The Power of Artificial Intelligence on Sports
DOI:
https://doi.org/10.71125/sporteconres.15Keywords:
Artificial intelligence (ai) in sports, ai-powered fan engagement, athletic performance enhancement, predictive analytics in sportsAbstract
This article explores the broader role that artificial intelligence (AI) will play in the changing sports industry, focusing on how it will impact areas such as player performance, management, strategy formulation, and access to fans. As demonstrated by technologies such as FIFA sideline technology and video-assisted refereeing (VAR), the fusion of artificial intelligence and sports is driving a redefinition of traditional concepts of justice and human decision-making, resulting in greater reliance on data and objective decision-making processes. The study identifies fundamental issues in the practical and economic elements of sports, including the utilisation of artificial intelligence (AI) and strategic planning. The present study traces the evolution of scientific discourse through a detailed literature analysis of AI in sports from 1975 to 2023. The present study explores the evolution of artificial intelligence applications and their influence on the digital economy. To this end, an investigation is conducted into patterns of academic publications, encyclopedia editions, and collaborative networks. A notable increase in academic demand has also been observed since 2017, suggesting a growing public awareness of AI's revolutionary potential. This study makes a theoretical contribution to the understanding of the integration of AI into the sports ecosystem. It has the potential to assist sports organisations and policymakers in addressing ethical issues and jobs created by the use of AI.
References
Abeza, G., O’Reilly, N., & Seguin, B. (2019). Social media in relationship marketing: The perspective of professional sport managers in the MLB, NBA, NFL, and NHL. Communication & Sport, 7, 80-109. https://doi.org/10.1177/2167479517740343 DOI: https://doi.org/10.1177/2167479517740343
Barlow, A., & Sriskandarajah, S. (2019). Artificial intelligence: Application to the sports industry. Pricewaterhouse Coopers.
Briner, R., & Demyer, D. (2012). Systematic review and evidence synthesis as a practice and scholarship tool. In D. M. Rousseau (Eds.), The Oxford handbook of evidence-based management (pp. 112-129). Oxford Library of Psychology. https://doi.org/10.1093/oxfordhb/9780199763986.013.0007 DOI: https://doi.org/10.1093/oxfordhb/9780199763986.013.0007
Chamorro-Atalaya, O., Olivares-Zegarra, S., Sobrino-Chunga, L., Guerrero-Carranza, R., Vargas-Diaz, A., Huarcaya-Godoy, H., Rasilla-Rovegno, J., Suarez-Bazalar, J., & Poma- Dahler-Larsen, P. (2022). The practical utility of mixed methods: An empirical study. Journal of Mixed Methods Research, 17(2), 187-208. https://doi.org/10.1177/15586898211057359 DOI: https://doi.org/10.1177/15586898211057359
Chamorro-Atalaya, O., Olivares-Zegarra, S., Sobrino-Chunga, L., Guerrero-Carranza, R., Vargas-Diaz, A., Huarcaya-Godoy, M., ... & Cruz-Telada, Y. (2023). Application of the Chatbot in university education: a bibliometric analysis of indexed scientific production in SCOPUS, 2013-2023. International Journal of Learning, Teaching and Educational Research, 22(7), 281-304. DOI: https://doi.org/10.26803/ijlter.22.7.15
DeSchriver, T., Webb, T., Tainsky, S., & Simion, A. (2021). Sporting events and the derived demand for hotels: Evidence from Southeastern Conference football games. Journal of Sport Management, 35(3), 228-238. https://doi.org/10.1123/jsm.2020-0268 DOI: https://doi.org/10.1123/jsm.2020-0268
Fort, R. (2004). Inelastic sports pricing. Managerial and Decision Economics, 25(2), 87-94. https://doi.org/10.1002/mde.1108 DOI: https://doi.org/10.1002/mde.1108
Fink, J. S., James, J. D., & Tainsky, S. (2022). Introduction: State of the literature special issue. Journal of Sport Management, 36(3), 213-214. https://doi.org/10.1123/jsm.2022-0065 DOI: https://doi.org/10.1123/jsm.2022-0065
Fried, G., & Mumcu, C. (Eds.). (2016). Sport analytics: A data-driven approach to sport business and management. New York, NY: Taylor & Francis. DOI: https://doi.org/10.4324/9781315619088
Funk, D. C. (2017). Introducing a sport experience design (SX) framework for sport consumer behaviour research. Sport Management Review, 20, 145-158. https://doi.org/10.1016/j.smr.2016.11.006 DOI: https://doi.org/10.1016/j.smr.2016.11.006
Galily, Y. (2018). Artificial intelligence and sports journalism: Is it a sweeping change? Technology in Society, 54, 47-51. https://doi.org/10.1016/j.techsoc.2018.03.001 DOI: https://doi.org/10.1016/j.techsoc.2018.03.001
