تدوین الگوی مدیریت استعدادیابی ورزش فوتبال مبتنی بر فناوری های نوین

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مدیریت ورزشی، دانشکده تربیت بدنی و علوم ورزشی، دانشگاه تبریز، تبریز، ایران

2 دانشیار مدیریت ورزشی، دانشکده تربیت بدنی و علوم ورزشی، دانشگاه تبریز، تبریز، ایران

چکیده

شناسایی استعداد در فوتبال مدرن به‌طور فزاینده‌ای متکی به فناوری‌های نوظهور شده است، در حالی که آکادمی‌های فوتبال ایران عمدتا از ارزیابی‌های ذهنی مربیان استفاده می‌کنند. در این راستا هدف این پژوهش توسعه چارچوبی مبتنی بر فناوری برای مدیریت شناسایی استعداد در فوتبال ایران است. در پژوهش حاضر از روش ترکیبی دو‌مرحله‌ای استفاده شد بگونه‌ای که ابتدا روش دلفی برای ایجاد اجماع نظری میان خبرگان و سپس روش دیمتل کلاسیک برای تحلیل ساختاری به کار گرفته شد. پنل کارشناسان و خبرگان شامل 15 مربی و مدیر فنی مرد با حداقل پنج سال سابقه در شناسایی استعدادهای جوان فوتبال بود که با نمونه‌گیری هدفمند انتخاب شدند. در روش دلفی، بیست مولفه اولیه تحقیق از بازبینی نظام‌مند متون علمی در پایگاه‌های بین‌المللی گوگل اسکولار، اسکپوس و پاپمد در بازه زمانی 2020–2025 استخراج شد و در روش دلفی به‌عنوان مولفه‌های اولیه قرار داده شد. براساس روش دلفی در سومین که آخرین دور اجماع نظری روی مولفه‌ها بود، بر 10 مولفه نهایی اجماع نظری حاصل شد. پس از بدست آوردن عوامل پژوهش با استفاده از روش دلفی، مولفه‌ها در جریان روش دیمیتل مورد تحلیل قرار گرفت تا تاثیرگذاری وتاثیرپذیری مولفه‌ها و همچنین الگوی داده‌ها بدست آید. یافته‌های حاصله، نشان دادند که وضعیت بلوغ زیستی قوی‌ترین عامل بود و پس از آن توان انفجاری و پوشش ادراکی–حسی به‌عنوان عوامل محرک شناخته شدند. این اولویت‌بندی مبتنی بر شواهد نشان می‌دهد که شناسایی استعداد نیازمند ارزیابی پی‌درپی مبانی زیستی پیش از توانایی‌های فنی–تاکتیکی است. چنین ساختار علّی‌ای رویکردی نظام‌مند در اختیار آکادمی‌های فوتبال ایران می‌گذارد تا سوگیری‌های ذهنی را کاهش دهد و از نادیده گرفته شدن استعدادهای دیررس در مراحل اولیه گزینش جلوگیری کنند.

کلیدواژه‌ها

عنوان مقاله [English]

Developing a framework for football talent identification and management based on emerging technologies

نویسندگان [English]

  • Vajiheh Javani 1
  • Kazem Mahmoudi 1
  • Mohammad Rasoul Khodadadi 2
1 Department of Sports Management, Faculty of Sports Sciences, University of Tabriz, Tabriz, Iran.
2 Department of Sport Management, Faculty of Physical Education and Sport Sciences, University of Tabriz, Tabriz,
چکیده [English]

Modern football talent identification increasingly relies on emerging technologies, yet Iranian football academies continue to use primarily subjective coach assessments. This study developed a technology-based framework for football talent identification management in Iran. A two-phase quantitative approach was employed, utilizing the Delphi method for consensus building followed by classical DEMATEL for structural analysis. The expert panel comprised 15 male coaches and technical managers with minimum five years of experience in youth football talent identification, selected through purposive sampling. Twenty initial components were extracted from systematic literature review of international databases (Scopus, PubMed, Google Scholar) covering 2020-2025. Through three Delphi rounds, consensus was reached on ten final components measured on a four-point Likert scale, which were then analyzed using DEMATEL pairwise comparison matrices. Data analysis employed SPSS for Delphi consensus metrics and Excel for DEMATEL calculations including normalized matrices and total influence matrix. Results revealed a hierarchical causal system where biological maturation status emerged as the strongest causal factor with relationship index of 2.2744, followed by explosive power and perceptual-sensory coverage as driving factors. Speed splits demonstrated highest prominence (R+C=6.5774) as a central mediating variable, while passing accuracy, interpersonal interactions, and internal load indices functioned as effect factors. The framework provides evidence-based prioritization showing talent identification requires sequential assessment of biological foundations before technical-tactical abilities. This causal structure offers Iranian football academies a systematic approach to reduce subjective bias and prevent overlooking late-maturing talents during early selection stages.

