/IPL-cricket-index

A cricket batting index is a metric and its purpose is to provide a single, comprehensive measure of a batsman's performance that takes into account multiple aspects of their ability to score runs.

IPL Cricket Index

A cricket batting index is a metric that is used to evaluate the performance of a cricket batsman. It is a composite measure that takes into account a variety of factors related to a batsman's ability to score runs, including batting average, strike rate, centuries, and other metrics.

There are various ways to calculate a cricket batting index, and different methods may place different emphasis on different factors. Some cricket batting indices may give more weight to batting average, while others may focus more on strike rate or other metrics.

The purpose of a cricket batting index is to provide a single, comprehensive measure of a batsman's performance that takes into account multiple aspects of their ability to score runs. It can be used to compare the performance of different batsmen, to rank batsmen within a team or league, or to evaluate the overall strength of a team's batting lineup.

IPL 2022 Performance Cricket Index

This cricket index has been made using multiple layers of weighted models

What is a weighted model?

A weighted model is a statistical model in which the contributions of different variables to the model's prediction are assigned different weights, or coefficients. These weights reflect the relative importance or influence of each variable on the outcome of the model. For example, in a linear regression model, the weights are the coefficients that are assigned to each predictor variable. These coefficients indicate the strength and direction of the relationship between the predictor variable and the outcome variable, and they are used to make predictions about the outcome based on the values of the predictor variables.

Weighted models can be useful when some variables are more important or relevant than others in predicting the outcome of interest. By assigning higher weights to these variables, the model can better capture the relationship between the variables and the outcome. Weighted models can also be used to downweight the influence of outliers or extreme values in the data, which can help to improve the accuracy and stability of the model.

A percentile has been made with the highest batting strength being 10 percentile

Contributors-

Aditya Pachpande
Aaryan Shah
Smayan Yambal

Link to Project:- https://docs.google.com/spreadsheets/d/1RCmn6XXh-bUhStYrwT8-bMc0UOVQUr7ZeTWUqzH0jQY/edit?usp=sharing