• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology


Indian Journal of Science and Technology

Year: 2020, Volume: 13, Issue: 34, Pages: 3586-3599

Original Article

Is the performance of a cricket team really unpredictable? A case study on Pakistan team using machine learning

Received Date:07 June 2020, Accepted Date:27 July 2020, Published Date:24 September 2020


Cricket is the second most popular game around the globe, particularly it breeds a high level of enthusiasm in Asia, Australia and UK. However, it is generally known and globally mentioned that Pakistan is an “unpredictable” cricket team, which leads to extreme reactions from the citizens in case of a loss, e.g., verbal anger, breaking of television sets and burning of players’ effigies. Objectives: In this study, we leverage machine learning techniques to demonstrate that the use of the “unpredictable” tag for Pakistan’s cricket performance is unjustified as the match outcome can be predicted with a pretty high confidence. Method: We produce a new dataset by scrapping latest statistics from cricinfo.com, the most reliable online source. Also, we propose a novel feature “consecutive wins” that incorporates recent performance trend of the team. With extensive experimental setup, state-of-the-art machine learning methodology was employed to prove effectiveness of proposed tool. Findings: Pakistan’s cricket performance can be predicted with 82% accuracy, i.e., it is possible to understand the patterns (in advance) which may lead to a winning or losing situation. Hence, using pre-match analysis, it is possible to avoid any prejudiced opinion or potentially dangerous reactions. Novelty: We employ state-of-the-art machine learning methodology based on application of various algorithms, feature selection and data splitting methods. Eventually, state-of-the-art prediction accuracy is achieved by exploiting all potential avenues in a structured way.

Keywords: Cricket, one day international, Pakistan, machine learning, performance, unpredictable


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© 2020 Ahmed et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee).


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