Observations of Player (de)Selection Within a Professional UK Soccer Academy

Rich J. Kite, Mark R. Noon, Rhys Morris, Peter Mundy, Neil D. Clarke

Journal of Science in Sport and Exercise ›› 2023, Vol. 6 ›› Issue (1) : 71-80. DOI: 10.1007/s42978-023-00222-3
Original Article

Observations of Player (de)Selection Within a Professional UK Soccer Academy

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Abstract

The present study engaged in an ethnographical observation of the processes used to determine player (de)selections within a professional academy. English category-2 youth academy players (n = 96) from U10–U16 age groups undertook anthropometric profiling (height, mass and somatic maturation) and fitness assessments (10 m, 20 m & 30 m linear sprints, 505-agility test, countermovement and squat jumps). Each players lead coach (n = 4) subjectively graded players utilising a red, amber and green (RAG) rating system on a weekly (current performance) and quarterly (perceived potential) basis, across 25 weeks. A MANCOVA, controlling for maturation, was applied to determine differences in (de)selection by physical performance. Mann Whitney-U tests were used to distinguish difference in (de)selection by subjective grading (weekly and quarterly). The key finding was that quarterly subjective gradings established a higher cumulative score of green ratings in selected players and a low cumulative score of red ratings, and vice versa for deselected players (P ≤ 0.001 to 0.03). However, whilst these findings suggest that quarterly subjective grades of potential were able to provide the best predictors for player (de)selection, the findings should be viewed with caution due to high potential for confirmatory bias.

Keywords

Coach intuition / Physiological / Performance grading / Maturation / Subjective assessment

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Rich J. Kite, Mark R. Noon, Rhys Morris, Peter Mundy, Neil D. Clarke. Observations of Player (de)Selection Within a Professional UK Soccer Academy. Journal of Science in Sport and Exercise, 2023, 6(1): 71‒80 https://doi.org/10.1007/s42978-023-00222-3

