Optimal feature selection for cricket talent identification

Abstract

Cricket talent identification (TiD) is a methodical process that aims to find the young athletes possessing a potential to excel in the cricket sport at an early age. The sports scientists have identified a set of twenty-eight parameters that determine the cricket TiD. In order to realize the objective of computational efficiency by reducing the feature set, we perform an optimal feature selection for cricket TiD using nine different feature selection techniques Viz. mutual information, information gain ratio, correlation, chi square, univariate root mean square error (RMSE), receiver operating characteristic (ROC) with decision tree classifier, reliefF, boruta and oneR. The individual results obtained from the feature selection techniques are provided along with the individual ranking. We aggregate the results using two different rank aggregation techniques namely average ranking aggregation and majority vote ranking aggregation. The aggregation resultsshow a significant agreement between the two schemes. Fourteen out of twenty-eight features are selected using a threshold of 0.52-the value selected on recommendation of four different domain experts. 71.4% of the selected features are sport-centric and only 28.6% of the selected features are from the cognitive ability category. To the best of our knowledge, this is first such attempt to identify the talent in cricket using this methodology.