论文标题
使用双变量泊松回归估算Covid-19期间足球主场优势的变化
Estimating the change in soccer's home advantage during the Covid-19 pandemic using bivariate Poisson regression
论文作者
论文摘要
在Covid-19的大流行之后，2019 - 2020年全球足球赛季被推迟并最终在2020年夏季组成。从各种学科的研究人员跳高了机会，将重新安排的游戏的机会进行比较，在空旷的体育馆前玩过，在以前的游戏中玩过粉丝。迄今为止，大多数此后的足球研究都使用了线性回归模型或版本，以估计家庭优势的潜在变化。但是，由于足球的结果是非线性的，我们认为利用泊松分布将更合适。首先，我们使用模拟表明，在估计一个相对于线性回归的单个赛季中，双变量泊松回归降低了绝对偏见，将几乎85％。接下来，借助来自17个职业足球联赛的数据，我们扩展了双变量泊松模型，估计由于没有球迷的游戏而进行的游戏，主场优势的变化。与当前的研究表明，当前的研究表明家庭优势下降，我们的发现混合了。在某些联赛中，证据指出有所下降，而在其他联赛中，主场优势可能会提高。总的来说，这暗示着一种更复杂的因果机制，用于粉丝对体育赛事的影响。
In wake of the Covid-19 pandemic, 2019-2020 soccer seasons across the world were postponed and eventually made up during the summer months of 2020. Researchers from a variety of disciplines jumped at the opportunity to compare the rescheduled games, played in front of empty stadia, to previous games, played in front of fans. To date, most of this post-Covid soccer research has used linear regression models, or versions thereof, to estimate potential changes to the home advantage. But because soccer outcomes are non-linear, we argue that leveraging the Poisson distribution would be more appropriate. We begin by using simulations to show that bivariate Poisson regression reduces absolute bias when estimating the home advantage benefit in a single season of soccer games, relative to linear regression, by almost 85 percent. Next, with data from 17 professional soccer leagues, we extend bivariate Poisson models estimate the change in home advantage due to games being played without fans. In contrast to current research that overwhelmingly suggests a drop in the home advantage, our findings are mixed; in some leagues, evidence points to a decrease, while in others, the home advantage may have risen. Altogether, this suggests a more complex causal mechanism for the impact of fans on sporting events.