References

[1.]
Armstrong RA. When to use the Bonferroni correction. Ophthalmic Physiol Opt, 2014, 34(5): 502-508,
CrossRef Pubmed Google scholar
[2.]
Baker J, Schorer J, Wattie N. Compromising talent: issues in identifying and selecting talent in sport. Quest, 2018, 70: 48-63,
CrossRef Google scholar
[3.]
Barber OR, Thomas C, Jones PA, et al.. Reliability of the 505 change-of-direction test in netball players. Int J Sports Physiol Perform, 2016, 11(3): 377-380,
CrossRef Pubmed Google scholar
[4.]
Bidaurrazaga-Letona I, Lekue JA, Amado M, Gil SM. Progression in youth soccer: selection and identification in youth soccer players aged 13–15 years. J Strength Cond Res, 2019, 33(9): 2548-2558,
CrossRef Pubmed Google scholar
[5.]
Cohen J. . Statistical power analysis for the behavioral sciences, second, 1988 Hillsdale Lawrence Erlbaum Associates
[6.]
Cormack SJ, Newton RU, McGulgan MR, Doyle TLA. Reliability of measures obtained during single and repeated countermovement jumps. Int J Sports Physiol Perform, 2008, 3(2): 131-144,
CrossRef Pubmed Google scholar
[7.]
Cripps AJ, Hopper LS, Joyce C. Coaches’ perceptions of long-term potential are biased by maturational variation. Int J Sport Sci Coach, 2016, 11(4): 478-481,
CrossRef Google scholar
[8.]
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(2): 34-47,
CrossRef Google scholar
[9.]
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: 147-153,
CrossRef Google scholar
[10.]
Deprez DN, Fransen J, Lenoir M, et al.. A retrospective study on anthropometrical, physical fitness, and motor coordination characteristics that influence dropout, contract status, and first-team playing time in high-level soccer players aged eight to eighteen years. J Strength Cond Res, 2015, 29(6): 1692-1704,
CrossRef Pubmed Google scholar
[11.]
Dodd KD, Newans TJ. Talent identification for soccer: physiological aspects. J Sci Med Sport, 2018, 21(10): 1073-1078,
CrossRef Pubmed Google scholar
[12.]
Dugdale JH, McRobert AP, Unnithan VB. Selected, deselected, and reselected: a case study analysis of attributes associated with player reselection following closure of a youth soccer academy. Front Sport Act Living., 2021, 3: 633124,
CrossRef Google scholar
[13.]
Dugdale JH, Sanders D, Myers T, et al.. A case study comparison of objective and subjective evaluation methods of physical qualities in youth soccer players. J Sports Sci, 2020, 38(11–12): 1304-1312,
CrossRef Pubmed Google scholar
[14.]
Emmonds S, Till K, Jones B, et al.. Anthropometric, speed and endurance characteristics of English academy soccer players: do they influence obtaining a professional contract at 18 years of age?. Int J Sport Sci Coach, 2016, 11(2): 212-218,
CrossRef Google scholar
[15.]
Epstein LH, Valoski AM, Kalarchian MA, McCurley J. Do children lose and maintain weight easier than adults: a comparison of child and parent weight changes from six months to ten years. Obes Res, 1995, 3: 411-417,
CrossRef Pubmed Google scholar
[16.]
Field A. Effect Sizes Null Hypothesis Significance Testing (NHST). 2005. http://www.discoveringstatistics.com/docs/effectsizes.pdf. Accessed 7 July 2021.
[17.]
Fritz CO, Morris PE, Richler JJ. Effect size estimates: current use, calculations, and interpretation. J Exp Psychol Gen, 2012, 141(1): 2-18,
CrossRef Pubmed Google scholar
[18.]
Jennings D, Cormack S, Coutts AJ, et al.. The validity and reliability of GPS units for measuring distance in team sport specific running patterns. Int J Sports Physiol Perform, 2010, 5(3): 328-341,
CrossRef Pubmed Google scholar
[19.]
Jokuschies N, Gut V, Conzelmann A. Systematizing coaches’ ‘eye for talent’: Player assessments based on expert coaches’ subjective talent criteria in top-level youth soccer. Int J Sport Sci Coach, 2017, 12(5): 565-576,
CrossRef Google scholar
[20.]
Kelly AL, Williams CA. Physical characteristics and the talent identification and development processes in male youth soccer: a narrative review. Strength Cond J, 2020, 42(6): 15-34,
CrossRef Google scholar
[21.]
Khamis HJ, Roche AF. Predicting adult stature without using skeletal age: the Khamis-Roche method. Pediatrics, 1994, 94(4 Pt 1): 504-507,
CrossRef Pubmed Google scholar
[22.]
Lath F, Koopmann T, Faber I, et al.. Focusing on the coach’s eye; towards a working model of coach decision-making in talent selection. Psychol Sport Exerc, 2021, 56: 102011,
CrossRef Google scholar
[23.]
le Gall F, Carling C, Williams M, Reilly T. Anthropometric and fitness characteristics of international, professional and amateur male graduate soccer players from an elite youth academy. J Sci Med Sport, 2010, 13: 90-95,
CrossRef Pubmed Google scholar
[24.]
Lloyd RS, Oliver JL, Faigenbaum AD, et al.. Chronological age vs biological maturation. J Strength Cond Res, 2014, 28(5): 1454-1464,
CrossRef Pubmed Google scholar
[25.]
Lloyd RS, Oliver JL, Radnor JM, et al.. Relationships between functional movement screen scores, maturation and physical performance in young soccer players. J Sports Sci, 2014,
