Summary of Modeling and Prediction Of the Uefa Euro 2024 Via Combined Statistical Learning Approaches, by Andreas Groll et al.
Modeling and Prediction of the UEFA EURO 2024 via Combined Statistical Learning Approaches
by Andreas Groll, Lars M. Hvattum, Christophe Ley, Jonas Sternemann, Gunther Schauberger, Achim Zeileis
First submitted to arxiv on: 1 Oct 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Applications (stat.AP)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed joint machine learning model combines three distinct models to forecast UEFA EURO 2024 matches, leveraging match results from 2004-2020, team characteristics, and enhanced variables derived from ranking methods. The model incorporates generalized linear models, random forests, and extreme gradient boosting techniques, trained on a comprehensive dataset featuring additional covariates and player ratings. By simulating the tournament 100,000 times based on estimated expected goal numbers, the combined model predicts France as the clear favourite with a winning probability of 19.2%, followed by England (16.7%) and host Germany (13.7%). |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper combines three different machine learning models to predict UEFA EURO 2024 matches. It uses data from previous tournaments and adds extra information about teams and players. The model is trained many times to get a good estimate of the chances of each team winning. In the end, it predicts that France will likely win, followed by England and Germany. |
Keywords
» Artificial intelligence » Extreme gradient boosting » Machine learning » Probability
