A method for predicting background advertisement exposure parameters in sporting events: Televised football game approach

Autoři: Yi Xiao aff001;  Collins John aff002;  Xiaoling Ren aff001;  Pei Zhang aff001
Působiště autorů: School of Economics and Management, Shanghai University of Sport, Shanghai, China aff001;  Kinesiology, Health Promotion and Recreation Department, University of North Texas, Denton, Texas, United States of America aff002
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0223662



The background advertisement exposure parameters (BAEP) forms a premise for sponsorship negotiation and the basis for estimating the sponsorship value of background advertising. Prediction of the BAEP has a great contribution to the sporting events organizers and sponsors in terms of negotiating, decision-making for bidding, and income-generating.


Virtual Reality (VR), technology was utilized to construct a virtual three-dimensional model of the sports venue and simulate the telecast of the event. Based on VR technology and computer graphics theory, a pre-event prediction method for estimating the background advertisement exposure parameters of sporting events was put forward. The pre and post measures of the thirty BAEP of televised football games were compared to verify the effectiveness of the prediction method.


There was no significant difference between the pre- and post-measurement results for the same football game. The pre- and post-measurement results of the thirty BAEP of televised football games were tightly matched.


Using the prediction method can predict the BAEP of televised football games effectively and overcomes the shortcomings of current prediction methods that inhibits the effectiveness of the prediction of exposure parameters due to changes such as the type of the sporting events, the size of the sports venue, the layout of the background advertisements, and the placement of the television cameras, etc.

Klíčová slova:

Algorithms – Cameras – Decision making – Sports – Video games – Advertising – Computer graphics


1. Cornwell T. Less “Sponsorship as Advertising” and More Sponsorship-Linked Marketing as Authentic Engagement. J Advert. 2019; 48: 1–12.

2. Cornwell TB, Kwon Y. Sponsorship-linked marketing: research surpluses and shortages. J Acad Mark Sci. 2019. https://doi.org/10.1007/s11747-019-00654-w.

3. Donlan L, Crowther P. Leveraging sponsorship to achieve consumer relationship objectives through the creation of ‘marketing spaces’: an exploratory study. J Mark Commun. 2014; 20: 291–306.

4. Aron M, Levin, Chris J, Gary C. The Impact of Sports Sponsorship on Consumers' Brand Attitudes and Recall: The Case of NASCAR Fans, J Curr Iss Res Advert. 2001; 23: 23–31.

5. Bennett Roger. Sports sponsorship, spectator recall and false consensus. Eur J Mark. 1999; 33: 291–313.

6. Djohari N, Weston G, Cassidy R, Wemyss M, Thomas S. Recall and awareness of gambling advertising and sponsorship in sport in the UK: a study of young people and adults. Harm Reduct J. 2019; 16: 1–12. doi: 10.1186/s12954-018-0274-2

7. Sponsorship Research International. Worldwide sponsorship values. London: SRI. 1996.

8. IEG. Signs point to healthy sponsorship spending in 2018. 2018 December 11 [cited 12 September 2019]. Available from: http://www.sponsorship.com/Report/2018/01/08/Signs-Point-To-Healthy-Sponsorship-Spending-In-201.aspx.

9. International Events Group. Sponsorship spending: economic uncertainty to slow sponsorship growth in 2012. 2012 November 18 [cited 12 December 2018]. Available from: http://www.sponsorship.com/AboutIEG/Press-Room/Economic-Uncertainty-To-Slow-Sponsorship-Growth-In.aspx.

10. Statista. Total revenue from sports sponsorship worldwide by geographical region. 2016 July [cited 5 July 2018]. Available from http://www.statista.com/statistics/269784/revenue-from-sports-sponsorship-worldwide-by-region/.

11. Hanstad DV. Risk management in major sporting events: a participating national olympic team's perspective. Event Manage. 2012; 16: 189–201.

12. Jabar SS, Hassan G, Fakhrozaman N. The Role of Sport Marketing Mix in Generating Revenue for Iranian Football Clubs. Ann Appl Sport Sci. 2018; 6: 95–102.

13. Xiao Y, Liu Y, Zhang L, Li NZ. Research on the Virtual Forecast Method of Background Advertisement Exposal Parameter of Sport Events. International Conference on Wireless Communications. IEEE. 2009.

14. Zeng LP. Sport advertising. Beijing: Beijing University of Sport Press; 2012.

15. Breuer C, Rumpf C. The impact of color and animation on sports viewers’ attention to televised sponsorship signage. J Sport Manage. 2015; 29: 170–183.

16. Cianfrone BA, Zhang JJ. The impact of gamer motives, consumption, and in-game advertising effectiveness: a case study of football sport video games. Int J Sport Commun. 2013; 6: 325–347.

17. Zhang F, Xiao Y. The Design and Realization of Software System Measuring Exposure Parameters of Background Advertisements in Sport Events, J Capital Inst Phys Educ. 2010; 22: 86–90.

18. Bu J, Lao SY, Bai L. Real-time Billboard Trademark Detection and Recognition in Sports Video. Int Soc Opt Eng. 2013; 8783.

