- Problem Statement With the vast amount of cricket data available on platforms like ESPN Cricinfo and CrickBuzz, cricket fans and analysts often struggle to retrieve structured, relevant, and actionable insights. Navigating between multiple web pages for match summaries, player statistics, and team combinations can be overwhelming. Additionally, building an optimal cricket team based on performance metrics and format-specific ranks remains a manual and subjective process. Goal: The main aim of this project is to create a web-based solution that provides: Easy access to recent match data
Navigation between teams and their players
External linking to real-time player stats
A smart team builder that forms teams based on ICC rankings and user input
- Methodology 2.1 Data Source & Scraping Player and team data is scraped from CrickBuzz Data fields: player name, country, role, game format, ICC rank, recent performance, etc.
2.2 Database Design ERD created to model relationships between players, teams, matches, and performance
Tables: Players, Matches, PlayerStats, Teams, Formats
2.3 Web Application Structure Frontend: HTML, CSS, JavaScript (React for interactivity)
Backend: Node.js
Database: MySQL 2.4 Features Implemented Home Page: Shows latest matches with dates, opponents, and results
Team Page:
Lists teams
Clicking a team shows players
Clicking a player redirects to CrickBuzz stat page
Smart Team Builder:
User selects game type (ODI, Test, T20) and country
System generates a best 11 based on ICC ranking and role constraints
Roles include top order, middle order, all-rounder, spinner, pace bowler
- Experimental Setup Environment: OS: Windows 10 / Ubuntu 22.04
Language: Python 3.11, JavaScript ES6
Frameworks: React.js, Flask/Express
Tools: Postman (for API testing), MySQL Workbench, VS Code
Browser: Chrome (for testing)
Dataset: Player data from CrickBuzz (Scraped)
ICC Rankings collected manually or scraped from official sources
Test Cases: Navigation between pages tested
Team builder functionality validated against ICC rankings
External link test for CrickBuzz redirection
Data integrity check after scraping
- Results and Output Analysis Feature Expected Output Result Home page Latest match info loads dynamically Passed Team navigation Team → Players → Player CrickBuzz profile Passed Smart Team Builder ICC-based team builds with correct role constraints Passed Game Format Selection Shows different players for ODI/Test/T20 Passed External Redirection Opens CrickBuzz stats page in new tab Passed
Team builder generates balanced teams with proper distribution (e.g., 4 top-order, 3 middle-order, 4 bowlers, etc.)
System is responsive and intuitive across devices
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Conclusion This project successfully demonstrates how web scraping, structured data storage, and front-end interaction can be combined to create a meaningful and interactive cricket data application. By automating data collection and providing a smart team-building utility, the system adds real-world value for fans, coaches, and analysts alike.
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Future Enhancements User Login System: Save favorite teams or players
Live Score API: Show real-time match updates on home page
Filter by stats: Allow filtering players by average, strike rate, etc.
Visualizations: Charts and graphs for individual player performance
Fantasy Team Simulator: Pick 11 and simulate outcome of matches
Machine Learning Module: Predict future performance of players