Brazilian jiu-jitsu simulated competition part I: metabolic, hormonal, cellular damage, and heart rate responses. J Strength Cond Res 29(9):2538–2549. CrossRefPubMedGoogle Scholar
  14. 14.
    Branco BHM, Andreato LV, Mendes AA, Gilio GR, Andrade A, Nardo-Júnior N (2016) Effects of a Brazilian jiu-jitsu training session on physiological, biochemical, hormonal and perceptive responses. Arch Budo Sci Martial Art 12:145–154Google Scholar
  15. 15.
    Branco BHM, Fukuda DH, Andreato LV, Santos JF, Esteves JV, Franchini E (2016) The effects of hyperbaric oxygen therapy on post-training recovery in jiu-jitsu athletes. PLoS One 11(3):0150517. CrossRefGoogle Scholar
  16. 16.
    Shannon SD, Gledhill BN, Jamnik VK, Warburton DE (2013) PAR-Q + and ePARmed-X + New risk stratification and physical activity clearance strategy for physicians and patients alike. Can Fam Physician 59(3):273–277 (PMID: 23486800) Google Scholar
  17. 17.
    World Anti-Doping Agency (WADA) (2017) The prohibited list. IOP Publishing Physics Web. Accessed 25 May 2017
  18. 18.
    Lohman TG, Roche AF, Martorell R (1988) Anthropometric standardization reference manual. Human Kinetics, ChampaignGoogle Scholar
  19. 19.
    Marfell-Jones MJ, Stewart AD, de Ridder JH (2012) International standards for anthropometric assessment. International Society for the Advancement of Kinanthropometry, WellingtonGoogle Scholar
  20. 20.
    Jackson AS, Pollock ML (1978) Generalized equations for predicting body density of men. Br J Nutr 40:497–504CrossRefPubMedGoogle Scholar
  21. 21.
    Siri WE (1961) Body composition from fluid spaces and density. In: Brozek J, Henschel A (eds) Techniques for measuring body composition. National Academy of Science, Washington, pp 223–244Google Scholar
  22. 22.
    Carter JEL, Heath BH (1990) Somatotyping: development and applications. Cambridge University Press, CambridgeGoogle Scholar
  23. 23.
    Laurent CM, Green JM, Bishop PA, Sjökvist J, Schumacker RE, Richardson MT, Curtner-Smith M (2011) A practical approach to monitoring recovery: development of a perceived recovery status scale. J Strength Cond Res 25(3):620–628. CrossRefPubMedGoogle Scholar
  24. 24.
    Borg GA (1982) Psychophysical bases of perceived exertion. Med Sci Sports Exerc 14:377–381PubMedGoogle Scholar
  25. 25.
    Cooke CB (2009) Maximal oxygen uptake, economy and efficiency. In: Eston R, Reilly T (eds) Kinanthropometry and exercise physiology laboratory manual tests, procedures and data, 3rd edn. Routledge, London, pp 174–212Google Scholar
  26. 26.
    Cooper KH (1968) A means of assessing maximal oxygen intake Correlation between field and treadmill testing. JAMA 203(3):201–204CrossRefPubMedGoogle Scholar
  27. 27.
    Marins JCB, Fernandez MD (2004) Comparação da frequência cardíaca máxima por meio de provas com perfil aeróbico e anaeróbico. Fit Perform J 3:166–174Google Scholar
  28. 28.
    Marins J (2003) Comparación de la frecuencia cardiaca máxima y fórmulas para su predicción. INEF Universidad de Granada, TeseGoogle Scholar
  29. 29.
    Tanaka H, Monahan KD, Seals DR (2001) Age-predicted maximal heart rate revisited. J Am Coll Cardiol 37(1):153–156CrossRefPubMedGoogle Scholar
  30. 30.
    Fox SM, Naughton JP, Haskell WL (1971) Physical activity and the prevention of coronary heart disease. Ann Clin Res 3:404–432PubMedGoogle Scholar
  31. 31.
    Karvonen JJ, Kentala E, Mustala OT (1957) The effects of training on the heart rate: a “longitudinal” study. Ann Med Exp Biol Fenn 35(3):307–315PubMedGoogle Scholar
  32. 32.
    Cohen J (1992) Quantitative methods in psychology. Psychol Bull 112(1):155–159CrossRefGoogle Scholar
  33. 33.
    Hopkins WG, Marshall SW, Batterham AM, Hanin J (2009) Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc 41(1):3–13. CrossRefPubMedGoogle Scholar
  34. 34.
    Franchini E (2010) Judô: desempenho competitivo. Manole, BarueriGoogle Scholar
  35. 35.
    Branco BHM, Silva JPL, Santos JFS, Julio UF, Panissa VLG, Franchini E (2017) Monitoring training during four weeks of three different modes of high-intensity interval training in judo athletes. Arch Budo 13:51–62Google Scholar
  36. 36.
    Zavorsky GS (2000) Evidence and possible mechanisms of altered maximum heart rate with endurance training and tapering. Sports Med 29:13–26. CrossRefPubMedGoogle Scholar
  37. 37.
    Bassett JDR, Howley ET (2000) Limiting factors for maximum oxygen uptake and determinants of endurance performance. Med Sci Sports Exerc 32:70–84. CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag Italia S.r.l., part of Springer Nature 2019

Authors and Affiliations

  • Braulio Henrique Magnani Branco
    • 1
    • 2
    • 3
    Email author
  • Fabiano de Oliveira Mendes
    • 1
    • 2
  • Gabriel Fassina Ladeia
    • 1
    • 2
  • Sônia Maria Marques Gomes Bertolini
    • 1
    • 2
    • 3
  • Pablo Valdés Badilla
    • 4
  • Leonardo Vidal Andreato
    • 2
  1. 1.University Center of Maringa (UniCesumar)MaringaBrazil
  2. 2.Research Group in Physical Education Physiotherapy, Sports, Nutrition and Performance (GEFFEND/UniCesumar)MaringaBrazil
  3. 3.Post-Graduation Program of Health Promotion of UniCesumarMaringaBrazil
  4. 4.Institute of Physical Activity and HealthUniversidad Autónoma de ChileProvidenciaChile

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