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dc.contributor.advisorBiswas, Rubel
dc.contributor.advisorMostakim, Moin
dc.contributor.authorMunir, Fahad
dc.contributor.authorHasan, Md. Kamrul
dc.contributor.authorAhmed, Sakib
dc.contributor.authorMd. Quraish, Sultan
dc.date.accessioned2015-09-03T06:38:44Z
dc.date.available2015-09-03T06:38:44Z
dc.date.copyright2015
dc.date.issued8/23/2015
dc.identifier.otherID 11201014
dc.identifier.otherID 11201032
dc.identifier.otherID 11201009
dc.identifier.otherID 11201017
dc.identifier.urihttp://hdl.handle.net/10361/4372
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (page 55-56).
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2015.en_US
dc.description.abstractData Mining and Machine learning in Sports Analytics, is a brand new research field in Computer Science with a lot of challenge. In this research the goal is to design a result prediction system for a T20 cricket match while the match is in progress. Different machine learning and statistical approach were taken to find out the best pos- sible outcome. A very popular data mining algorithm, decision tree were used in this research along with Multiple Linear Regression in order to make a comparison of the results found. These two model are very much popular in predictive modeling. Forecasting a T20 cricket match is a challenge as the momentum of the game can change dras- tically at any moment. As no such work has done regarding this for- mat of cricket, we have decided to take the challenge as T20 cricket matches are very much popular now a days. We are using decision tree algorithm to design our forecasting system by depending on the previous data of matches played between the teams. This system will help the teams to take major decision when the match is in progress such as when to send which batsman or which bowler to bowl in the middle overs. It significantly expands the exposure of research in sports analytics as it was previously bound between some other selected sports.en_US
dc.description.statementofresponsibilityFahad Munir
dc.description.statementofresponsibilityMd. Kamrul Hasan
dc.description.statementofresponsibilitySakib Ahmed
dc.description.statementofresponsibilitySultan Md. Quraish
dc.format.extent56 pages
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectData mining
dc.subjectForecasting
dc.subjectResults
dc.subjectIPL
dc.subjectLinear Regression
dc.subjectMachine learning
dc.subjectComputer science and engineeringen_US
dc.subjectT20 cricketen_US
dc.titlePredicting a T20 cricket match result while the match is in progressen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University
dc.description.degreeB. Computer Science and Engineering


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