IPL Base Price Modelling & Visualization using Linear Regression

Authors: Rajat Chelani

Country: India

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Abstract: The Indian Premier League (IPL) is a professional Twenty20 cricket league in India contested during April and May of every year by teams representing Indian cities. The aim of the research was to predict the base price of players for IPL Auction. The performance of players from different leagues and world tournaments were collected and important features including Runs Scored, Strike Rate, Average, Wickets, Economy Rate were considered. The initial step of our action plan was to clean the data for which we used Python’s Pandas. Once the data was cleansed and organized in a structured way, we calculated the Base Price Score, which was a summation of the extracted features, and each feature had its own weightage depending on the impact on IPL. The next step was to calculate the Average Score depending on the weightage given on the basis of different leagues and tournaments. The machine algorithm which was used here was Multiple Linear Regression as, in the above case, we had multiple dependent variables for an independent variable i.e. Base Price Score. For measuring the accuracy of the model, Root Mean Square Error method was incorporated.

Keywords: IPL, Linear Regression, Price Prediction, T-20

Paper Id: 1276

Published On: 2021-10-29

Published In: Volume 9, Issue 5, September-October 2021

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