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Predicting Champions League Winner Sponsor

Description

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.

Features

  • 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.

Technologies Used

  • 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.

How It Works

  1. Dataset Loading: The historical dataset of team performances is loaded and preprocessed.
  2. Model Training: A linear regression model is trained using the historical data.
  3. User Interface: Users input the team's statistical data through a web form.
  4. Prediction: The input data is normalized and passed to the model to get the goal prediction.
  5. Result Display: The predicted number of goals is displayed to the user.

Data Source

The statistical data and information can be retrieved from FBref - Real Madrid Statistics.