An Analysis of Bangladesh One Day International Cricket Data: A Machine Learning Approach

TLDR: This work analyzed One Day International cricket data of Bangladesh, based on seventeen features and finds out the most important features that are enough for better prediction, not only important features but also can take much decision in the authors' analysis.

Abstract: Nowadays Data mining is an emerging field in sports analysis. To choose a most effective team or to predict suitable formation for winning a game or to analyze weakness of the opponent, data mining plays a vital role. However, no research has been done yet for the Bangladesh cricket team. So, we analyzed One Day International cricket data of Bangladesh, based on seventeen features and find out the most important features that are enough for better prediction, not only important features but also can take much decision in our analysis. Our analysis divided into three sections; before starting the game, after one innings played and continuous fall of wickets which leads to the probable prediction of the chances of winning and losing even while the game is in progress. In our analysis, we used the latest version of the decision tree algorithm that is C5.0 on our own collected data set and successfully get the accuracy of 63.63% for before starting the game, 72.72% and 81.81% when Bangladesh played in the first and second innings, finally 80% and 70% for fall of wicket analysis. We also used other classification algorithms and shown the accuracy level of our data set.