https://github.com/dipeshgoyal013/ipl_win_probability
A project which help you to check win probability of batting team in inning 2nd
https://github.com/dipeshgoyal013/ipl_win_probability
machine-learning matplotlib numpy pandas python sklearn
Last synced: 5 months ago
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A project which help you to check win probability of batting team in inning 2nd
- Host: GitHub
- URL: https://github.com/dipeshgoyal013/ipl_win_probability
- Owner: dipeshgoyal013
- Created: 2024-09-15T12:38:57.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-09-25T11:02:05.000Z (over 1 year ago)
- Last Synced: 2025-04-05T21:44:49.947Z (about 1 year ago)
- Topics: machine-learning, matplotlib, numpy, pandas, python, sklearn
- Language: Jupyter Notebook
- Homepage:
- Size: 1.69 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# IPL_Win_probability
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.
## Explore the Project
### 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.
### 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
* Logistic Regression
* NumPy
* pandas
* sklearn
## Predict with Confidence
Explore the "IPL Win Predictor" and make data-driven predictions about IPL match outcomes. Get real-time insights and enhance your understanding of match dynamics.