ML-Premier-League-Wins-Predictor is my first machine learning project that predicts the number of wins for each team in the Premier League using linear regression. Explore the key factors that contribute to becoming a champion in one of the world's most competitive football leagues. Jupyter Notebook and code included.
The project utilizes several datasets related to the Premier League:
- results.csv: Contains information about all the match results in the Premier League between the 2006/07 season and the 2017/18 season.
- stats.csv: Expands on the statistical categories that are official for the Premier League and will be used for analysis.
- EPL standings 2000-2022.csv: Provides the standings of the individual teams throughout the seasons 2000-2022.
- with_goalscorers.csv: Provides the top goalscorers from the formation of the Premier League in 1992 until now.
The main goal of this project is to build a linear regression model to predict the number of wins for each team in a Premier League season. Additionally, we want to identify the key factors that contribute to a team becoming a champion. By doing so, we aim to gain insights into what makes a team successful in the Premier League.
- Data Acquisition and Exploration: Reading and exploring the datasets to understand the available data.
- Data Preprocessing: Cleaning and preparing the data for further analysis.
- Exploratory Data Analysis (EDA): Visualizing and analyzing the data to gain insights into the trends and patterns.
- Model Building: Constructing a linear regression model to predict the number of wins and identifying important features.
- Conclusion: Summarizing the findings and key takeaways from the analysis.
- Clone the repository:
git clone https://github.com/your-username/ML-Premier-League-Wins-Predictor.git - Open the Jupyter Notebook file "ML-Premier-League-Wins-Predictor.ipynb".
- Run the cells in the notebook to execute the code step by step.
After running the notebook, you will obtain insights into the factors that influence a team's success in the Premier League. The linear regression model will provide predictions for the number of wins, and feature importance analysis will highlight the key factors that contribute to becoming a champion.
Contributions are welcome! If you want to contribute to this project, please follow these guidelines:
- Fork the repository.
- Create a new branch for your feature or bug fix.
- Make your changes and commit them with descriptive messages.
- Push your changes to your forked repository.
- Submit a pull request explaining your changes.
This project is licensed under the MIT License. Feel free to use, modify, and distribute the code as per the terms of the license.
- Robert Rusev - robertrusev
Special thanks to Kaggle and FBref for providing the datasets used in this project.