🏏 IPL Winning Probability Predictor

This project is a Machine Learning-powered web application that predicts the winning probability of an IPL cricket team in real time, based on current match statistics. It uses past IPL match data to train a model that understands match dynamics like run rate, wickets, and target.

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📌 Features

• Predicts real-time winning probability between two IPL teams.
• Uses historical match data (matches.csv, deliveries.csv).
• Built with scikit-learn and deployed using Streamlit.
• Interactive user interface for entering match details.
• Pre-trained ML model for instant predictions.

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📊 Dataset

The project uses multiple IPL datasets:

• matches.csv – Match results and summary.
• deliveries.csv – Ball-by-ball match data.
• teamwise_home_and_away.csv – Team home/away performance.
• most_runs_average_strikerate.csv – Player batting stats.

Source: Kaggle IPL Dataset

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🧠 Model Details

• Algorithm: Logistic Regression (via scikit-learn pipeline).
• Features Used:
  • Current Score
  • Overs Completed
  • Wickets Lost
  • Target Score
  • Remaining Balls
  • Required Run Rate
  • Team Batting & Bowling

The model outputs probabilities for Batting Team Win and Bowling Team Win.

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🚀 Installation & Usage

1️⃣ Clone the repository

git clone https://github.com/J-TECH-bot/IPL_Winning_Probability.git
cd IPL_Winning_Probability

2️⃣ Install dependencies
pip install -r requirements.txt

3️⃣ Run the app locally
streamlit run app.py

🌐 Deployment

The project can be deployed on Streamlit Cloud or any Python hosting service.
Example:

streamlit run app.py

📸 Screenshots

1. Web App Interface


📜 License

Licensed under the MIT License. You are free to use and modify it for educational purposes.

🙌 Acknowledgements

IPL datasets from Kaggle

Built with Python, Pandas, scikit-learn, Streamlit


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