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https://github.com/neerajcodes888/ipl-victory-analysis-with-prediction
This repository contains code for analyzing and predicting outcomes in the Indian Premier League (IPL) cricket matches from 2008 to 2022. It includes data analysis notebooks, a prediction model, and a Flask-based web application for interactive predictions. Explore historical match data, gain insights, and make predictions on upcoming matches .
https://github.com/neerajcodes888/ipl-victory-analysis-with-prediction
css3 csv-datasets eda feature-extraction flask-application github html5 notebooks pandas-library preprocessing python3 render-deployment sckiit-learn
Last synced: about 1 month ago
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This repository contains code for analyzing and predicting outcomes in the Indian Premier League (IPL) cricket matches from 2008 to 2022. It includes data analysis notebooks, a prediction model, and a Flask-based web application for interactive predictions. Explore historical match data, gain insights, and make predictions on upcoming matches .
- Host: GitHub
- URL: https://github.com/neerajcodes888/ipl-victory-analysis-with-prediction
- Owner: neerajcodes888
- License: epl-2.0
- Created: 2024-02-25T10:56:50.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-03-12T13:37:28.000Z (10 months ago)
- Last Synced: 2024-04-17T22:09:13.944Z (9 months ago)
- Topics: css3, csv-datasets, eda, feature-extraction, flask-application, github, html5, notebooks, pandas-library, preprocessing, python3, render-deployment, sckiit-learn
- Language: Jupyter Notebook
- Homepage: https://ipl-victory-analysis-with-prediction.onrender.com/
- Size: 16.7 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# 🏏 **IPL Winning Prediction 🏆 and Full Data Analysis**
## **Contents in this Project**
1. Data Loading and Summary Checking
2. Data Cleaning
3. Feature Extraction
4. EDA and Data Visualisation
5. Best Player Clusters since 2008 based on Performance
6. IPL Match Winning Prediction 🏆
## Index of Contents
1. [Introduction](#introduction)
2. [Features](#features)
3. [Demo](#demo)
4. [Deployed Link](#deployed-link)
5. [Directory Structure](#directory-structure)
6. [Technology Stack](#technology-stack)
7. [Installation](#installation)
8. [Usage](#usage)
9. [Contribution](#contribution)
10. [License](#license)
## Introduction
This project aims to analyze IPL match data from 2008-2022 and make predictions based on the analysis. It includes an analysis notebook (`Analysis.ipynb`) for exploring the data and a prediction notebook (`Prediction.ipynb`) for developing a prediction model. The web application for predictions is built using Flask, HTML, and CSS.
## Features
- Analyze IPL match data from 2008 to 2022.
- Develop and train prediction models based on historical data.
- Deploy a Flask-based web application for interactive predictions.
- Gain insights into team performance, player statistics, and match outcomes.
- Make predictions on upcoming IPL matches.
## Demo
## Deployed Link
The web application is deployed on Render. You can access it [here](https://ipl-victory-analysis-with-prediction.onrender.com/).
## Directory Structure
| File/Folder | Description |
|------------------|--------------------------------------------------|
| dataset | Folder containing dataset files |
| ├── balls_by_balls.csv | CSV file containing ball-by-ball data |
| └── matches.csv | CSV file containing match data |
| static | Folder containing static files (e.g., CSS) |
| └── style.css | CSS file for styling the web application |
| templates | Folder containing HTML templates |
| ├── index.html | HTML template for the main page of the web app |
| └── result.html | HTML template for displaying prediction results |
| Analysis.ipynb | Jupyter notebook for IPL match data analysis |
| Prediction.ipynb | Jupyter notebook for prediction model development|
| app.py | Flask application file |
| requirements.txt | File containing a list of required dependencies |
## Technology Stack
- Python 🐍
- Flask 🌐
- HTML/CSS 🎨
- joblib 🧠
- scikit-learn 📊
- pandas 🐼
## Installation
1. **Clone the repository:**
```bash
git clone https://github.com/neerajcodes888/IPL-Victory-Analysis-with-Predictions.git
cd IPL-Victory-Analysis-with-Predictions
## Usage
1. **Run the Flask application:**
```bash
python app.py
```
2. **Visit http://localhost:5000 in your web browser to access the web app.**
## Contribution
Contributions are welcome! If you'd like to contribute to this project, feel free to submit a pull request.
## License
This project is licensed under the [EPL 2.0](https://github.com/neerajcodes888/IPL-Victory-Analysis-with-Prediction/blob/main/LICENSE)