https://github.com/githubasr2001/ipl_dashboard
https://github.com/githubasr2001/ipl_dashboard
Last synced: about 2 months ago
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- Host: GitHub
- URL: https://github.com/githubasr2001/ipl_dashboard
- Owner: githubasr2001
- Created: 2025-01-13T01:27:48.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-03-21T17:15:54.000Z (2 months ago)
- Last Synced: 2025-03-21T18:24:57.685Z (about 2 months ago)
- Language: Python
- Size: 1.87 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# IPL Analytics Dashboard (2008-2024) 🏏
## Overview
A comprehensive Streamlit-based web application for analyzing Indian Premier League (IPL) cricket data from 2008 to 2024. The dashboard provides in-depth insights into team and player performances through interactive visualizations and detailed statistical analysis.
Live Demo : https://ipl-analytics-pro.streamlit.app
## Features
### 1. Head to Head Analysis
- Compare performance between two teams
- Detailed metrics across different match phases
- Comprehensive statistical breakdown
### 2. Player Analysis
#### Batsman Analysis
- Total runs, strike rate, and performance metrics
- Performance against different teams
- Runs distribution across match phases
- Comparative visualizations
#### Bowler Analysis
- Wickets, economy rate, and performance metrics
- Performance against different teams
- Wickets distribution across match phases
- Comparative visualizations
### 3. Milestones & Records
- Batting Records
- Fastest fifties and centuries
- Most sixes and fours
- Most centuries and fifties
- Bowling Records
- Best bowling figures
- Most wickets
- Best economy rates
- Five-wicket hauls
- Team Records
- Highest team totals
- Best team strike rates
- Most team wins
## Technologies Used
- Python
- Streamlit
- Pandas
- Plotly
- NumPy
## Prerequisites
- Python 3.8+
- Streamlit
- Pandas
- Plotly
## Installation
1. Clone the repository
```bash
git clone https://github.com/yourusername/ipl-analytics-dashboard.git
cd ipl-analytics-dashboard
```
2. Install required packages
```bash
pip install -r requirements.txt
```
3. Ensure you have the `deliveries.csv.zip` file in the project directory
## Running the Dashboard
```bash
streamlit run app.py
```
## Data Source
- Comprehensive IPL match delivery-level data from 2008 to 2024