Vol.69, No.1, 2021, pp.1215-1232, doi:10.32604/cmc.2021.016659
OPEN ACCESS
ARTICLE
Evolution-Based Performance Prediction of Star Cricketers
  • Haseeb Ahmad1, Shahbaz Ahmad1, Muhammad Asif1, Mobashar Rehman2,*, Abdullah Alharbi3, Zahid Ullah4
1 Department of Computer Science, National Textile University, Faisalabad, Pakistan
2 Faculty of Information and Communication Technology, Universiti Tunku Abdul Rahman, Kampar, 31900, Perak, Malaysia
3 Department of Information Technology, College of Computers and Information Technology, Taif University, Taif, 21944, Saudi Arabia
4 Department of Information Systems, King Abdulaziz University, Jeddah, Saudi Arabia
* Corresponding Author: Mobashar Rehman. Email:
(This article belongs to this Special Issue: AI for Wearable Sensing--Smartphone / Smartwatch User Identification / Authentication)
Received 07 January 2021; Accepted 01 March 2021; Issue published 04 June 2021
Abstract
Cricket databases contain rich and useful information to examine and forecasting patterns and trends. This paper predicts Star Cricketers (SCs) from batting and bowling domains by employing supervised machine learning models. With this aim, each player’s performance evolution is retrieved by using effective features that incorporate the standard performance measures of each player and their peers. Prediction is performed by applying Bayesian-rule, function and decision-tree-based models. Experimental evaluations are performed to validate the applicability of the proposed approach. In particular, the impact of the individual features on the prediction of SCs are analyzed. Moreover, the category and model-wise feature evaluations are also conducted. A cross-validation mechanism is applied to validate the performance of our proposed approach which further confirms that the incorporated features are statistically significant. Finally, leading SCs are extracted based on their performance evolution scores and their standings are cross-checked with those provided by the International Cricket Council.
Keywords
Online social databases; cricket; star cricketers; prediction; machine learning
Cite This Article
H. Ahmad, S. Ahmad, M. Asif, M. Rehman, A. Alharbi et al., "Evolution-based performance prediction of star cricketers," Computers, Materials & Continua, vol. 69, no.1, pp. 1215–1232, 2021.
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