Revenue generating in the NHL: Multiple regression analysis on generating revenue in the National Hockey League

Abstract

This thesis aims to explain the differences between different National Hockey League teams generated revenues. This is done by analyzing the previous researches on different major sports leagues in the Northern America and comparing them with the findings from the NHL. By the data available, different regression models are constructed and further evaluated to analyze the different factors affecting revenue generating in the NHL. Scope of this research is from season 2005/2006 to season 2014/2015. From recent seasons, only a relatively small amount of data was available, thus the season 2014/2015 is the latest season of interest in this research. The data used to build the regression models was first collected in Excel, and then imported to Stata, which was used to build the models. After testing and analysis, a fixed effects model proved out to be the preferred model. Further analysis of the results pointed out the importance of competitive balance in the league to maximize the profitability between teams. In addition, the geographical features of a team, such as population in the area a team is located, proved out to be important when analyzing the generated revenues. Compared with the previous researches, the results had similarities, but as expected, some differences appeared as well. The most noticeable difference from the previous researches was that the regular season success of a team did not appear as a significant factor in any of the models presented. In addition, some earlier studies suggested that pricing of the tickets would be a significant factor in generating revenue, but surprisingly models used in this research did not provoke similar results. Overall, the results indicate that modeling the revenue generating of a NHL team is complicated, but definitely achievable. Further research on the topic should be done, as the financial side of the NHL still remains underexplored