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For the efficient of sales and marketing management of athletic clubs, it is crucial that there be a way to appropriately estimate the level of demand for the sporting events. More precise estimates allow for an appropriate financial and operational plan, which results in better club performance and a higher quality of service delivered to the fans.
Evaluating the demand potential and preparing a demand forecast is an important function of sales and marketing managers.
One of the key measures of sales forecasting performance is the accuracy of the forecast.
The focus of this study, therefore, is to examine the demand for soccer stadiums in Brazil through an analysis of the paying public at the matches of the A series of the Brazilian Championship (Campeonato Brasileiro) between 2004 and 2009.
From the literature review, the following hypotheses can be made:
The average per capita income of the city negatively influences the demand
The size of city's population impacts positively the demand
The better the rating of the home team (or opponent), the greater the demand
The higher the number of points won by the teams, the greater the demand
The greater the number of goals scored by the teams, the greater the demand
More advanced stages of the championship have higher demand
Others...
We compare the results of the regression model with normally distributed errors (benchmark), the TOBIT model and the Gamma and Poisson generalized linear model. The models included explanatory variables related to the economic environment, product quality and monetary and non-monetary incentives that people have to go to the stadium. We used different measures of accuracy to evaluate the performance of demand forecasts,
We showed that most of the explanatory variables are statistically significant to explain the amount of fans that go to the stadiums. We also found that the soccer demand is inelastic, and that the best predictions were obtained using the Gamma distribution.
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