Discover the Top 5 Influential Variables in Football Match Predictions

In a recent study, researchers used a synthetic dataset to explore how different variables impact the outcomes of football matches. The dataset included statistics like goals scored, number of passes, ball possession percentage, and the number of red or yellow cards. Two machine learning models, Decision Tree and Random Forest, were trained to predict match results. The analysis revealed that the number of goals scored was the most influential variable, followed by ball possession percentage, number of passes, and the number of red or yellow cards. These findings highlight the critical role of these variables in determining match outcomes, providing insights into the mechanics of football analytics. The study also set out to find thresholds for these influential variables, offering a deeper understanding of their impact on model predictions.

Source: towardsdatascience.com