Involvement of Computing to Improve Decision Making in Cricket
Jahangir Kamal1, Manoj Kumar2, Kailash Kumar3, Aditya Tandon4, Phong Thanh Nguyen5
1Jahangir Kamal, Jagannath University, Jaipur (Rajasthan), India.
2Manoj Kumar, Ph.D Scholar, Jagannath University, Jaipur (Rajasthan), India.
3Kailash Kumar, Assistant Professor, Department of CSE, Manav Rachna University, Faridabad (Haryana), India.
4Aditya Tandon, Assistant Professor, College of Computing and Informatics, Saudi Electronic University, Riyadh, Kingdom of Saudi Arabia.
5Phong Thanh Nguyen, Research Scholar, Director, Amity University, Department of Project Management, Ho Chi Minh City Open University, Vietnam.
Manuscript received on 15 May 2019 | Revised Manuscript received on 19 May 2019 | Manuscript Published on 23 May 2019 | PP: 2096-2101 | Volume-7 Issue-6S5 April 2019 | Retrieval Number: F13760476S519/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In shorter format of Cricket, the choice of a bowler has three main parameters namely: economy, strike rate and dot balls delivered. In most of the cases, the most hitting parameters are economy rate and number of wickets taken, which again are inter related with the dot balls delivered. This paper presents a survey operational linear approach which comparative analyze the above-cited three parameters and suggests a solution based approach to choose a best bowler in “Playing Eleven” with highest preference to the dot balls delivered. The inter-relationship among these parameters are established based on collected data. The proposed indicator is proved useful while making decisions. A software-based architecture is also proposed relating to decision support system for selecting a bowler in playing eleven using past data.
Keywords: Twenty-Twenty Match, Cricket, Bowler Selection, Indicator, Parameter, Decision Tree, Bowling Score.
Scope of the Article: Parallel Computing on GPU