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Economics of Governance

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18-02-2022 | Original Paper

The impact of winter Olympic games participation on NHL attendance

Authors: Rodrigo Schneider, Peter von Allmen, Garrett Munck

Published in: Economics of Governance | Issue 3-4/2022

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Abstract

The Winter Olympics occur once every four years during the first few weeks of February, which is in the middle of the National Hockey League (NHL) regular season. Prior to 1998, the International Olympic Committee prohibited participation by professional athletes. Beginning in that year, the governing body changed the policy to explicitly permit professionals to participate. For the next 20 years, the NHL allowed players to represent their country by participating, in part based on the hope that it would increase demand for the sport. In 2017, the league reversed this decision citing fatigue and significant disruption to the regular season. Previous policy analysis has focused on post-Olympics team performance effects of player participation. To our knowledge, no previous studies have considered the effects on demand for NHL games. Controlling for a variety of other possible factors, we study the effects of the Olympics on game-level attendance. We find that having players on the team roster who participated in the Games does increase attendance in the short run. Thus, it is possible that the original policy shift by the IOC was correct as the benefits to Olympic participation may outweigh the costs.

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The basketball competition is held during the Summer Games.

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Another possible strategy would be to test the impact of Olympic participation on international media rights and licensing. Unfortunately, we do not have access to the data required do so, as it would require detailed country data on such arrangements.

The 2012–13 season is excluded here as it was shortened significantly by a labor stoppage. Outdoor games, which typically have attendance several times that of an indoor game and are not evenly distributed across teams, are excluded from these averages and from our analysis below.

Mike Chairi. 2014. Olympic hockey 2014. Tracking stats for every NHL player at Sochi. February 11, 2014. At https://bleacherreport.com/articles/1955884-olympic-hockey-2014-tracking-stats-for-every-nhl-player-at-sochi. Accessed March 2, 2021. 2014 Men’s Olympic Hockey. At https://www.hockey-reference.com/olympics/years/2014. Accessed March 2, 2021. Attendance data can be found at https://www.hockey-reference.com/leagues/NHL_2014_games.html. While we regard Hockey-reference.com as a highly reputable source for NHL data, we acknowledge their disclaimer that “Attendance figures and arena capacities may not be 100 percent accurate and are subject to minor errors.” We use only attendance figures in our analysis and do not make use of their reported capacities.

We also tested whether our model would change if we added a dummy variable indicating when the teams that did not make it to the playoffs became officially eliminated. The coefficient for this variable was statistically insignificant and did not alter our main results. In an effort to keep our final model parsimonious, we did not include this variable in the final specification. We are grateful to an anonymous referee for this suggestion.

To mitigate concern that Olympians might have an impact on winning in the post Olympics period, we estimated a probabilistic model to analyze the impact of having more Olympians on the probability of winning a game. After controlling for accumulated points of home and away team prior to each game, we found no statistically significant impact of the number of Olympians on the probability of winning.

Notice that our model proposed in Eq. (1) estimates a non-linear relationship between attendance and the number of Olympians. Therefore, if we want to compare the marginal impact of Olympians on attendance starting at a different point than zero, then we need to adapt the change and consider the decreasing marginal returns of Olympians. For instance, if we want to measure the marginal attendance of having a third Olympian in a team, i.e., from 2 to 3 Olympians, we should calculate it in the following way: two Olympians = (531.23 × 2) + (−51.61 × 2²) = 856.02. And three Olympians = (531.23 × 3) + (− 51.61 × 3²) = 1,129.2. Thus, the marginal effect of a third Olympian on attendance is equal to: three Olympians—two Olympians = 273.18.

We create seven dummies to identify each of the eight possibilities to quantify the number of Olympians that each NHL team had, i.e., a number between 2 and 10, except for 8 as no team had 8 Olympians. Formally, we regress the following model:

$${Attendance}_{it}=\lambda {Post}_{t}+ {Post}_{t}.\sum_{g=3, g\ne 8}^{10}{\beta }_{g}.{Treatment}_{ig}+{X}_{it}+{\rho }_{i}+{\theta }_{t}+{\mu }_{d}+{\delta }_{y}+{\epsilon }_{it}.$$

To test for the existence of an attendance break in other years, we conducted a falsification test in which we ran the same regression as the one represented in Fig. 3 for the seasons 2011–12 and 2014–15. We included a dummy variable for the Olympic break and a treatment variable measuring the number of Olympians in 2014. Except for an increase from two to three Olympians in 2011–12, we found no increase in attendance for the teams with more Olympians.

It is possible that some of the increase in attendance could simply be pent up demand to attend NHL games. However, if this were the primary driver of the attendance change, we would not observe differences based on the number of Olympians per team. While such an effect is possible, we are not able to test for a baseline case of increases in attendance simply due to the break because no team had fewer than two Olympians.

In 2013–14, the NHL All Star game was not played because of the Olympic Games. First and second team All Stars were named by the Professional Hockey Writers Association. We use this list of names as our All Stars. NHL Announces 2013–14 All Star Teams. NHL.com at https://www.nhl.com/sharks/news/nhl-announces-2013-14-all-star-teams/c-723852. Accessed May 4, 2021.

We found similar results when we considered 30 days after the actual end; 45 days before the actual date; and 45 days after the actual date. Using 15 days (before or after), we found statistically significant results similar to those found in Table 3. This is not unexpected, as 15 days is close to the actual end of the Olympics and, therefore, can still be affected by the outcome we are trying to identify and measure.

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Title: The impact of winter Olympic games participation on NHL attendance
Authors: Rodrigo Schneider
Peter von Allmen
Garrett Munck
Publication date: 18-02-2022
Publisher: Springer Berlin Heidelberg
Published in: Economics of Governance / Issue 3-4/2022
Print ISSN: 1435-6104
Electronic ISSN: 1435-8131
DOI: https://doi.org/10.1007/s10101-022-00264-3

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