Bio-Banding in Youth Sports: Background, Concept, and Application


Inter-individual differences in size, maturity status, function, and behavior among youth of the same chronological age (CA) have long been a concern in grouping for sport. Bio-banding is a recent attempt to accommodate maturity-associated variation among youth in sport. The historical basis of the concept of maturity-matching and its relevance to youth sport, and bio-banding as currently applied are reviewed. Maturity matching in sport has often been noted but has not been systematically applied. Bio-banding is a recent iteration of maturity matching for grouping youth athletes into ‘bands’ or groups based on characteristic(s) other than CA. The percentage of predicted young adult height at the time of observation is the estimate of maturity status of choice. Several applications of bio-banding in youth soccer have indicated positive responses from players and coaches. Bio-banding reduces, but does not eliminate, maturity-associated variation. The potential utility of bio-banding for appropriate training loads, injury prevention, and fitness assessment merits closer attention, specifically during the interval of pubertal growth. The currently used height prediction equation requires further evaluation.

This is a preview of subscription content, log in to check access.

Fig. 1


  1. 1.

    Although Crampton is given credit for coining the term “physiological age”, he indicated that the credit “…properly belongs to … Franz Boas, who, with G. Stanley Hall and Luther H. Gulick, gave the author [Crampton] the encouragement of their approval and interest” (p. 52) [92]. Boas was an anthropologist with a primary interest in the study of growth and especially adolescence, Hall was a psychologist who focused on adolescence, and Gulick was a physician active in school physical education and physical training.

  2. 2.

    Krogman worked under the direction of T.W. Todd at Western Reserve University in Cleveland in the 1930s; skeletal maturity was likely assessed with the atlas method of Todd [27], which was in the process of development at this time.


  1. 1.

    Cumming SP, Lloyd RS, Oliver JL, et al. Bio-banding in sport: applications to competition, talent identification, and strength and conditioning of youth athletes. Strength Cond J. 2017;39:34–47.

    Google Scholar 

  2. 2.

    Horrocks JE. The psychology of adolescence: behavior and development. Cambridge: Houghton Mifflin; 1951.

    Google Scholar 

  3. 3.

    Tanner JM. Growth at adolescence. 2nd ed. Oxford: Blackwell; 1962.

    Google Scholar 

  4. 4.

    Beunen G (1989) Biological age in pediatric research. In: Bar-Or O (ed) Advances in pediatric sports sciences. Biological issues, Vol. 3. Champaign: Human Kinetics, pp. 1–39.

  5. 5.

    Beunen G, Malina RM. Growth and physical performance relative to the timing of the adolescent spurt. Exerc Sport Sci Rev. 1988;16:503–40.

    CAS  PubMed  Google Scholar 

  6. 6.

    Malina RM. Physical growth and biological maturation of young athletes. Exerc Sports Sci Rev. 1994;22:389–433.

    CAS  Google Scholar 

  7. 7.

    Malina RM, Bouchard C, Bar-Or O. Growth, maturation, and physical activity. 2nd ed. Champaign: Human Kinetics; 2004.

    Google Scholar 

  8. 8.

    Malina RM, Beunen G. Matching of opponents in youth sports. In: Bar-Or O, editor. The child and adolescent athlete. Oxford: Blackwell Science; 1996. p. 202–13.

    Google Scholar 

  9. 9.

    Beunen G, Malina RM. Growth and biologic maturation: relevance to athletic performance. In: Hebestreit H, Bar-Or O, editors. The young athlete. Malden: Blackwell Publishing; 2008. p. 3–17.

    Google Scholar 

  10. 10.

    Malina RM. Skeletal age and age verification in youth sport. Sports Med. 2011;41:925–47.

    PubMed  PubMed Central  Google Scholar 

  11. 11.

    Young GM, Hancock WD (eds) Factories regulation act, 1833. English historical documents, XII(1), 1833–1874. New York: Oxford University Press; 1956. p. 949–52 (see also The Factory Act 1833,, accessed 16 Jan 2019).

  12. 12.

    Saunders E. Teeth as a test of age considered with reference to the factory children: addressed to the members of both houses of parliament. London: H Renshaw; 1837.

    Google Scholar 

  13. 13.

    Saunders E. The teeth as a test of age. Lancet. 1938;30(774):492–6.

    Google Scholar 

  14. 14.

