12  Data Analytics for Business Development in Sport

12.1 Introduction

To this point, we’ve explored sport data analytics from the ‘performance’ side, whether in regards to tactical decision-making, injury prevention, or other aspects of physical performance. However, it’s important to be aware of the increased integration of data analytics and advanced technologies in the ‘business’ aspects of sport [2].

For example, in talent acquisition, data-driven methods, including artificial intelligence and machine learning, are now critical in identifying and predicting the development of promising athletes [1]. Researchers have also demonstrated how sports analytics content -such as statistics, video, and data visualisation - enhances fan engagement by providing entertainment, information, and opportunities for social interaction.

Together, these advances seem to reflect the growing importance of data in optimising decision-making and enriching our overall experience of sport.

References

[1] N. Reyaz, G. Ahamad, N. J. Khan and M. Naseem, Machine Learning in Sports Talent Identification: A Systematic Review, 2022 2nd International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET), Patna, India, 2022, pp. 1-6, doi: 10.1109/ICEFEET51821.2022.9848247.

[2] Ratten, V., & Dickson, G. (2020). Big data and business intelligence in sport. In Statistical Modelling and Sports Business Analytics (eds., Ratten, V., & Hayduk, T.). London: Routledge. https://doi.org/10.4324/9780367854454-3

12.2 Guided Reading

Both papers for this week are available for reading and download via the module reading list, which can be accessed via myplace.

  • de la Torre, R., Calvet, L. O., Lopez-Lopez, D., Juan, A. A., & Hatami, S. (2022). Business Analytics in Sport Talent Acquisition: Methods, Experiences, and Open Research Opportunities. International Journal of Business Analytics, 9(1), 1–20. https://doi.org/10.4018/IJBAN.290406

  • Cho, M., Cottingham, M., Hawkins, B., & Lee, D. (2023). Sport Analytics Business: Exploring Fan Engagement on Analytical Content. International Journal of Applied Sports Sciences : IJASS, 35(2), 201–214. https://doi.org/10.24985/ijass.2023.35.2.201

Key Observations

A number of key themes can be identified in our reading this week:

  • Integration of data in sport: Both papers emphasise the growing use of data analytics and advanced technologies in sports. While de la Torre et al. (2022) focus on talent acquisition, Cho et al. (2023) discuss fan engagement; different but complementary areas of data application in sports.

  • Role of data-driven decision making: De la Torre et al. (2022) highlight how professional sports teams increasingly rely on data analytics, artificial intelligence, and machine learning to enhance player recruitment processes. This reflects a broader shift toward data-driven decision-making in sports management.

  • Impact of technology on sports media: Cho et al. (2023) address the impact of sport analytics on fan-oriented content production, emphasising how multimedia platforms and advanced data visualisation have transformed the way fans engage with sports.

  • Enhancement of fan experience: Cho et al. (2023) find that different types of analytics content (statistics, video, data visualisation) enhance fan engagement through information, entertainment, identity, and social interaction. This shows how data not only supports management decisions but also enriches the spectator experience.

  • Challenges and future directions: De la Torre et al. (2022) explore challenges and open lines of research in the application of data analytics to talent acquisition, while Cho et al. (2023) suggest that the continued integration of analytics in sports media production and fan engagement is an evolving trend worth further exploration.

12.3 Questions for Reflection

  • How can the use of data analytics in talent acquisition improve the long-term success of sports teams, and what challenges might arise in fully integrating these methods into traditional scouting practices?

  • In what ways could advancements in sport analytics content, such as data visualisation and decision-aid tools, further evolve fan engagement and influence the future of sports media production?

  • What ethical considerations should be taken into account when using data-driven methods, both in the recruitment of athletes and in shaping the fan experience through personalised content?