Abstract
Cricket has always been a popular game since its invention in the world. Moreover, it became a religion in India. The selection committees like BCCI,PCB,ACB etc. pick the players based on their previous performances in domestic cricket tournaments like IPL,Ranji Trophy, Syed Mushtaq Ali Trophy etc. by committee decisions but there is no application for selection process till now. To develop an application we need player performance analysis and assessment. This paper suggests an important approach for Selecting Cricket players by Evaluating his Statistics and Provides a comparative look at machine learning techniques in cricket player selection. In this paper a model for Bowlers and Batsmen Separately was proposed which was implemented using Random Forest, Ada Boost, Support Vector Machines(SVM), Light GBM, Cat Boost, Logistic Regression Linear Discriminant Analysis(LDA), Voting Classifier, Naïve Bayes. The findings obtained by the suggested methodology in this paper are the same as in the Cricket board selected team players.
Highlights
INTRODUCTIONCricket is the game with the most popularity in the country India. Test, ODI, T20 are recognized formats
There are many, the mentioned statistics are much important for batsmen as well as bowler in every format These make batsmen selected, Experience plays a crucial role in Big Matches like World Cup, ICC events etc
For batsmen dataset Random Forest and AdaBoost outperformed among all other algorithms
Summary
Cricket is the game with the most popularity in the country India. Test, ODI, T20 are recognized formats. In every format certain statistics of a player are very important for batsmen as well as bowler. There are many, the mentioned statistics are much important for batsmen as well as bowler in every format These make batsmen selected , Experience plays a crucial role in Big Matches like World Cup, ICC events etc. If the senior player is Selected and he gets injured in those Conditions , our System plays a major role in selecting the players who are good at first class matches. It gives a better opportunity for players who are willing to showcase their talent in international matches. To deploy the machine learning model as a web application for usage
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Engineering and Advanced Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
