Buraimo, Babatunde ORCID: 0000-0003-3928-5624, Forrest, David ORCID: 0000-0003-0565-3396, McHale, Ian G ORCID: 0000-0002-7686-3879 and Tena, JD ORCID: 0000-0001-8281-2886
(2021) ARMCHAIR FANS: MODELLING AUDIENCE SIZE FOR TELEVISED FOOTBALL MATCHES. European Journal of Operational Research, 298 (2). pp. 644-655.

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Modelling audience size for televised football matches has utility for a number of stakeholders. In the short-term it can inform the choice of broadcasters as to which matches to show and decisions of firms regarding how much to bid for advertising slots during the game. For elite clubs and leagues, for which television rights is their principal source of revenue, it offers a means of understanding which match characteristics will draw the largest audience and this should inform long-term decisions on how to structure their competitions. The paper argues that previous modelling in this area has typically depended on an inappropriate measure of audience size and unsatisfactory metrics to capture important match characteristics such as the quality of the talent on show and the significance of the match for the championship or relegation. In contrast to this prior literature, the present paper draws on sport analytics to derive its measures of player talent and match significance. This makes a material difference to findings from modelling audience size for 790 English Premier League matches between 2013 and 2019. For example, it identifies elevated interest for matches potentially significant for end-of-season outcomes. This has implications when organisers consider the optimal structure of the competition and revenue sharing arrangements between member clubs of the league. For the wider television industry, we show that measurement of audience size (and some results from modelling) are sensitive to whether focus is on the whole programme or just its core content (in this case the match itself).

Item Type: Article
Uncontrolled Keywords: OR in sports, Sport analytics, Football, Television audience
Divisions: Faculty of Humanities and Social Sciences > School of Management
Depositing User: Symplectic Admin
Date Deposited: 14 Jul 2021 09:53
Last Modified: 25 Nov 2023 11:50
DOI: 10.1016/j.ejor.2021.06.046
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