کلیدواژه‌ها [English]

  • Sports talent identification
  • football
  • emerging technologies
  • AI

مراجع

Alvares, P.D., Chaves, P.J., Oliveira Junior, M.N.S.D., Fernandes, T.L.B., Veneroso, C.E. & Cabido, C.E.T. (2020). Efeitos da puberdade no desempenho de saltos e sprints em jogadores jovens de futsal. Revista Brasileira de Medicina do Esporte, 26, 167-171. https://doi.org/10.1590/1517-869220202602215518
Cao, S. (2024). Passing path predicts shooting outcome in football. Scientific Reports, 14(1), 9572. https://doi.org/10.1038/s41598-024-60183-7.
Cardoso, F.D.S.L., Afonso, J., Roca, A. & Teoldo, I. (2021). The association between perceptual-cognitive processes and response time in decision making in young soccer players. Journal of Sports Sciences, 39(8), 926–935. https://doi.org/10.1080/02640414.2020.1851901
Coutinho, D., Kelly, A.L., Santos, S., Figueiredo, P., Pizarro, D. & Travassos, B. (2023). Exploring the effects of tasks with different decision-making levels on ball control, passing performance, and external load in youth football. Children (Basel, Switzerland), 10(2), 220. https://doi.org/10.3390/children10020220
Criollo-C, S., González-Rodríguez, M., Guerrero-Arias, A., Urquiza-Aguiar, L.F. & Luján-Mora, S. (2024). A review of emerging technologies and their acceptance in higher education. Education Sciences, 14(1), 10. https://doi.org/10.3390/educsci14010010
de Haan, M., van der Zwaard, S., Sanders, J., Beek, P.J. & Jaspers, R.T. (2025). Classifying soccer players based on physical capacities and match-specific running performance using machine learning. Journal of Sports Science & Medicine, 24(4), 764–778. https://doi.org/10.52082/jssm.2025.764
Dolson, C.M., Harlow, E.R., Phelan, D.M., Gabbett, T.J., Gaal, B., McMellen, C., Geletka, B.J., Calcei, J.G., Voos, J.E. & Seshadri, D.R. (2022). Wearable sensor technology to predict core body temperature: a systematic review. Sensors (Basel, Switzerland), 22(19), 7639.https://doi.org/10.3390/s22197639
Dudley, C., Johnston, R., Jones, B., Till, K., Westbrook, H. & Weakley, J. (2023). Methods of monitoring internal and external loads and their relationships with physical qualities, injury, or illness in adolescent athletes: a systematic review and best-evidence synthesis. Sports Medicine (Auckland, N.Z.), 53(8), 1559–1593. https://doi.org/10.1007/s40279-023-01844-x
Fortin-Guichard, D., Huberts, I., Sanders, J., van Elk, R., Mann, D.L. & Savelsbergh, G.J.P. (2022). Predictors of selection into an elite level youth football academy: A longitudinal study. Journal of Sports Sciences, 40(9), 984–999. https://doi.org/10.1080/02640414.2022.2044128
Foster, G., O'Reilly, N. & Naidu, Z. (2021). Playing-side analytics in team sports: multiple directions, opportunities, and challenges. Frontiers in Sports and Active Living, 3, 671601. https://doi.org/10.3389/fspor.2021.671601.
Garrido, D., Antequera, D.R., Campo, R.L.D., Resta, R. & Buldú, J.M. (2021). Distance between players during a soccer match: the influence of player position. Frontiers in Psychology, 12, 723414. https://doi.org/10.3389/fpsyg.2021.723414
Giblin, G., Tor, E. & Parrington, L. (2016). The impact of technology on elite sports performance. Sensoria: A Journal of Mind, Brain & Culture, 12(2). https://doi.org/10.7790/SA.V12I2.436
Guardian, S.T. (2024). Once upon a time in the West Country: the origin story of Ollie Watkins. https://www.theguardian.com/football/article/2024/jul/11/once-upon-a-time-in-the-west-country-the-origin-story-of-ollie-watkins
Hill, M., Scott, S., Malina, R.M., McGee, D. & Cumming, S.P. (2020). Relative age and maturation selection biases in academy football. Journal of Sports Sciences, 38(11-12), 1359–1367. https://doi.org/10.1080/02640414.2019.1649524
Holienka, M., Mikulič, M., Kováč, K., Schlossár, M., Mokrý, P. & Babic, M. (2025). Speed ability of youth soccer players in the match. Journal of Physical Education & Sport, 25(3). https://doi.org/10.7752/jpes.2025.03069
Jeras, N.M.J., Bovend'Eerdt, T.J.H. & McCrum, C. (2020). Biomechanical mechanisms of jumping performance in youth elite female soccer players. Journal of Sports Sciences, 38(11-12), 1335–1341. https://doi.org/10.1080/02640414.2019.1674526
Johnston, K., Wattie, N., Schorer, J. & Baker, J. (2018). Talent identification in sport: a systematic review. Sports medicine (Auckland, N.Z.), 48(1), 97–109. https://doi.org/10.1007/s40279-017-0803-2
