The Cricket Data Analytics🏏 project is made on T-20 Cricket World Cup data using Power BI.

Cricket Analytics and Prediction Project

A set of python scripts to extract cricket data from https://cricbuzz.com for analytics purpose.

Cricket Data Analytics Using HDFS and Mapreduce APIs

Used Snowflake to build our DataWarehouse from Json files and get analytics.

The Cricket Data Analytics project is made on T-20 Cricket World Cup Data.

This project analyses various ODI and IPL matches. Match predictions are made using various machine learning algorithms

IPL_ML – Playing_with_ML is your sandbox for experimenting with machine learning and data analysis techniques using IPL (Indian Premier League) datasets. Designed for hands-on learning, it serves as a flexible foundation for exploring cricket analytics through code, models, and insights.

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An interactive Tableau dashboard that transforms IPL match data (2008–2025) into powerful visual insights — track runs, wickets, team stats, and trends with precision. Cricket meets analytics. 🏏📊

End-to-end sports data analytics project. In this project, I'll cover web scraping (from the ESPN Cricinfo website), python, pandas, and Power BI to perform analyses on T20 world cup cricket data.

This project demonstrates the application of machine learning in sports analytics, offering value to data science learners, ML enthusiasts, and cricket fans. Future enhancements can include live data integration, advanced deep learning approaches, and deployment as a web app for real-time match predictions.

A comprehensive analytics project for T20 cricket (e.g., IPL), extracting insights on player performance, venue effects, toss impacts, run rate trends, and match predictions using Python, Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, and XGBoost. Features data manipulation, visualizations, statistical tests, and ML modeling.

An end‑to‑end Snowflake ELT pipeline that ingests 2,460 ODI cricket match JSON files, cleans and transforms semi‑structured data into a dimensional star schema, and powers fast analytical queries on match‑level and ball‑by‑ball metrics.

Cricket data and analytics

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An end-to-end sports data analytics project leveraging web scraping, Python, pandas, and Power BI to analyze T20 World Cup cricket data.

In this sports data analytics project, we have used cricket T20 world cup (2022) data to build insights on a best 11 players team using bright data web scraping (from the ESPN Cricinfo website), python, pandas, and Power BI to perform analysis on T20 world cup cricket data.

Cricket-Data-Analysis – A cricket analytics dashboard that visualizes match and player statistics for deeper insights and performance analysis.

Hello Everyone👋, this project 💻 is based on Cricket 🏏data base that we took from Kaggle, link🔗 of which will be provided in the Readme. So basically the cricket database is used to create Data visualization(using Zoho analytics) and linked to the front end which is created using HTML, CSS and JavaScript. If you like it do share it with your friends😁😁

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End-to-end sports data analytics project for your resume. In this project, we will cover web scraping (from the ESPN Cricinfo website), python, pandas, and Power BI to perform analyses on T20 world cup cricket data.

🏏 Modern cricket analytics platform with real-time match data, player visualizations, and dark mode | Built with React, TypeScript, and Chart.js

The T20 Cricket Team Selection Dashboard is a Power BI project that uses data analytics for strategic team selection. It scrapes raw JSON data, preprocesses it with a Python notebook, and applies DAX measures to evaluate player performance.

End-to-end IPL (2008–2022) analytics project using SQL, Python, and Power BI. Perform match & ball-by-ball analysis, visualize top performers, toss impact, venue stats, and team trends. Clean ETL pipeline, interactive dashboards, and insights for data-driven cricket analysis.

ADSC Fall 24 Project for cricket analytics with hawkeye data

"Wincrics" is a cricket project offering insights into teams, matches, and predictions. It provides data analytics, match predictions, team rankings, player profiles, and historical data, enhancing the cricket experience for fans and enthusiasts.

Cricket Data Analytics

I have used cricket T20 world cup (2022) data to build insights on a best 11 players team that I can assemble from the earth that can go and play with aliens. We used bright data web scraping to collect data from espncricinfo website then I performed some data transformation and cleaning in pandas, followed by building dashboards in power bi.