🏏 Cricket Performance Predictor

A machine learning-based web app that predicts a cricketer's future performance using recent form, batting average, and strike rate.

📌 Overview

This project uses regression techniques to estimate performance output. It’s designed to assist analysts, players, or enthusiasts in understanding potential match outcomes based on player metrics.

🔧 Technologies Used

• Python
• Streamlit
• scikit-learn
• Pandas, NumPy

🚀 Features

• Input interface for recent match stats
• Linear Regression model prediction
• Accuracy evaluation with R² score
• Deployed live on Streamlit Cloud

📊 Dataset

A sample dataset with historical cricket statistics was used to train the model.

🖥 Live Demo

👉 Launch App

📂 Project Structure

cricket-performance-predictor/ ├── model.py ├── app.py ├── utils.py ├── dataset.csv └── requirements.txt

🧠 What I Learned

• Hands-on experience with regression and ML workflows
• Model evaluation techniques
• Building interactive UIs with Streamlit

📎 License

This project is open-source and free to use for educational purposes.

👤 Author: Hriday Goyal
🔗 GitHub | LinkedIn