Govindan, K., & Hasanagic, M. (2018). A systematic review on drivers, barriers, and practices towards circular economy: A supply chain perspective. International Journal of Production Research, 52(1-2), 278-311. https://doi.org/10.1080/00207543.2017.1402141 DOI: https://doi.org/10.1080/00207543.2017.1402141
Haenlein, M., & Kaplan, A. (2019). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. California Management Review, 61, 5-14. https://doi.org/10.1177/0008125619864925 DOI: https://doi.org/10.1177/0008125619864925
Hirschberg, J., & Manning, C. D. (2015). Advances in natural language processing. Science, 349, 261-266. https://doi.org/10.1126/science.aaa8685 DOI: https://doi.org/10.1126/science.aaa8685
Hoeber, L., & Hoeber, O. (2012). Determinants of an innovation process: A case study of technological innovation in a community sport organisation. Journal of Sport Management, 26(3), 213-223. https://doi.org/10.1123/jsm.26.3.213 DOI: https://doi.org/10.1123/jsm.26.3.213
Kong, F. (2020). Application of artificial intelligence in the teaching of modern art. International Journal of Emerging Technologies in Learning, 15(13), 238-251. https://doi.org/10.3991/ijet.v15i13.15351 DOI: https://doi.org/10.3991/ijet.v15i13.15351
Lemire, J. (2018, August 13). Minute can automatically generate sports video teasers in real-time. SportTechie. https://www.sporttechie.com/minute-can-automatically-generate-sports-videoteasers-in-real-time
Lemire, J. (2019, July 27). Team Altemus uses AI to help pro athletes find a financial advisor. SportTechie. https://www.sporttechie.com/team-altemus-nfl-nba-ai-financial-adviser-exiger-ddiq
Legg, S., & Hutter, M. (2007). Universal intelligence: A definition of machine intelligence. Minds and Machines, 17, 391-444. https://doi.org/10.1007/s11023-007-9079-x DOI: https://doi.org/10.1007/s11023-007-9079-x
Mach, J. (2019, September 22). Is Skynet the future of artificial intelligence? Medium. https://medium.com/datadriveninvestor/is-skynet-really-the-future-of-artificialintelligence-83b7d6ad0d05
Mathiyazhagan, K., Rajak, S., Sampurna Panigrahi, S., Agarwal, V., & Manani, D. (2021). Reverse supply chain management in the manufacturing industry: A systematic review. International Journal of Productivity and Performance Management, 70(4), 859-892. https://doi.org/10.1108/IJPPM-06-2019-0293 DOI: https://doi.org/10.1108/IJPPM-06-2019-0293
Naraine, M.L. & Wanless, L. (2020). Going All in on AI: Examining the Value Proposition of and Integration Challenges With One Branch of Artificial Intelligence in Sport Management. Sports Innovation Journal, 1, 49-61. https://doi.org/10.18060/23898 DOI: https://doi.org/10.18060/23898
Perez, A., Howell Smith, M. C., Babchuk, W. A., & Lynch O’Brien, L. I. (2023). Advancing quality standards in mixed methods research: Extending the legitimation typology. Journal of Mixed Methods Research, 17(1), 29-50. https://doi.org/10.1177/15586898221093872 DOI: https://doi.org/10.1177/15586898221093872
Perianes-Rodriguez, A., Waltman, L., & van Eck, N. (2016). Constructing bibliometric networks: A comparison between full and fractional counting. Journal of Informetrics, 10(4), 1178-1195. https://doi.org/10.1016/j.joi.2016.10.006 DOI: https://doi.org/10.1016/j.joi.2016.10.006
Prahani, B. K., Rizki, I. A., Jatmiko, B., Suprapto, N., & Tan, A. (2022). Artificial intelligence in education research during the last ten years: A review and bibliometric study. International Journal of Emerging Technologies in Learning, 17(8), 169-188. https://doi.org/10.3991/ijet.v17i08.29833 DOI: https://doi.org/10.3991/ijet.v17i08.29833
Song, P., & Wang, X. A. (2020). A bibliometric analysis of worldwide educational artificial intelligence research development in the recent twenty years. Asia Pacific Education Review, 21(3), 473-486. https://doi.org/10.1007/s12564-020-09640-2 DOI: https://doi.org/10.1007/s12564-020-09640-2
Szymanski, S. (2020). Sport analytics: Science or alchemy? Kinesiology Review, 9(1), 57-63. https://doi.org/10.1123/kr.2019-0066 DOI: https://doi.org/10.1123/kr.2019-0066
Watanabe, N., Yan, G., & Soebbing, B.P. (2015). Major League Baseball and Twitter usage: The economics of social media use. Journal of Sport Management, 29(6), 619-632. https://doi.org/10.1123/JSM.2014-0229 DOI: https://doi.org/10.1123/JSM.2014-0229
Watanabe, N.M., Yan, G., Soebbing, B.P., & Fu, W. (2019). Air pollution and attendance in the Chinese Super League: Environmental economics and the demand for sport. Journal of Sport Management, 33(4), 289-302. https://doi.org/10.1123/jsm.2018-0214 DOI: https://doi.org/10.1123/jsm.2018-0214
Zupic, I., & Cater, T. (2015). Bibliometric methods in management and organisation: A review. Academy of Management, 18(3), 429-472. https://doi.org/10.5465/ambpp.2013.13426abstract DOI: https://doi.org/10.5465/ambpp.2013.13426abstract
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