https://github.com/deepaksilaych/ipl-win-predictor
Welcome to the "IPL Win Predictor" project! This machine learning model, built using logistic regression, predicts the probability of a team winning an IPL match based on the current match situation.
https://github.com/deepaksilaych/ipl-win-predictor
datascience ipl python steamlit
Last synced: about 1 month ago
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Welcome to the "IPL Win Predictor" project! This machine learning model, built using logistic regression, predicts the probability of a team winning an IPL match based on the current match situation.
- Host: GitHub
- URL: https://github.com/deepaksilaych/ipl-win-predictor
- Owner: DeepakSilaych
- Created: 2024-07-14T10:56:48.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-07-14T10:59:21.000Z (11 months ago)
- Last Synced: 2025-03-30T18:23:16.574Z (2 months ago)
- Topics: datascience, ipl, python, steamlit
- Language: Jupyter Notebook
- Homepage:
- Size: 2.73 MB
- Stars: 4
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
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README
# IPL Win Predictor
[](https://github.com/DeepakSilaych/ipl-win-predictor)
[](LICENSE)
[](https://www.python.org/)
[](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html)
[](https://numpy.org/)
[](https://pandas.pydata.org/)
[](https://www.streamlit.io/)
Welcome to the "IPL Win Predictor" project! This machine learning model, built using logistic regression, predicts the probability of a team winning an IPL match based on the current match situation. Get ready to make data-driven predictions!
## About This Project
The "IPL Win Predictor" leverages logistic regression to provide insights into the probability of a team winning an IPL match. This model analyzes various match features, team performance, and player statistics to offer real-time predictions.
### Features
- **Real-Time Predictions**: Get live predictions for IPL match outcomes based on the current match situation.
- **Interactive Interface**: The predictor is deployed on Streamlit, offering a user-friendly interface for exploring match scenarios.
- **Customizable Inputs**: Adjust the match parameters and teams to simulate different match scenarios.
- **Deployment**: Hosted on Streamlit Cloud for easy access and sharing.
## Usage
To make predictions, provide the following parameters when prompted:
- **Batting Team**: The team currently at bat.
- **Bowling Team**: The team currently bowling.
- **City**: The location of the match.
- **Current runs**: The current score of batting team.
- **Overs Completed**: The number of overs completed.
- **Wickets**: The number of wickets lost.
- **Target Runs**: The total runs scored by a bowling team.
The predictor will calculate the probability of the batting team winning based on these parameters and the current match situation.
## Technologies Used
This project leverages the following technologies:
- [Python](https://www.python.org/)
- [Logistic Regression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html)
- [NumPy](https://numpy.org/)
- [pandas](https://pandas.pydata.org/)
- [Streamlit](https://www.streamlit.io/)
## Installation
To run this project locally, follow these steps:
1. Clone the repository to your local machine using this command:
```shell
git clone https://github.com/DeepakSilaych/ipl-win-predictor.git
```
2. Navigate to the project directory:
```shell
cd ipl-win-predictor
```
3. Install the required Python libraries:
```shell
pip install -r requirements.txt
```
4. Run the Streamlit app locally:
```shell
streamlit run app.py
```
5. Open the provided local URL in your web browser to access the IPL Win Predictor.
## Usage
To make predictions, provide the current match situation including team performance, player statistics, and match conditions. The predictor will calculate the probability of a team winning.
## Contribute
If you'd like to contribute to this project or have suggestions for improvement, please feel free to submit issues or pull requests on [GitHub](https://github.com/DeepakSilaych/ipl-win-predictor).
Thank you for exploring the "IPL Win Predictor"! We hope this tool assists your IPL match predictions. 🏏🌟