IPL Victory Probability Estimator

Project Overview

The IPL Victory Probability Estimator is a predictive model designed to forecast the outcomes of IPL matches based on historical match data. This project aims to provide cricket enthusiasts and analysts with insights and predictions, enhancing their understanding and enjoyment of the game.

Features

• Data Analysis: Analyzes IPL match data from Kaggle using Python.
• Predictive Modeling: Utilizes machine learning to estimate match outcomes.
• Interactive Web App: Built using Streamlit for easy user interaction.
• Model Deployment: Saves the trained model using the pickle library for quick access.

Tech Stack

• Python: Core programming language for analysis and modeling.
• Pandas: For data manipulation and preprocessing.
• Scikit-learn: Machine learning framework for model development.
• Pickle: To serialize and store the trained model.
• Streamlit: For creating an interactive UI.
• Jupyter Notebook: For exploratory data analysis.

Installation & Usage

1. Clone the repository:

   git clone https://github.com/chiragSahani/iplPredictor.git
   cd ipl-victory-estimator

2. Install dependencies:

   pip install -r requirements.txt

3. Run the Streamlit app:

   streamlit run app.py

4. Interact with the model by inputting match details and viewing predictions.

Contributing

Contributions are welcome! Feel free to fork this repository and submit a pull request.

License

This project is licensed under the MIT License.

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Developed with ❤️ using Python & Streamlit