    Crampton CW. Pubescence: a preliminary report. Am Anthropol. 1904;6:705–9.

    Google Scholar 

  15. 15.

    Crampton CW. The influence of physiological age upon scholarship. Psychol Clin. 1907;1(4):115–20.

    PubMed  PubMed Central  Google Scholar 

  16. 16.

    Crampton CW. Anatomical or chronological age: versus chronological age. Pedagogical Semin. 1908;15:230–7.

    Google Scholar 

  17. 17.

    Crampton CW. Physiological age—a fundamental principle. Am Phys Educ Rev. 1908;13:141–54.

    Google Scholar 

  18. 18.

    Rotch TM. Chronological and anatomical age early in life. JAMA. 1908;51:1197–205.

    Google Scholar 

  19. 19.

    Rotch TM. A study of the development of the bones in childhood by the roentgen method, with the view of establishing a developmental index for the grading of and the protection of early life. Trans Assoc Am Physicians. 1909;24:603–24.

    Google Scholar 

  20. 20.

    Foster WL. Physiological age as a basis for the classification of pupils entering high schools—relation of pubescence to height. Psychol Clin. 1910–1911;4:83–8.

  21. 21.

    Baldwin BT. A measuring scale for physical growth and physiological age. Fifteenth yearbook of the National Society for the Study of Education, Part 1. Bloomington:Public School Publishing Company; 1916. p. 11–23.

  22. 22.

    Baldwin BT. The physical growth of children from birth to maturity. University of Iowa Studies in Child Welfare, Vol. 1. Iowa City: The University; 1921. p. 1–411.

  23. 23.

    Dimock HS. A research in adolescence. 1. Pubescence and physical growth. Child Develop. 1935;6:177–95.

    Google Scholar 

  24. 24.

    Dimock HS. Rediscovering the adolescent: a study of personality development in adolescent boys. New York: Association Press; 1937.

    Google Scholar 

  25. 25.

    Rotch TM, Smith HW. A study of the development of the epiphyses of the hand and wrist for the purpose of classifying cadets at Annapolis. Trans Assoc Am Physicians. 1910;25:200–10.

    Google Scholar 

  26. 26.

    Smith HW. Rotch method of roentgenographic age determination. US Naval Med Bull. 1913;7:1–20.

    Google Scholar 

  27. 27.

    Todd TW. Atlas of skeletal maturation. St. Louis: Mosby; 1937.

    Google Scholar 

  28. 28.

    American Association for Health, Physical Education and Recreation. Desirable athletic competition for children: joint committee report. Washington, DC: American Association for Health Physical Education and Recreation; 1952.

  29. 29.

    Stotz CE, Baldwin MW. At bat with Little League. Philadelphia: Macrae Smith Company; 1952.

    Google Scholar 

  30. 30.

    Hale CJ. Physiologic maturity of Little League baseball players. Res Q. 1956;27:276–84.

    Google Scholar 

  31. 31.

    Krogman WM. Maturation age of 55 boys in the little league world series, 1957. Res Q. 1959;30:54–6.

    Google Scholar 

  32. 32.

    Malina RM. Biological maturity status of young athletes. In: Malina RM, editor. Young athletes: biological, psychological and educational perspectives. Champaign: Human Kinetics; 1988. p. 121–40.

    Google Scholar 

  33. 33.

    Malina RM, Coelho-e-Silva MJ, Figueiredo AJ. Growth and maturity status of youth players. In: Williams AM, editor. Science and soccer: developing elite performers. 3rd ed. Abington: Routledge; 2013. p. 307–32.

    Google Scholar 

  34. 34.

    Beunen GP, Rogol AD, Malina RM. Indicators of biological maturation and secular changes in biological maturation. Food Nutr Bull. 2006;27:S244–56.

    PubMed  Google Scholar 

  35. 35.

    Malina RM, Coelho-e-Silva MJ, Figueiredo AJ, et al. Tanner-Whitehouse skeletal ages in male youth soccer players: TW2 or TW3? Sports Med. 2018;48:991–1008.

    PubMed  Google Scholar 

  36. 36.

    Malina RM. Assessment of biological maturation. In: Armstrong N, van Mechelen W, editors. Oxford textbook of children’s exercise science and medicine. Oxford: Oxford University Press; 2017. p. 3–11.

    Google Scholar 

  37. 37.

