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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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    1. Troilo, Michael & Bouchet, Adrien & Urban, Timothy L. & Sutton, William A., 2016. "Perception, reality, and the adoption of business analytics: Evidence from North American professional sport organizations," Omega, Elsevier, vol. 59(PA), pages 72-83.
    2. P.-A. Chiappori, 2002. "Testing Mixed-Strategy Equilibria When Players Are Heterogeneous: The Case of Penalty Kicks in Soccer," American Economic Review, American Economic Association, vol. 92(4), pages 1138-1151, September.
    3. Fister, Iztok & Ljubič, Karin & Suganthan, Ponnuthurai Nagaratnam & Perc, Matjaž & Fister, Iztok, 2015. "Computational intelligence in sports: Challenges and opportunities within a new research domain," Applied Mathematics and Computation, Elsevier, vol. 262(C), pages 178-186.
    4. Bruno Travassos & Keith Davids & Duarte Araújo & T. Pedro Esteves, 2013. "Performance analysis in team sports: Advances from an Ecological Dynamics approach," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 13(1), pages 83-95, April.
    5. Tim McGarry, 2009. "Applied and theoretical perspectives of performance analysis in sport: Scientific issues and challenges," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 9(1), pages 128-140, April.
    6. Carmine Sellitto & Paul Hawking, 2015. "Enterprise Systems and Data Analytics: A Fantasy Football Case Study," International Journal of Enterprise Information Systems (IJEIS), IGI Global, vol. 11(3), pages 1-12, July.
    7. Samo Rauter & Iztok Fister & Iztok Fister Jr., 2015. "How to Deal with Sports Activity Datasets for Data Mining and Analysis: Some Tips and Future Challenges," International Journal of Advanced Pervasive and Ubiquitous Computing (IJAPUC), IGI Global, vol. 7(2), pages 27-37, April.
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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. 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.
    3. 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.
    4. 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.
    5. 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).
    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. 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.
    8. 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.
    9. 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.

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