Tech-Driven Talent Identification in Sports: Advancements and Implications

Authors

    Luis Felipe Reynoso-Sanchez * Department of Social Sciences and Humanities, Autonomous University of Occident, Los Mochis, Sinaloa, Mexico felipe.reynoso@uadeo.mx
https://doi.org/10.61838/kman.hn.1.3.11

Keywords:

Tech-Driven, Talent Identification, Sports, Advancement and implications

Abstract

This commentary delves into the transformative role of technology in talent identification within the sports arena, marking a significant shift from traditional scouting methods to sophisticated, data-driven approaches. It explores the latest advancements in technology, including artificial intelligence, biometric analysis, and advanced data analytics, and how they revolutionize the identification and nurturing of sporting talent. The commentary provides a critical comparison between conventional practices and modern technological methods, highlighting the increased accuracy, efficiency, and objectivity that technology offers. It also addresses the broader implications of these advancements, including ethical considerations like privacy and data security, and their impact on athletes, coaches, and sports organizations. Challenges and limitations of current technologies are discussed, alongside a perspective on future directions and potential improvements. This article aims to provide a comprehensive overview of the current state of tech-driven talent identification in sports, offering insights into its profound implications for the future of sports management and athlete development.

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Author Biography

  • Luis Felipe Reynoso-Sanchez, Department of Social Sciences and Humanities, Autonomous University of Occident, Los Mochis, Sinaloa, Mexico

    felipe.reynoso@uadeo.mx

References

1. Khan NJ, Ahamad G, Naseem M. An IoT/FOG based framework for sports talent identification in COVID-19 like situations. International Journal of Information Technology. 2022;14(5):2513-21. [PMID: 35669983] [PMCID: PMC9148553] [DOI]

2. Shahidi SH, Carlberg B, Kingsley D. Talent Identification and Development in Youth Sports: A Systematic Review. International Journal of Kinanthropometry. 2023;3(1):73-84. [DOI]

3. Čular D, Babić M, Zubac D, Kezić A, Macan I, Peyré-Tartaruga LA, et al. Tensiomyography: from muscle assessment to talent identification tool. Frontiers in Physiology. 2023;14. [PMID: 37435303] [PMCID: PMC10330706] [DOI]

4. Yablonsky S. AI-driven platform enterprise maturity: from human led to machine governed. Kybernetes. 2021;50(10):2753-89. [DOI]

5. Reddicharla N, Varnam PR, Nair P, Al-Marzooqi SM, Sultan Ali MA, editors. Empowering the Workforce of the Future Through Strategic Data Science Framework to Demystify Digitalization in ADNOC Onshore to Create Sustainable Business Value. Abu Dhabi International Petroleum Exhibition and Conference; 2022: SPE. [DOI]

6. Kotz D, Xing G. Introduction to the Special Issue on the Wearable Technologies for Smart Health, Part 2. ACM New York, NY, USA; 2021. p. 1-2. [DOI]

7. Reyaz N, Ahamad G, Naseem M, Ali J, Rahmani KI. Information communication and technology in sports: a meticulous review. Frontiers in Sports and Active Living. 2023;5. [PMID: 37465319] [PMCID: PMC10351379] [DOI]

8. Jiang L, Zhang D. Deep Learning Algorithm based Wearable Device for Basketball Stance Recognition in Basketball. International Journal of Advanced Computer Science and Applications. 2023;14(3). [DOI]

9. Kalinina LY, Ivanov D, Nikitin N. Efficiency of technology for early identification of giftedness in children aged 6-7 through contemporary art. Перспективы Науки и Образования Perspectives of Science and Education.253.

10. Chan JY, Wang Z, Xie Y, Meisel CA, Meisel JD, Solano P, Murillo H. Identifying potential managerial personnel using pagerank and social network analysis: The case study of a european it company. Applied Sciences. 2021;11(15):6985. [DOI]

11. Chen W, Ding J, editors. The Innovation and Development of School-running Mode of Continuing Education in the Internet Age. 2015 International Conference on Social Science, Education Management and Sports Education; 2015: Atlantis Press. [DOI]

12. Parry J. The youth olympic games–some ethical issues. Olympic Ethics and Philosophy: Routledge; 2014. p. 36-52.

13. Chelst K, Canbolat YB. Value-added decision making for managers: CRC press; 2011. [DOI]

14. Papagiannopoulou C, Parchen R, Rubbens P, Waegeman W. Fast pathogen identification using single-cell matrix-assisted laser desorption/ionization-aerosol time-of-flight mass spectrometry data and deep learning methods. Analytical chemistry. 2020;92(11):7523-31. [PMID: 32330016] [DOI]

15. Varillas-Delgado D, Del Coso J, Gutiérrez-Hellín J, Aguilar-Navarro M, Muñoz A, Maestro A, Morencos E. Genetics and sports performance: the present and future in the identification of talent for sports based on DNA testing. European journal of applied physiology. 2022;122(8):1811-30. [PMID: 35428907] [PMCID: PMC9012664] [DOI]

16. Gupta C. The Future of Talent Management: Leveraging Automation and HR Analytics for Success—A Critical Review of Literature. MDIM Journal of Management Review and Practice. 2023;1(2). [DOI]

17. Utamayasa IGD. Talent Identification of Future Sportsmen Using Sport Search Application. Budapest International Research and Critics Institute-Journal (BIRCI-Journal). 2021;4(1):690-5. [DOI]

18. Barraclough S, Till K, Kerr A, Emmonds S. Methodological Approaches to Talent Identification in Team Sports: A Narrative Review. Sports (Basel). 2022;10(6). [PMID: 35736821] [PMCID: PMC9227581] [DOI]

19. Eze J, Zhang S, Liu E, Eze E, editors. Cognitive radio technology assisted vehicular ad-hoc networks (VANETs): Current status, challenges, and research trends. 2017 23rd International conference on automation and computing (ICAC); 2017: IEEE. [PMID: 28992912] [DOI]

20. Takeyama Y, Fujii K. Proposal for a New Sports Talent Identification System Based on the Tracking Phenomenon of Height. Medical & Clinical Research, 8 (11), 01. 2023;6. [DOI]

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Published

2023-07-01

How to Cite

Reynoso-Sanchez, L. F. (2023). Tech-Driven Talent Identification in Sports: Advancements and Implications. Health Nexus, 1(3), 77-82. https://doi.org/10.61838/kman.hn.1.3.11