    Van Wieringen JC, Wafelbakker F, Verbrugge HP, De Haas JH. Growth diagrams 1965 Netherlands. Groningen: Wolters-Noordhoof Publishing; 1971.

    Google Scholar 

  38. 38.

    Roche AF, Wellens R, Attie KM, Siervogel RM. The timing of sexual maturation in a group of US White youths. J Pediatr Endocrinol Metab. 1995;8:11–8.

    CAS  PubMed  Google Scholar 

  39. 39.

    Roche AF, Tyleshevski F, Rogers E. Non-invasive measurement of physical maturity in children. Res Q Exerc Sport. 1983;54:364–71.

    Google Scholar 

  40. 40.

    Malina RM. Top 10 research questions related to growth and maturation of relevance to physical activity, performance, and fitness. Res Q Exerc Sport. 2014;85:157–73.

    PubMed  Google Scholar 

  41. 41.

    Nicolson AB, Hanley C. Indices of physiological maturity: deviation and interrelationships. Child Dev. 1953;24:3–38.

    CAS  PubMed  Google Scholar 

  42. 42.

    Bielicki T, Koniarek J, Malina RM. Interrelationships among certain measures of growth and maturation rate in boys during adolescence. Ann Hum Biol. 1984;11:201–10.

    CAS  PubMed  Google Scholar 

  43. 43.

    Bielicki T. Interrelationships between various measures of maturation rate in girls during adolescence. Stud Phys Anthrop. (Wrocław, Poland). 1975;1:51–64.

  44. 44.

    Malina RM, Rogol AD, Cumming SP, et al. Biological maturation of youth athletes: assessment and implications. Br J Sports Med. 2015;49:852–9.

    PubMed  PubMed Central  Google Scholar 

  45. 45.

    Mirwald RL, Baxter-Jones ADG, Bailey DA, Beunen GP. An assessment of maturity from anthropometric measurements. Med Sci Sports Exerc. 2002;34:689–94.

    PubMed  Google Scholar 

  46. 46.

    Moore SA, McKay HA, Macdonald H, et al. Enhancing a somatic maturity prediction model. Med Sci Sports Exerc. 2015;47:1755–64.

    PubMed  Google Scholar 

  47. 47.

    Malina RM, Kozieł SM. Validation of maturity offset in a longitudinal sample of Polish boys. J Sports Sci. 2014;32:424–37.

    PubMed  Google Scholar 

  48. 48.

    Malina RM, Kozieł SM. Validation of maturity offset in a longitudinal sample of Polish girls. J Sports Sci. 2014;32:1374–82.

    PubMed  Google Scholar 

  49. 49.

    Kozieł SM, Malina RM. Modified maturity offset prediction equations: validation in independent longitudinal samples of boys and girls. Sports Med. 2018;48:221–36.

    PubMed  Google Scholar 

  50. 50.

    Malina RM, Choh AC, Czerwinski SA, Chumlea WC. Validation of maturity offset in the Fels longitudinal Study. Pediatr Exerc Sci. 2016;28:439–55.

    PubMed  Google Scholar 

  51. 51.

    ESPN. Little League’s change in age requirement takes effect in 2018. 11 Sep 2015. Accessed 17 Jan 2019.

  52. 52.

    Ferguson A. Leading. London: Hoddler and Stoughton; 2015.

    Google Scholar 

  53. 53.

    Price RJ, Hawkins RD, Hulse MA, et al. The Football Association medical research programme: an audit of injuries in academy youth football. Br J Sports Med. 2004;38:466–71.

    CAS  PubMed  PubMed Central  Google Scholar 

  54. 54.

    Weigerinck JI, Yntema C, Brouwer HJ, Struijs PAA. Incidence of calcaneal apophysitis in the general population. Eur J Pediatr. 2014;173:677–9.

    Google Scholar 

  55. 55.

    Gholve PA, Scher DM, Khakharia S, et al. Osgood Schlatter syndrome. Curr Opin Pediatr. 2007;19:44–50.

    Google Scholar 

  56. 56.

    Willie MC. Revised maturity and physical fitness standards for the selection/classification screening procedures: the selection/classification program procedures for implementation of the regulations of the Commissioner of Education regarding athletic eligibility standards for pupils of advanced or delayed maturity. Albany: University of the State of New York; 1982.

  57. 57.

    University of the State of New York. Athletic placement process for interschool athletic programs. Albany: University of the State of New York, New York State Education Department, Office of Curriculum and Instruction; 2015.

