Predicting T20 International Cricket Scores using Machine Learning: An Evaluation of Six Different Algorithms

About the project

The Current Run Rate (CRR) method is currently used to predict the final score in T20 cricket matches. This method involves multiplying the average runs scored in an over by the total number of overs. However, this approach is not effective for T20 matches, where the match can rapidly change within a few overs, regardless of the current run rate. To accurately predict the score, a more efficient system is needed. Given that many people enjoy watching cricket and predicting the final score, this project aims to develop an accurate prediction system for live T20 International matches. We consider various factors that can impact the score prediction and utilize the available previous matches data to achieve a more accurate prediction

Research Paper

Click here

Predicted Scores Comparison of Algorithms

Dependencies

• Install required libraries like pandas, numpy, flask, catboost etc. using pip
• For Eg.

pip install catboost

Installing

• Download this repo or clone it using 'git clone'

Executing program

• Open the project folder where basic.py is present.
• Create a virtual environment

python -m venv env

• Activate it

source env/bin/activate    # For Linux/MacOS
env\Scripts\activate.bat   # For Windows

• Set the FLASK_APP environment variable to your application

export FLASK_APP=app.py    # For Linux/MacOS
set FLASK_APP=app.py       # For Windows

• Run the Flask application

flask run

• You can now use the web portal from your browser

Web Portal Samples

Contact

Your Name - @linkedin - [email protected]