This project predicts the win probability of an IPL (Indian Premier League) team during a live match using a machine learning model trained on historical IPL data.
Built with Streamlit, this app provides an interactive user interface to enter match conditions like teams, score, overs, and wickets. It then calculates and visualizes the real-time winning probability of the batting team.
- Source: Kaggle - IPL Data Set
- The dataset contains match-by-match and ball-by-ball IPL statistics till the 2022 season.
- Select batting and bowling teams
- Choose host city
- Input target score, current score, overs completed, and wickets fallen
- Model predicts:
- Win and loss probabilities
- Visualized in a pie chart
- Streamlit progress bar
- Input validation with real-time warnings
- The model is trained using Scikit-learn.
- Key features include:
- Batting & Bowling Team
- Venue (city)
- Target runs
- Current runs & overs
- Wickets fallen
- Current Run Rate (CRR) and Required Run Rate (RRR)
- Output: Probability of winning (
pipe.predict_proba())
- Python
- Streamlit – for the web UI
- Pandas, NumPy – for data manipulation
- Scikit-learn – for model training
- Matplotlib – for charting the prediction
# 1. Clone the repository
git clone https://github.com/your-username/ipl-win-predictor.git
cd ipl-win-predictor
# 2. Install Dependencies
pip install -r requirements.txt
# 3. Ensure the following files are present in the same directory
# - application.py
# - pipe.pkl
# - requirements.txt
# 4. Run the Streamlit App
streamlit run application.pyThe app will open in your browser at:
👉 http://localhost:8501
Chayank Tatavarty
Built with ❤️ to make IPL more thrilling using data and ML!
This project is open-source and available under the MIT License.