  58. 58.

    University Interscholastic League. 2018–2019 junior high school athletics coaches manual. Austin: University Interscholastic League; 2018.

    Google Scholar 

  59. 59.

    Iowa High School Athletic Association. Junior high sports manual. Boone: Iowa High School Athletic Association; 2017.

    Google Scholar 

  60. 60.

    Bayley N, Pinneau SR. Tables for predicting adult height from skeletal age: revised for use with the Greulich-Pyle hand standards. J Pediatr 1952;423–41.

    CAS  PubMed  Google Scholar 

  61. 61.

    Bayer LM, Bayley N. Growth diagnosis: selected methods for interpreting and predicting development from 1 year to maturity. Chicago: University of Chicago Press; 1959.

    Google Scholar 

  62. 62.

    Roche AF, Wainer H, Thissen D. The RWT method for the prediction of adult stature. Pediatrics. 1975;56:1026–33.

    Google Scholar 

  63. 63.

    Roche AF, Wainer H, Thissen D. Predicting adult stature for individuals. Monographs in Paediatrics 3. Basel: Karger; 1975.

  64. 64.

    Khamis HJ, Guo S. Improvement in the Roche–Wainer–Thissen stature prediction model: a comparative study. Am J Hum Biol. 1993;5:669–79.

    CAS  PubMed  Google Scholar 

  65. 65.

    Tanner JM, Whitehouse RH, Cameron N, et al. Assessment of skeletal maturity and prediction of adult height. 2nd ed. New York: Academic Press; 1983.

    Google Scholar 

  66. 66.

    Tanner JM, Healy MJR, Goldstein H, et al. Assessment of skeletal maturity and prediction of adult height (TW3 method). 3rd ed. London: Saunders; 2001.

    Google Scholar 

  67. 67.

    Khamis HJ, Roche AF. Predicting adult stature without using skeletal age: the Khamis–Roche method. Pediatrics 1994; 94: 504–7 [Erratum in Pediatrics 1995;95:457 (corrected tables)].

  68. 68.

    Roche AF. Growth, maturation and body composition: the Fels Longitudinal Study 1929–1991. Cambridge: Cambridge University Press; 1992.

    Google Scholar 

  69. 69.

    Cumming SP, Brown DJ, Mitchell S, et al. Premier League academy soccer players’ experiences of competing in a tournament bio-banded for biological maturation. J Sports Sci. 2018;36:757–65.

    PubMed  Google Scholar 

  70. 70.

    Cumming SP, Searle C, Hemsley JK, et al. Biological maturation, relative age and self-regulation in male professional academy soccer players: a test of the underdog hypothesis. Psychol Sport Exerc. 2018;39:147–53.

    Google Scholar 

  71. 71.

    Thomas CH. A pilot study of the demands of chronological age group and bio-banded match play in elite youth soccer [dissertation]. Cardiff: Cardiff Metropolitan University, Cardiff School of Sport; 2017.

    Google Scholar 

  72. 72.

    Thomas CH, Oliver J, Kelly A, Knapman H. A pilot study of the demands of chronological age group and bio-banded match play in elite youth soccer [poster]. British Assoc Sports Exerc Sci, University of St Mark and St John, Plymouth, Devon, 12–13 Apr 2017.

  73. 73.

    Bradley B, Johnson D, Hill M, et al. Bio-banding in academy football: player’s perceptions of a maturity matched tournament. Ann Hum Biol. 2019.

    Article  PubMed  Google Scholar 

  74. 74.

    Preece MA. Prediction of adult height: methods and problems. Acta Paediatr Scand Suppl. 1988;347:4–11.

    CAS  PubMed  Google Scholar 

  75. 75.

    Cumming SP, Hill M, Mitchell SB. US Soccer: bio-banded tournament report. Bath: University of Bath; 2018.

  76. 76.

    Roche AF, Chumlea WC, Thissen D. Assessing the skeletal maturity of the hand-wrist: Fels method. Springfield: CC Thomas; 1988.

    Google Scholar 

  77. 77.

    Malina RM, Dompier TP, Powell JW, et al. Validation of a noninvasive maturity estimate relative to skeletal age in youth football players. Clin J Sports Med. 2007;17:362–8.

    Google Scholar 

  78. 78.

