Streamlit Dashboard: Let's analyse how Virat Kohli performs!

3 min read • 6/19/2025

4 comments • 54 views

🏏 Player Analytics: An Interactive Dashboard for Cricket Lovers

Hi, I'm Dhanush Devadiga — a front-end developer and passionate analyst. But at the same time, I’m also a cricket enthusiast and a fan of Virat Kohli, arguably the best batsman in the world today.

So, I thought, why not combine my love for cricket and data? That’s how I built Player Analytics, an interactive dashboard to analyze player performance, provide insights, and even predict future outcomes.

GitHub repo: https://github.com/dhanushd1998/streamlit-cricket-performance-dashboard.git
Live Demo: https://dhanushd1998-cricket-performance-dashboard-main-ejl7hp.streamlit.app/
Data Set on Kaggle: https://www.kaggle.com/code/dhanush1998/virat-kohli-performance-dashboard-analytics
youTube: https://lnkd.in/gBy-rdXq

🎨 UI & Design Highlights

Page Title: Set to “Player Analytics” for easy tab identification.
Favicon: A cricket themed logo serves as a visual identifier.
Layout: Wide mode enabled for better screen utilization.
Theme: Customized using config.toml to reflect India’s blue jersey and a dark mode aesthetic.
Sidebar: Starts collapsed by default and is reserved strictly for navigation via radio buttons.

📊 Understanding the Dashboard

On initial load, the Cricket Performance Dashboard is visible. If you’re not a cricket follower, here’s some context:

Cricket has three primary formats:

ODI (One Day Internationals) – the most popular
Test Matches – the longest format
T20 (Twenty20) – the shortest and most fast-paced

Virat Kohli is a three-format player, so his data spans across all these formats.

🔁 Dynamic Tabs & Metrics

The dashboard allows users to:

Switch between formats (ODI, Test, T20) using tabs.
Automatically update plots and metrics according to the selected format.

Key Metrics Displayed:

Total Runs
Matches Played
Average Strike Rate
Best Score
Number of Hundreds (100s)
Number of Fifties (50s)

👤 About Tab

This page gives a short introduction of the cricketer being analyzed — essential to establish context for the user.

🔮 Score Predictor

This page showcases cascading filter criteria to introduce predictive analytics.

How it works:

Select Match Type, Opposition, and Ground.
Based on historical data, the model predicts a potential score.

The filter values are dependent:

For example, choosing ODI and England shows Indian or English grounds.
Choosing T20 and Ireland filters the ground to Malahide in Ireland.

📋 Interactive Data Table

Features include:

Filtering by match type
Sorting by date (newest/oldest)
Filtering by opposition
Year range selection using a slider
Download filtered data as CSV

🧪 Example:

Filter for all T20 matches against England and Australia between 2010–2020 — and easily download the results.

📈 Visualizations

1. Area Plot — Runs Scored vs Year

Configuration hidden inside a Streamlit expander for a cleaner UI.
Allows selection of a year range to analyze performance trends.

2. Spider Plot — Matches by Country

Visualize the number of matches played against top N countries.
Default is top 6 countries.
Helps identify dominant matchups.

3. Bar Plot — Top 5 Scoring Grounds

Test: Highest runs at Adelaide
ODI: Highest runs at Mirpur

4. Vertical Bar Plot — Runs by Batting Position

T20: Highest runs at No. 3 position
Test: Highest at No. 4
Helps understand role evolution and effectiveness by position.

5. Line Chart — Total Runs Over Time

Select a year range to view trends.
From 2010–2020: Notable 56.68% dip (possibly due to COVID-19).
From 2008–2010: Positive upward trend.

🧠 Why Cricket Analytics Matters

In a billion-dollar sport where every run counts, data-driven insights are crucial. This dashboard transforms raw match data into actionable intelligence.

Cricketlytics (Cricket + Analytics) is on the rise — used by analysts, broadcasters, coaches, and fans alike.

⚠️ Current Drawbacks

Data is preloaded from a static CSV
No real-time data or API integration
Lacks light/dark mode switching
Best viewed on desktop, not optimized for mobile yet

🚀 Future Enhancements

API Integration for live stats
Advanced AI Models for score predictions
Add more visualizations (wagon wheels, dismissals, partnerships)
Player Comparison Tool
Mobile responsiveness / Progressive Web App (PWA)
Light/Dark mode toggle
Integration with platforms like Paddy Power or BoyleSports for monetization

🏁 Final Thoughts

This project represents the fusion of data, design, and cricket fandom. Whether you’re an analyst, developer, or just a cricket fan — this dashboard has something insightful for you.

“In cricket, your bat talks louder than words. But now, so can your data.”

Feel free to explore the dashboard, offer feedback, or suggest collaborations!

📌 Built using Python, Streamlit, Pandas, and Plotly — powered by a love for cricket and clean UI.