This web application predicts the number of goals scored by a team in the Champions League based on various statistical parameters. It uses a linear regression model trained on a historical dataset of team performances.
- User Input: Users can input the team's statistical data, such as matches played, wins, draws, losses, goal difference, and points.
- Goal Prediction: The application uses a linear regression model to predict the number of goals scored by the team based on the input data.
- Form Validation: The form ensures that all fields are filled out correctly before submitting the data for prediction.
- Python: The main programming language used to develop the application.
- Flask: A micro web framework used to build the web application.
- Pandas: A library used for data manipulation and analysis.
- Scikit-learn: A library used to build and train the linear regression model.
- HTML/CSS: Used to build the user interface.
- JavaScript: Used for client-side form validation.
- Render: The platform used for deploying the application.
- Dataset Loading: The historical dataset of team performances is loaded and preprocessed.
- Model Training: A linear regression model is trained using the historical data.
- User Interface: Users input the team's statistical data through a web form.
- Prediction: The input data is normalized and passed to the model to get the goal prediction.
- Result Display: The predicted number of goals is displayed to the user.
The statistical data and information can be retrieved from FBref - Real Madrid Statistics.