CrossRef Pubmed Google scholar
[26.]
Malina RM, Cumming SP, Morano PJ, et al.. Maturity status of youth football players: a noninvasive estimate. Med Sci Sports Exerc, 2005, 37(6): 1044-1052,
CrossRef Pubmed Google scholar
[27.]
Malina RM, Dompier TP, Powell JW, et al.. Validation of a noninvasive maturity estimate relative to skeletal age in youth football players. Clin J Sport Med, 2007, 17(5): 362-368,
CrossRef Pubmed Google scholar
[28.]
Meylan C, Cronin J, Oliver J, Hughes M. Talent identification in soccer: the role of maturity status on physical, physiological and technical characteristics. Int J Sport Sci Coach, 2010, 5(Suppl–1): 571-592,
CrossRef Google scholar
[29.]
Mirwald RL, Baxter-Jones ADG, Bailey DA, Beunen GP. An assessment of maturity from anthropometric measurements. Med Sci Sport Exerc, 2002, 34(4): 689-694,
CrossRef Google scholar
[30.]
Myburgh GK, Cumming SP, Silva CE, M,, et al.. Growth and maturity status of elite British junior tennis players. J Sports Sci, 2016, 34(20): 1957-1964,
CrossRef Pubmed Google scholar
[31.]
Nimphius S, Callaghan SJ, Bezodis NE, Lockie RG. Change of direction and agility tests: challenging our current measures of performance. Strength Cond J, 2018, 40(1): 26-38,
CrossRef Google scholar
[32.]
Nimphius S, Callaghan SJ, Spiteri T, Lockie RG. Change of direction deficit: a more isolated measure of change of direction performance than total 505 time. J Strength Cond Res, 2016, 30(11): 3024-3032,
CrossRef Pubmed Google scholar
[33.]
Patel R, Nevill A, Smith T, et al.. The influence of birth quartile, maturation, anthropometry and physical performances on player retention: observations from an elite football academy. Int J Sport Sci Coach, 2020, 15(2): 121-134,
CrossRef Google scholar
[34.]
Pion J, Lenoir M, Vandorpe B, Segers V. Talent in female gymnastics: a survival analysis based upon performance characteristics. Int J Sports Med, 2015, 36(11): 935-940,
CrossRef Pubmed Google scholar
[35.]
Premier League. Elite Player Performance Plan. 2011. http://www.premierleague.com/content/premierleague/en-gb/youth/elite-player-performance-plan.html. Accessed 15 Aug 2020.
[36.]
Reilly T, Williams AM, Nevill A, Franks A. A multidisciplinary approach to talent identification in soccer. J Sports Sci, 2000, 18: 695-702,
CrossRef Pubmed Google scholar
[37.]
Roberts A, Greenwood D, Stanley M, et al.. Understanding the “gut instinct” of expert coaches during talent identification. J Sports Sci, 2021, 39(4): 359-367,
CrossRef Pubmed Google scholar
[38.]
Roberts AH, Greenwood DA, Stanley M, et al.. Coach knowledge in talent identification: a systematic review and meta-synthesis. J Sci Med Sport, 2019, 22(10): 1163-1172,
CrossRef Pubmed Google scholar
[39.]
Rothwell M, Rumbold JL, Stone JA. Exploring British adolescent rugby league players’ experiences of professional academies and dropout. Int J Sport Exerc Psychol, 2020, 18(4): 485-501,
CrossRef Google scholar
[40.]
Shalfawi SAI, Enoksen E, Tønnessen E, Ingebrigtsen J. Assessing test-retest reliability of the portable brower speed trap II testing system. Assess TEST-RETEST Reliab, 2012, 44: 24-30
[41.]
Sieghartsleitner R, Zuber C, Zibung M, et al.. Talent selection in youth football: Specific rather than general motor performance predicts future player status of football talents. Curr Issues Sport Sci., 2019, 4: 1-14,
CrossRef Google scholar
[42.]
Sieghartsleitner R, Zuber C, Zibung M, Conzelmann A. Science or coaches’ eye? both! beneficial collaboration of multidimensional measurements and coach assessments for efficient talent selection in elite youth football. J Sport Sci Med, 2019, 18(1): 32-43
[43.]
Stewart PF, Turner AN, Miller SC. Reliability, factorial validity, and interrelationships of five commonly used change of direction speed tests. Scand J Med Sci Sport, 2014, 24(3): 500-506,
CrossRef Google scholar
[44.]
Till K, Baker J. Challenges and [possible] solutions to optimizing talent identification and development in sport. Front Psychol, 2020, 11: 1-14,
CrossRef Google scholar
[45.]
Towlson C, Cope E, Perry JL, et al.. Practitioners’ multi-disciplinary perspectives of soccer talent according to phase of development and playing position. Int J Sport Sci Coach, 2019, 14(4): 528-540,
CrossRef Google scholar
[46.]
Van Der Sluis A, Elferink-Gemser MT, Brink MS, Visscher C. Importance of peak height velocity timing in terms of injuries in talented soccer players. Int J Sports Med, 2015, 36: 327-332,
CrossRef Pubmed Google scholar
[47.]
Vandendriessche JB, Vaeyens R, Vandorpe B, et al.. Biological maturation, morphology, fitness, and motor coordination as part of a selection strategy in the search for international youth soccer players (age 15–16 years). J Sports Sci, 2012, 30(15): 1695-1703,
CrossRef Pubmed Google scholar

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