TV-Audience, Uncertainty of Outcome and Change in Viewership During Half-Time
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TV-audience, uncertainty of outcome and change in viewership during half-time Evidence from the Dutch Eredivisie Sybren Negenman, s2163705 Abstract This paper looks into the relationship between TV-audience and the uncertainty of outcome hypothesis in the Dutch football league. The model used in this paper predicts that fans prefer matches with a clear favourite and an underdog. The findings of this paper are in line with the majority of previous studies. In addition, this paper presents a new approach by looking at the change in viewers at half-time and match uncertainty. Results show that the measure for uncertainty at half-time has no effect on the change in viewers. However, goal difference at half-time has a significant effect on change in viewership. Keywords: uncertainty of outcome hypothesis, loss aversion, TV-audience, football, Dutch league Supervisor: Professor R. H. Koning University of Groningen Netherlands June 7, 2018 1 Introduction In 2016, the KNVB, the Dutch football association, asked Chris Woerts, a marketeer and commercial director at Feyenoord and Sunderland, to come up with an idea to make the Dutch Eredivisie more attractive for the public. One of the arguments he made was to reduce the number of teams to 16 to increase competitive balance and this would increase viewership and attendance. However, this only holds when the public cares about competitive balance. Sports is full of uncertainty. The winner of a match, the score of every match and league standings at the end of the season are all uncertain. The thing that makes sports interesting is that there is always uncertainty about the outcome no matter which teams are playing. The consumer does not know the outcome of the match before the match has started. Rottenberg (1956) was one of the first to come up with the idea that the demand for sports matches depends on the uncertainty of the outcome of that match. He looked at the uncertainty of league standings. In his paper, the uncertainty of outcome hypothesis (UOH) states that demand for a game depends on the uncertainty of the outcome of that game. Rottenberg (1956) argues that "The tighter a competition, the larger the demand" in other words, the demand of individuals increases when the level of the teams are close to each other. Neale (1964) agrees with the idea that uncertainty leads to interesting matches in sports. He argues that more changes in league standings increases the demand. In addition, he extends the UOH by adding a paradox. The so-called Louis-Schmelling paradox describes the situation of a monopolist in the market i.e. a dominant and wealthy team that buys all the talent in the league. The results is that the competitive balance in the league is disrupted. Other teams are not able to compete with the 'monopolist' team in the league. According to the UOH, this disruption in competitive balance results in lower demand. In their chase to become the best of every team, they still need competition to increase demand. Before Coates et al.(2014), there has not been a theoretical model that models consumer behaviour of watching or attending sports matches. The UOH has been accepted without a theoretical basis. In their paper they develop a model of an individual's decision to attend or watch a sports match that includes uncertainty and reference-dependent preferences. They use this model to verify whether or not the UOH holds. Their model is based on 1 a model by Card and Dahl (2009). The uncertainty of outcome hypothesis predicts that demand is highest for matches where the outcome is most uncertain however when the UOH does not emerge from the model, individuals prefer upsets. Upsets are matches where there is little uncertainty about the outcome of the match and the team with the much lower probability of winning actually wins. For the ease of simplicity I assume that an upset occurs when the team with the lower probability of winning, wins the game. The degree of the upset depends on the difference of the winning probabilities of both teams involved. The model by Coates et al. (2014) can identify whether or not individuals are more interested in watching games where the outcome is uncertain or prefer watching games where the outcome is more certain. Previous research has applied this model to different sports and different leagues. In this paper, I will use the model by Coates et al. (2014) to help identify whether or not television demand in the Dutch Eredivisie follows the uncertainty of outcome hypothesis. I will look at the decision to watch matches as well as a dynamic framework in which individuals are allowed to change channels during half-time. This leads to the following two research questions: 1: Does TV-audience in the Dutch Eredivisie follow the UOH? 2: Do fans, after they know the half-time results, keep watching the game or do they switch to games where the outcome is more uncertain? In the next section of this paper I will explain the theoretical model from Coates et al. (2014). After that I will discuss previous research that has been done regarding the UOH and the main findings. After that I will come up with an econometric model and state the hypothesis. Next, I will discuss the data I will be using to test my hypothesis. In the last two sections I will present the results and draw conclusions. 2 Theoretic model The model that I will use in this paper and that previous studies also used, is the model by Coates et al. (2014). They model a fans' behaviour to attend live games when the outcome is uncertain. They base their model on the model by Card and Dahl (2009) and extend it to examine the UOH in baseball. It models fans' decision to watch a game. This decision 2 to watch a game contains an element of risk. Kahneman and Tversky (1979) modelled decision making under risk and is known as prospect theory. Prospect theory helps with decision making that involves risk. It states that individuals do not make decision based on the final outcome but on the potential gains or losses and that reference points are important when making decisions when risk is involved. Before the match begins, the individual does not know the outcome of the game. The reference point reflects the fans' expectations beforehand about the outcome of the game and makes decisions with respect to this point. Without reference points, consumer theory implies that individuals gain "consumption utility" from watching a game, they gain utility from a win (U W ) and utility from a loss (U L), where the utility from a win is larger than the utility from a loss, U W > U L. Let p be the probability of the home team winning, then: E[U] = pU W + (1 − p)U L (1) The expected utility is increasing in p. This implies that the expected utility is highest for matches where there is a clear favourite, high probability of winning the game. Under the assumption that fans of either team want to see their team win, the total demand for the match where the home team is expected to win increases with fans that support the home team. I assume that home team is the team the fan is supporting and away team is the team that the home team is playing. The opposite is true when the probability of the away team winning is greatest. This is not in line with the UOH, which predicts that demand is highest for matches where teams' performances are equal to each other i.e. probability of winning, p in equation 1, is equal to 0:5. Accoring to equation 1, expected utility is higher for values of p > 0:5. Coates et al. (2014) extended the model by including a reference point. Koszegi and Rabin (2006) extended the model by not only allowing for "consumption utility" but also utility that is derived from the actual outcome and some reference point, "gain-loss utility". The reference point is different for every game and every individual. Coates et al. (2014) assume that the outcome of sport matches are binary, y = 1 when the home team wins and y = 0 when the home team loses. In football there is also the possibility that the outcome is a draw. I have that y can take on three possible values, 1 1 y = i for i = 0; 2 ; 1. Here y = 0 when the home team loses, y = 2 when the results is a draw and y = 1 when the home team wins. Previous studies regarding sports where a 3 draw is a possibility also used the model proposed by Coates et al. (2014). Following Koszegi and Rabin (2006), I assume that the reference point is the fans' expectation about the final results of the match. The reference point of the fan is given by E(y = 1) = 1 × pr + 0 × (1 − pr) = pr. For any fan, the reference point is equal to the expected win probability of their team before the game has begun. Experiencing a win results in "consumption utility" (U W ) and "gain-loss utility" conditional on the reference point (pr) of the fan. Deviation from the reference point results in "gain-loss utility". The utility from a win of the home team is given by U W + α(y − pr) = U W + α(1 − pr) Where α is assumed to be the marginal impact of a deviation from the reference point. I also assume that α > 0. The equation shows that an unexpected win results in higher utility than an expected win.