    Malina RM, Coelho e Silva MJ, Figueiredo AJ, et al. Interrelationships among invasive and non-invasive indicators of biological maturation in adolescent male soccer players. J Sports Sci 2012;30:1705–17.

    PubMed  Google Scholar 

  79. 79.

    Bunce J. The future of soccer in the United States, part 3: high performance [paper]. US Soccer conference—US Soccer Coaches Convention; 9–13 Jan 2019; Chicago.

  80. 80.

    Malina RM, Cumming SP, Morano PJ, et al. Maturity status of youth football players: a noninvasive estimate. Med Sci Sports Exerc. 2005;37:1044–52.

    PubMed  Google Scholar 

  81. 81.

    Figueiredo AJ, Gonçalves CE, Coelho-e-Silva MJ, Malina RM. Youth soccer players, 11–14 years: maturity, size, function, skill and goal orientation. Ann Hum Biol. 2009;36:60–73.

    PubMed  Google Scholar 

  82. 82.

    Sanders JO, Qiu A, Lu X, et al. The uniform pattern of growth and skeletal maturation during the human adolescent growth spurt. Sci Rep. 2017;7:16075.

    CAS  Article  Google Scholar 

  83. 83.

    Molinari L, Gasser T, Largo R. A comparison of skeletal maturity and growth. Ann Hum Biol. 2013;40:333–40.

    PubMed  Google Scholar 

  84. 84.

    Tillmann V, Clayton PE. Diurnal variation in height and the reliability of height measurements using stretched and unstretched techniques in the evaluation of short term growth. Ann Hum Biol. 2001;28:195–206.

    CAS  PubMed  Google Scholar 

  85. 85.

    Cole TJ. Seasonality of growth. In: Ulijaszek SJ, Johnston FE, Preece MA, editors. The Cambridge encyclopedia of human growth and development. Cambridge: Cambridge University Press; 1998. p. 223.

    Google Scholar 

  86. 86.

    Coelho-e-Silva SJ, Figueiredo AJ, Simões F, et al. Discrimination of U-14 soccer players by level and position. Int J Sports Med. 2010;31:390–6.

    Google Scholar 

  87. 87.

    Huijgen BCH, Elferink-Gemser MT, Lemmink KAPM, Visscher C. Multidimensional performance characteristics in selected and deselected talented soccer players. Eur J Sport Sci. 2010;14:2–10.

    Google Scholar 

  88. 88.

    Figueiredo AJ, Goncalves CE, Coelho-e-Silva MJ, Malina RM. Characteristics of youth soccer players who drop out, persist or move up. J Sports Sci. 2009;27:883–91.

    PubMed  Google Scholar 

  89. 89.

    Figueiredo AJ, Coelho-e-Silva MJ, Cumming SP, Malina RM. Relative age effect: characteristics of youth soccer players by birth quarter and subsequent playing status. J Sports Sci. 2019;37:677–84.

    PubMed  Google Scholar 

  90. 90.

    Johnson A, Farooq A, Whiteley R. Skeletal maturation status is more strongly associated with academy selection than birth quarter. Sci Med Football. 2017;1:157–63.

    Google Scholar 

  91. 91.

    Mann DL, van Ginneken PJMA. Age-ordered shirt numbering reduces the selection bias associated with the relative age effect. J Sports Sci 2017;784–90.

    PubMed  Google Scholar 

  92. 92.

    Crampton CW. Statement of C. W. Crampton, M.D. Child Develop. 1944;15:52 (this number of the journal includes a reprint of Crampton [17]: Physiological age: a fundamental principle. Child Develop. 1944;15:3–51.

    Google Scholar 

Download references

Author information



Corresponding author

Correspondence to Robert M. Malina.

Ethics declarations


No funding was provided to any of the authors for this review. The research on Portuguese youth soccer players used in several tables was supported in part by Fundação para Ciência e a Tecnologia.

Conflict of interest

Robert Malina, Alan Rogol, Manuel Coelho-e-Silva, Antonio Figueiredo, Jan Konarski, and Sławomir Kozieł declare that they have no conflicts of interest. Sean Cumming has worked in research and consultancy roles with the Premier League, the English Football Association, the Lawn Tennis Association, and British Gymnastics.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Malina, R.M., Cumming, S.P., Rogol, A.D. et al. Bio-Banding in Youth Sports: Background, Concept, and Application. Sports Med 49, 1671–1685 (2019).

Download citation