🏏 IPL Analysis Dashboard — Streamlit App

An interactive IPL (Indian Premier League) analytics dashboard built with Streamlit. Explore team performance, batsman and bowler stats, boundary analysis, and Orange Cap holders across IPL seasons 2008–2019.

Features · Modules · Installation · Usage · Dataset · Project Structure

---

✨ Features

• 📊 7 analysis modules accessible from the sidebar
• 🎯 Filterable views — drill down by team, player, season, or boundary type
• 📈 Rich visualizations using both Matplotlib and Plotly (bar, line, pie, area, scatter, histogram)
• 🏆 Season winners and win count comparisons across all IPL franchises
• 🦾 Orange Cap tracker — top run-scorer per season, visualized with a scatter plot
• 🏏 Per-batsman breakdown — runs scored against each bowling team
• 🎳 Bowler analysis — total runs conceded with pie and line charts
• 🔴 Boundary analysis — fours and sixes comparison with dual-line overlay chart

---

📋 Modules

1. 🏟️ Most Played Team

• Ranks all IPL teams by total matches played
• Displays results in a sortable table
• Visualized with a Matplotlib line chart and an interactive Plotly line chart

2. 🏆 Season Winner

• Filter by season and/or winning team using sidebar dropdowns
• Shows the IPL winner for each season in a bar chart
• Displays total number of IPL title wins per team in a second bar chart

3. 🏏 Batsman

• Filter to a specific batsman or view the Overall Top 25
• Total runs scored across IPL seasons 2008–2019
• Vertical and horizontal bar charts for easy comparison

4. 🎳 Bowler

• Filter to a specific bowler or view the Overall Top 25
• Total runs conceded across seasons
• Plotly line chart and pie chart showing run distribution among top 25 bowlers

5. 🔴 Boundaries Analysis

• Filter by run type (4 or 6) and batsman
• Histogram of fours hit by all batsmen
• Area chart of top 25 six-hitters
• Dual-line overlay chart comparing fours vs. sixes for top batsmen

6. 📊 Batsman Score

• Select any batsman to see their runs against each bowling team
• Table + Plotly chart rendered from the helper.batsman_scored() function

7. 🟠 Orange Cap Holder

• Filter by season or view all seasons at once
• Table of Orange Cap winners per season
• Scatter plot with encoded Y-axis showing which batsman won the Orange Cap in each season

---

📂 Project Structure

ipl-analysis/
│
├── app.py                      # Main Streamlit dashboard
├── helper.py                   # All data processing & chart helper functions
│
├── IPL-anaylsis/
│   ├── deliveries(1).csv       # Ball-by-ball delivery data
│   └── matches(1).csv          # Match-level data (teams, venue, winner, season)
│
└── requirements.txt            # Python dependencies

helper.py Functions

Function	Description
Most_Played_Team(Matches)	Count matches played per team
Season_Winner(Matches)	Extract unique seasons and winners for dropdowns
fetch_Season_Winner(Matches, season, winner)	Filter season winner data
Batsman_Run(Deliveries)	Get list of batsmen for dropdown
fetch_Batsman_Run(Deliveries, batsman)	Fetch runs for a selected batsman
Bolwer_Run(Deliveries)	Get list of bowlers for dropdown
fetch_Bowler_Run(Deliveries, bowler)	Fetch runs conceded by a selected bowler
boundry(Deliveries)	Get boundary run types and batsmen for dropdowns
count_boundaries(Deliveries, run, batsman)	Filter boundary data
batsman(Deliveries)	Get all batsman names
batsman_scored(Deliveries, name)	Return a Plotly chart for a batsman's runs vs teams
season(Matches)	Get all seasons for dropdown
orange_cap_holder(Deliveries, Matches, season)	Find Orange Cap winner per season

---

⚙️ Installation

Prerequisites

• Python 3.9 or higher

1. Clone the repository

git clone https://github.com/your-username/ipl-analysis.git
cd ipl-analysis

2. Create and activate a virtual environment

python -m venv venv

# Linux / macOS
source venv/bin/activate

# Windows
venv\Scripts\activate

3. Install dependencies

pip install -r requirements.txt

---

🚀 Usage

streamlit run app.py

Open your browser at http://localhost:8501.

1. Use the sidebar radio menu to select an analysis module
2. Use the sidebar dropdowns to filter by team, player, or season
3. View interactive Plotly charts and data tables in the main panel

---

🗄️ Dataset

The app uses two CSV files covering IPL seasons 2008–2019:

deliveries(1).csv — Ball-by-Ball Data

Column	Description
match_id	Unique match identifier
batsman	Batsman on strike
bowler	Bowler delivering the ball
batsman_runs	Runs scored by the batsman off that ball
total_runs	Total runs off that ball (including extras)
bowling_team	Team bowling

matches(1).csv — Match-Level Data

Column	Description
id	Unique match identifier
season	IPL season year
team1	Home team
team2	Away team
winner	Winning team

Data source: Kaggle — IPL Dataset

---

📦 Dependencies

streamlit
pandas
matplotlib
plotly

Install all at once:

pip install streamlit pandas matplotlib plotly

---

🤝 Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature/your-feature
3. Commit your changes: git commit -m 'Add your feature'
4. Push to the branch: git push origin feature/your-feature
5. Open a Pull Request

---

📜 License

This project is licensed under the MIT License. See LICENSE for details.

---

Built with ❤️ using Streamlit · Plotly · Pandas · IPL Dataset 2008–2019