King, M., Brown, M., Cox, J., McLellan, R., Towlson, C. & Barrett, S. (2024). Talent identification in soccer: The influence of technical, physical and maturity-related characteristics on a national selection process. PloS One, 19(3), e0298359. https://doi.org/10.1371/journal.pone.0298359
Lames, M., Hermann, S., Prüßner, R. & Meth, H. (2021). Football match dynamics explored by recurrence analysis. Frontiers in Psychology, 12, 747058. https://doi.org/10.3389/fpsyg.2021.747058
Liu, Z. (2024). Construction and optimization of sports athlete selection and talent cultivation system based on data analysis. Journal of Electrical Systems, 20(6s), 2070-2081. https://doi.org/10.52783/jes.3122
Malina, R.M., Bouchard, C. & Bar-Or, O. (2004). Growth, maturation, and physical activity. Human kinetics. https://doi.org/10.5040/9781492596837
Mead, J., O’Hare, A. & McMenemy, P. (2023). Expected goals in football: Improving model performance and demonstrating value. PloS One, 18(4), e0282295.
Milosavljević, V., Kitanović, V., Milošević, M. & Rajković, Ž. (2025). Predictive model of career success of young elite football players. Journal of Applied Sports Sciences, 9, 115-136.
Munoz-Macho, A.A., Domínguez-Morales, M.J. & Sevillano-Ramos, J.L. (2024). Performance and healthcare analysis in elite sports teams using artificial intelligence: a scoping review. Frontiers in Sports and Active Living, 6, 1383723. https://doi.org/10.3389/fspor.2024.1383723
Nosek, P., Brownlee, T.E., Drust, B. & Andrew, M. (2021). Feedback of GPS training data within professional English soccer: a comparison of decision making and perceptions between coaches, players and performance staff. Science & Medicine in Football, 5(1), 35–47. https://doi.org/10.1080/24733938.2020.1770320
Okoli, C. & Pawlowski, S.D. (2004). The Delphi method as a research tool: an example, design considerations and applications. Information & Management, 42(1), 15-29. https://doi.org/10.1016/j.im.2003.11.002
Sánchez-Sánchez, J., Botella, J., Felipe Hernández, J.L., León, M., Paredes-Hernández, V., Colino, E., Gallardo, L. & García-Unanue, J. (2021). Heart rate variability and physical demands of in-season youth elite soccer players. International Journal of Environmental Research and Public Health, 18(4), 1391. https://doi.org/10.3390/ijerph18041391
Schulze, E., Julian, R. & Skorski, S. (2021). The accuracy of a low-cost GPS system during football-specific movements. Journal of Sports Science & Medicine, 20(1), 126–132. https://doi.org/10.52082/jssm.2021.126
Sieghartsleitner, R., Zuber, C., Zibung, M. & Conzelmann, A. (2019). Science or coaches' eye? - both! beneficial collaboration of multidimensional measurements and coach assessments for efficient talent selection in elite youth football. Journal of Sports Science & Medicine, 18(1), 32–43.
Tahmasbpourshafiei, M., Razavi, S.M.H., Amirnejad, S., Dousti, M. & Hosseini, S.E. (2025). Developing a comprehensive management model to identify iranian football talent. Sport Management Journal, 17(1), 44-19. https://doi.org/10.22059/jsm.2021.311639.2595. [In Persian]
Vrban, R. (2021). Development of prediction model for support in decision-making process in football academies–literature review. In 34th Bled Conference Digital Support from Crisis to Progressive Change: Conference Proceedings (pp. 789-795).
Wang, B., Wan, B., Chen, S., Zhang, Y., Bai, X., Xiao, W., Tang, C. & Long, B. (2024). A systematic review of the factors that affect soccer players' short-passing ability-based on the loughborough soccer passing test. BMC Sports Science, Medicine & Rehabilitation, 16(1), 96. https://doi.org/10.1186/s13102-024-00880-y.
Welch, M., Schaerf, T.M. & Murphy, A. (2021). Collective states and their transitions in football. PloS One, 16(5), e0251970. https://doi.org/10.1371/journal.pone.0251970
Wrona, H.L., Zerega, R., King, V.G., Reiter, C.R., Odum, S., Manifold, D., Latorre, K. & Sell, T.C. (2023). Ability of countermovement jumps to detect bilateral asymmetry in hip and knee strength in elite youth soccer players. Sports (Basel, Switzerland), 11(4), 77. https://doi.org/10.3390/sports11040077
Zou, Y., Kuek, F., Feng, W. & Cheng, X. (2025). Digital learning in the 21st century: trends, challenges, and innovations in technology integration [Review]. Frontiers in Education, 10- 2025. https://doi.org/10.3389/feduc.2025.1562391
مدیریت توسعه پایدار در ورزش
دوره 6، شماره 15
دی 1404
صفحه 426-450

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