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. However, we argue that leveraging the Poisson distribution would be more appropriate and use simulations to show that bivariate Poisson regression (Karlis and Ntzoufras in J R Stat Soc Ser D Stat 52(3):381–393, 2003) reduces absolute bias when estimating the home advantage benefit in a single season of soccer games, relative to linear regression, by almost 85%. 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 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.

在 Covid-19 大流行之后，世界各地的 2019-2020 足球赛季被推迟，并最终在 2020 年夏季结束。来自不同学科的研究人员抓住机会比较重新安排的比赛，在空荡荡的体育场，对于以往的比赛，都是在球迷面前进行的。迄今为止，大多数这种后 Covid 足球研究都使用线性回归模型或其版本来估计主场优势的潜在变化。然而，我们认为利用泊松分布会更合适，并使用模拟来表明双变量泊松回归（Karlis 和 Ntzoufras in JR Stat Soc Ser D Stat 52(3):381–393, 2003）在估计主场优势在单赛季足球比赛中的收益，相对于线性回归，增加了近 85%。下一个，利用来自 17 个职业足球联赛的数据，我们扩展了双变量泊松模型来估计由于在没有球迷的情况下进行的比赛而导致的主场优势的变化。与当前表明主场优势下降的研究相反，我们的研究结果喜忧参半；在一些联赛中，证据表明主场优势有所下降，而在其他联赛中，主场优势可能有所上升。总而言之，这表明球迷对体育赛事的影响存在更复杂的因果机制。