19. Sports events Research Center of Shanghai University of Sport. Toray Cup—Research on the Advertising Media Value of Shanghai International Marathon, China: Shanghai. 2011.

20. Xiao Y, Zhang F. Method of measuring exposure parameters of background advertisements of sports competitions. J Shanghai U Sport. 2009; 33:20–23.

21. Sports events Research Center of Shanghai University of Sport. Television broadcast and sponsorship effectiveness evaluation report, China: Shanghai. 2007.

22. Lee CH, Hwang FM, Yeh YC. The impact of publicity and subsequent intervention in recruitment advertising on job searching freshmen\"s attraction to an organization and job pursuit intention. J Appl Soc Psychol. 2013; 43: 1–13.

23. Gabrielė L, Gabrielė S, Julijus J, Eglė V, Ligita Z, Robertas D. Analysis of Affective and Gender Factors in Image Comprehension of Visual Advertisement. Computer Science On-line Conference. Springer, Cham. 2018.

24. Cianfrone BA, Trail GT, Zhang JJ, Lutz RJ. Effectiveness of in-game advertisements in sport video games: an experimental inquiry on current gamers. Int J Sport Commun. 2008; 1: 195–218.

25. Gonzalez WJ. Philosophico-methodological analysis of prediction and its role in economics. Theor Decis Libr. 2015; 50.

26. Guney H, Bakir MA, Aladag CH. A Novel Stochastic Seasonal Fuzzy Time Series Forecasting Model. Int J Fuzzy Syst. 2017; 20:1–12

27. Malik MH, Arif AFM. Ann prediction model for composite plates against low velocity impact loads using finite element analysis. Compos Struct. 2013; 101: 290–300.

28. Tien TL. A research on the grey prediction model ${rm gm (1, n) $. Appl Math & Comput. 2012; 218: 4903–4916.

29. Zhang JL, Tan ZF. Prediction of the chaotic time series using hybrid method. Sys Eng Theory Pract. 2013; 33:763–769.

30. Ludlow BL. Virtual reality: emerging applications and future directions. Rural Spec Educ Quart. 2015; 34: 3–10.

31. Garcia-Bonete MJ, Jensen M, Katona G. A practical guide to developing virtual and augmented reality exercises for teaching structural biology. Biochem Mol Biol Edu. 2018; 47: 16–24.

32. Juan YK, Chen HH, Chi HY. Developing and Evaluating a Virtual Reality-Based Navigation System for Pre-Sale Housing Sales. Appl Sci. 2018; 8: 952.

33. Kerrebroeck HV, Brengman M, Willems K. Escaping the crowd: an experimental study on the impact of a virtual reality experience in a shopping mall. Comput Hum Behav. 2017. http://doi.org/10.1016/j.chb.2017.07.019.

34. Lin CJ, Chen HJ, Cheng PY, Sun TL. Effects of displays on visually controlled task performance in three-dimensional virtual reality environment. Hum Factors Ergon Man. 2015; 25: 523–533.

35. Craig C. Understanding perception and action in sport: how can virtual reality technology help? Sports Technol. 2013; 6: 161–169.

36. Dempsey. VR in. sport. Eng Technol. 2016; 11: 51.

37. Huang AL. Research into the application of virtual reality technology in simulation of sports training, Inform Technol J. 2013; 12: 5689–5692.

38. Neumann DL, Moffitt RL, Thomas PR, Loveday K, Watling DP, Lombard CL, et al. A systematic review of the application of interactive virtual reality to sport. Virtual Real, 2018; 22: 183–198.

39. Yang B, Ren J. The guidelines of public television signal production standards of sports events, Beijing: The Chinese Communication University Press; 2007; 142–146.

40. Agoston MK. Computer graphics and geometric modeling: implementation and algorithms”, J Interpers Violence. 2015; 85: 781–811.

41. Zhu CY, Xiong YS, Tan K, Pan XH, Computer SO. Improved Seed-fill Algorithm Based on Refinement Strategy of Triangular Surface Mesh. Comput Eng. 2013; 39: 279–283.

42. Sarker MMK, Weihua C, Song MK. Detection and Recognition of Illegally Parked Vehicles Based on an Adaptive Gaussian Mixture Model and a Seed Fill Algorithm. J Inform Commun Convergence Eng. 2015; 13:197–204.

43. Yu W, He F, Xi P. A rapid 3D seed-filling algorithm based on scan slice. Comput Graph. 2010; 34: 449–459.

44. Srivastav MK. Transformation of an Object in Computer Graphics: A Case Study of Mathematical Matrix Theory. Elixir Int J. 2016; 100: 43396–43399.

45. Gijsenberg MJ. Going for gold: Investigating the (non) sense of increased advertising around major sports events. Int J Res Mark. 2014; 31: 2–15.

46. Henderson CM, Mazodier M, Sundar A. The Color of Support: The Effect of Sponsor-Team Visual Congruence on Sponsorship Performance. J Mark. 2019; 83: 50–71.

47. Mazodier M, Rezaee A. Are sponsorship announcements good news for the shareholders? Evidence from international stock exchanges. J Acad Mark Sci. 2013; 41: 586–600.

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2019 Číslo 10
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