It is well known that, in most if not all sports, there is a sizeable advantage to playing at home. However, it isn't clear exactly what mechanism causes this home advantage to arise. Is it because when a team (or individual sportsperson) is playing at home, they don't have to travel as far, and are refreshed and comfortable at game time? Or, is it because the team (or individual sportsperson) is more familiar with the home venue than their competitors are? Or, is it because of home fan support?
Previous research has found it very difficult to disentangle these different mechanisms as being the underlying cause of home advantage. Cue the coronavirus pandemic, which created an excellent natural experiment that allows us to test a range of hypotheses, including about home advantage in sports. Since fans were excluded from stadiums in many sports, if home advantage was no longer apparent, we can at least rule out home fan support as being a contributor to home advantage.
And that is essentially what the research reported in this new article by Jeffrey Cross (Hamilton College) and Richard Uhrig (University of California, Santa Barbara), published in the Journal of Sports Economics (open access), tries to do. Specifically, they look at four of the top five European football leagues (Bundesliga, La Liga, Premier League, and Serie A), all of which faced a disrupted 2019-20 season, and after the disruption resumed play with restrictions that prevented fan attendance at games. Essentially, they compare home team performance before and after the introduction of the no-fans policy. Their preferred outcome variable is 'expected goals' rather than actual goals scored. Cross and Uhrig justify the choice as:
Due to randomness, human error, and occasional moments of athletic brilliance, the realized score of a match is a noisy signal for which team actually played better over the course of 90 minutes. In order to mitigate this noise, we focus on expected goals, or xG, which measure the quantity and quality of each team’s chances to score; they have been shown to better predict future performance and more closely track team actual performance than realized goals... Expected goals are calculated by summing the ex ante probabilities that each shot, based on its specific characteristics and historical data, is converted into a goal... For example, if a team has four shots in a game, each with a scoring probability of 0.25, then their expected goals for the match would sum to 1. However, their realized goals could take any integer value from 0 to 4...
Their data goes back to the 2009-10 season, and includes some 15,906 games in total. However, they only have data on expected goals from the 2017-18 season onwards, which includes 4,336 games. Because the games with no fans were played later than usual, the temperature was higher (as the season was extending closer to summer), so they make sure to control for weather, as well as for the number of coronavirus cases.
Looking at realised goals, Cross and Uhrig find that:
...raw home field advantage decreased by 0.213 goals per game from a baseline of a 0.387 goals per game advantage for the home team... This represents a decrease of 55%.
But, as they argue, this is quite a noisy measure of home advantage. So, they turn to their measure of expected goals, and find that:
...raw home field advantage, as measured by expected goals instead of realized goals, decreased by 64% from a 0.307 expected goal advantage for the home team to just 0.110 expected goals. Although the magnitude of the decrease is smaller than realized goals in absolute terms (0.197 xG as opposed to 0.213 G), it represents a larger fraction of the initial home field advantage (64% as opposed to 55%) because the initial home field advantage is smaller as measured by expected goals than realized goals.
Finally, looking at game outcomes, they find that:
...the lack of fans led to fewer home wins and more home losses, but the probability of a draw is unaffected, suggesting that fans are symmetrically pivotal: fans are approximately as likely to shift a result from a draw to a home win as they are from a home loss to a draw... Approximately 5.4 percentage points are shifted from the probability of winning to the probability of losing.
So, coming back to the question we started with, at least some of the home advantage that football teams experience is due to home crowd support. Given that home advantage decreased by somewhere between 55 percent and 64 percent, the share of home advantage that home crowd support is responsible for is sizeable. Of course, this doesn't necessarily extend to all sports. But it does show that home crowd support is important.
No comments:
Post a Comment