Sports marketing innovation: increasing fan engagement via innovative statistics from facial emotion recognition

Kröckel P, Piazza A, Wessel P (2022)


Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2022

Pages Range: 220-231

Event location: Ansbach DE

URI: http://ocs.editorial.upv.es/index.php/BMT/BMT2022/paper/view/15631

DOI: 10.4995/bmt2022.2022.15631

Open Access Link: http://ocs.editorial.upv.es/index.php/BMT/BMT2022/paper/view/15631

Abstract

Technology in football is increasingly used for decision making. Adoption, especially in Germany, has been slow. However, the benefits of data analytics for pre-, and post-match analysis have motivated decision makers to pay attention to the data science trend. Nowadays, football clubs from the third leagues or even amateur clubs are using technology to help them gain a competitive edge. Fan experience, both online and offline (home in front of the TV or at the stadium) is driving the next innovation stage in football. The study presented here is focused on testing and evaluation a facial recognition software on images from football coaches, just a few seconds after an important situation during the match has taken place (e.g., win, goal scored). We demonstrated that, in fact, emotion recognition software captures unexpected emotional reactions from coaches which could then be used to calculate interesting statistics and increase fan engagement and entertainment.

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How to cite

APA:

Kröckel, P., Piazza, A., & Wessel, P. (2022). Sports marketing innovation: increasing fan engagement via innovative statistics from facial emotion recognition. In Proceedings of the 4th International Conference Business Meets Technology (BMT22) (pp. 220-231). Ansbach, DE.

MLA:

Kröckel, Pavlina, Alexander Piazza, and Pascal Wessel. "Sports marketing innovation: increasing fan engagement via innovative statistics from facial emotion recognition." Proceedings of the 4th International Conference Business Meets Technology (BMT22), Ansbach 2022. 220-231.

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