论文标题
FIFA世界杯2022
Nested Zero Inflated Generalized Poisson Regression for FIFA World Cup 2022
论文作者
论文摘要
本文通过嵌套零膨胀的广义泊松回归介绍了2022年FIFA世界杯的预测。我们的回归模型结合了参与团队的ELO点，比赛的位置以及特定团队在攻击和防守方面的技能，作为协变量。拟议的模型允许就概率进行预测，以量化每个团队达到比赛的某个阶段的机会。我们使用Monte Carlo模拟来估计比赛的每场比赛的结果，我们可以从中模拟整个比赛本身。自2016年以来，该模型适合参加参加日期和重要性的所有足球比赛。提供了与以前的比赛的验证，并与其他泊松模型进行了比较。
This article is devoted to the forecast of the FIFA World Cup 2022 via nested zero-inflated generalized Poisson regression. Our regression model incorporates the Elo points of the participating teams, the location of the matches and the of team-specific skills in attack and defense as covariates. The proposed model allows predictions in terms of probabilities in order to quantify the chances for each team to reach a certain stage of the tournament. We use Monte Carlo simulations for estimating the outcome of each single match of the tournament, from which we are able to simulate the whole tournament itself. The model is fitted on all football games of the participating teams since 2016 weighted by date and importance. Validation with previous tournaments and comparison with other Poisson models are given.
