Cricket Player Selection using Machine Learning 
I. Sri Ram Teja1, T. Pavan Kalyan2, V. Akhil Kumar Reddy3
1I,Sri Ram Teja* ,Department of Computer Science and Engineering, K L University.
2T.Pavan Kalyan, Department of Computer Science and Engineering, K L University.
3V.Akhil Kumar Reddy, Department of Computer Science and Engineering, K L University.
Manuscript received on May 03, 2020. | Revised Manuscript received on May 15, 2020. | Manuscript published on June 30, 2020. | PP: 68-71 | Volume-9 Issue-5, June 2020. | Retrieval Number: E9291069520/2020©BEIESP | DOI: 10.35940/ijeat.E9291.069520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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, AdaBoost, Support Vector Machines(SVM), LightGBM,CatBoost, 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.
Keywords: Support Vector Machines, Naïve Bayes, Ada Boost, LightGBM, random forest, Linear Discriminant Analysis, Voting Classifier,Cat Boost,Logistic Regression