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The Intertwine of Brain and Body: A Quantitative Analysis on How Big Data Influences the System of Sports

Author

Listed:
  • Devansh Patel

    (Indus University)

  • Dhwanil Shah

    (L.J. Institute of Engineering and Technology)

  • Manan Shah

    (Pandit Deendayal Petroleum University)

Abstract

Big data, artificial intelligence, data analytics, machine learning, neural networks are promising prospects in the industry right now and subsequently the posterity for the current technological landscape. Initially, we looked into the overwhelming amount of sectors it is involved in. In the auditing process, we were able to conclude; the sports industry seems to be one of the most promising applications of these modern technologies. Hence, this paper offers a deeper look into how the entire sports industry has been affected in a multi-faceted way. Not only, are the on field antics that have been impacted but also the business implications and immersion of fans. The following is a comprehensive review expanding on the aforementioned aspects.

Suggested Citation

  • Devansh Patel & Dhwanil Shah & Manan Shah, 2020. "The Intertwine of Brain and Body: A Quantitative Analysis on How Big Data Influences the System of Sports," Annals of Data Science, Springer, vol. 7(1), pages 1-16, March.
    • Handle: RePEc:spr:aodasc:v:7:y:2020:i:1:d:10.1007_s40745-019-00239-y
    DOI: 10.1007/s40745-019-00239-y
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    References listed on IDEAS

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    Cited by:

    1. Song Wei & Kuili Wang & Xiangliang Li, 2022. "Design and implementation of college sports training system based on artificial intelligence," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(3), pages 971-977, December.
    2. Jyh-How Huang & Yu-Chia Hsu, 2021. "A Multidisciplinary Perspective on Publicly Available Sports Data in the Era of Big Data: A Scoping Review of the Literature on Major League Baseball," SAGE Open, , vol. 11(4), pages 21582440211, November.
    3. Poojan Thakkar & Manan Shah, 2021. "An Assessment of Football Through the Lens of Data Science," Annals of Data Science, Springer, vol. 8(4), pages 823-836, December.
    4. Uwaise Ibna Islam & Enamul Haque & Dheyaaldin Alsalman & Muhammad Nazrul Islam & Mohammad Ali Moni & Iqbal H. Sarker, 2023. "A Machine Learning Model for Predicting Individual Substance Abuse with Associated Risk-Factors," Annals of Data Science, Springer, vol. 10(6), pages 1607-1634, December.
    5. Šuštaršič Ana & Videmšek Mateja & Karpljuk Damir & Miloloža Ivan & Meško Maja, 2022. "Big Data in Sports: A Bibliometric and Topic Study," Business Systems Research, Sciendo, vol. 13(1), pages 19-34, June.
    6. Zbigniew Waśkiewicz, 2023. "Unveiling The Pathway To Success: Leadership In Sport And Management - Exploring Future Directions In Research," Economy & Business Journal, International Scientific Publications, Bulgaria, vol. 17(1), pages 212-218.
    7. A. Ramesh Babu & Niraj Upadhayaya, 2023. "A Framework for Collaborative Computing on Top of Mobile Cloud Computing to Exploit Idle Resources," Annals of Data Science, Springer, vol. 10(6), pages 1635-1651, December.
    8. Braznev Sarkar & Malay Bhattacharyya, 2021. "Spectral Algorithms for Streaming Graph Analysis: A Survey," Annals of Data Science, Springer, vol. 8(4), pages 667-681, December.
    9. Beiderbeck, Daniel & Evans, Nicolas & Frevel, Nicolas & Schmidt, Sascha L., 2023. "The impact of technology on the future of football – A global Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 187(C).

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