Analysis and classification of strike rate of a cricketer: Using machine learning techniques

Nowadays machine learning and data science, one of the most applied fields of computer science and it has a notable impact on the game of cricket. In this paper we use various ML techniques on cricket. We use 3 different classifiers and one clustering technique. We propose a simple ML based model that classifies data into three different categories that is corresponding to three different formats of cricket. We followed data science life cycle in overall this paper. We compare four ML classifiers in our paper and conclude to the best result. In our data set SVM is best in terms of result and we justify this result with proper statements and figures. And that comparative study is unique to this paper.