dc.contributor.advisor | Biswas, Rubel | |
dc.contributor.advisor | Mostakim, Moin | |
dc.contributor.author | Munir, Fahad | |
dc.contributor.author | Hasan, Md. Kamrul | |
dc.contributor.author | Ahmed, Sakib | |
dc.contributor.author | Md. Quraish, Sultan | |
dc.date.accessioned | 2015-09-03T06:38:44Z | |
dc.date.available | 2015-09-03T06:38:44Z | |
dc.date.copyright | 2015 | |
dc.date.issued | 8/23/2015 | |
dc.identifier.other | ID 11201014 | |
dc.identifier.other | ID 11201032 | |
dc.identifier.other | ID 11201009 | |
dc.identifier.other | ID 11201017 | |
dc.identifier.uri | http://hdl.handle.net/10361/4372 | |
dc.description | Cataloged from PDF version of thesis report. | |
dc.description | Includes bibliographical references (page 55-56). | |
dc.description | This 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.abstract | Data 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.statementofresponsibility | Fahad Munir | |
dc.description.statementofresponsibility | Md. Kamrul Hasan | |
dc.description.statementofresponsibility | Sakib Ahmed | |
dc.description.statementofresponsibility | Sultan Md. Quraish | |
dc.format.extent | 56 pages | |
dc.language.iso | en | en_US |
dc.publisher | BRAC University | en_US |
dc.rights | BRAC 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.subject | Data mining | |
dc.subject | Forecasting | |
dc.subject | Results | |
dc.subject | IPL | |
dc.subject | Linear Regression | |
dc.subject | Machine learning | |
dc.subject | Computer science and engineering | en_US |
dc.subject | T20 cricket | en_US |
dc.title | Predicting a T20 cricket match result while the match is in progress | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, BRAC University | |
dc.description.degree | B. Computer Science and Engineering | |