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Register a new userPrediction of the FIFA World Cup 2018 – A random forest approach with an emphasis on estimated team ability parameters
توقعات كأس العالم فيفا ٢٠١٨, نموذج يستخدم الغابات العشوائية مع توظيف بارامترات تقديرية لقدرات الفريق
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Shadi Saleh
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في هذا البحث, نقارن ثلاثة طرق نمذجة أهداف مباريات كرة القدم مع الأخذ بعين الاعتبار الأداء المتنبئ به اعتمادا على جميع المباريات في كؤوس الفيفا الأربعة السابقة 2002--2014: نماذج الانحدار بواسون, طرق الغابات العشوائية, وطرق الترتيب.
In this work, we compare three different modeling approaches for the scores of soccer matches with regard to their predictive performances based on all matches from the four previous FIFA World Cups 2002 – 2014: Poisson regression models, random forests and ranking methods.
References used
Groll, A., G. Schauberger, and G. Tutz (2015): “Prediction of major international soccer tournaments based on team-specific regularized Poisson regression: an application to the FIFA World Cup 2014,” Journal of Quantitative Analysis in Sports, 11, 97–115.
Groll, A., T. Kneib, A. Mayr, and G. Schauberger (2018): “On the dependency of soccer scores – A sparse bivariate Poisson model for the UEFA European Football Championship 2016,” Statistical Modelling, to appear.
Groll, A. and J. Abedieh (2013): “Spain retains its title and sets a new record - generalized linear mixed models on European football championships,” Journal of Quantitative Analysis in Sports, 9, 51–66
Gneiting, T. and A. Raftery (2007): “Strictly proper scoring rules, prediction, and estimation,” Journal of the American Statistical Association, 102, 359–376
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