This repository includes all of the different materials pertinent to the project.
In this project we have created statistical learning models using metrics that measure tactical principles coaches could prioritize to predict the outcome of a soccer match. We used data from the 2022 and 2023 Major League Soccer regular season games. This data was obtained from the FBRef website. This data is provided by Opta, or StatsPerform. The results of this project are very relevant as they allow us to better understand the predictive power of commonly used metrics in the sport and specifically within the application of the data to the sport.
This project was completed for CSC 642 - Statistical Learning at the University of Miami. My partner was Patrick Geraghty. His GitHub can be found here: https://github.com/PatGeraghty
Repository Contents:
- The folder named "data" contains an excel file with all of the regular season games from the 2022 and 2023 MLS regular seasons.
- The folder named "src" contains an r script file, where all of the code we used to build these models can be found.
- The folder named "docs" contains our final paper and presentation