Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Statistic analysis of IPL match score and winner inning wise using machine learning algorithms Subject The topic of the resource Cricket analytics; Data analysis; IPL score prediction; Machine learning; Predictive modeling Description An account of the resource This study explains the statistical analysis of cricket match score prediction using machine learning. According to recent changes in data science and sports, the use of sports-based machine learning and data mining shows the importance of process in outcome performance and prediction. The scope of this research paper is to evaluate current measurements used in the previous work to understand the estimation the ways used to model and analyze data and characterize the variables that govern performance using statistical methods. Actually, this research article will present a reliable statistical tool for data analysis using machine learning algorithms. At present, sports organizations produce enough statistical information on every player, team, match, and season for particular related sports. The first sports researchers were thought to be experts, coaches, team managers, and analysts. Sports organizations want to do statistical analysis of player from their previous data stored on their database using different data mining and machine learning algorithms. Sports data helps coaches and managers in many ways, such as predicting results, analyzing player performance, and skills, and evaluating strategies. Forecasts help managers and organizations make decisions to win teams and competitions. The current evaluation of research shows that primary studies of data mining systems can predict outcomes and evaluate the strengths and weaknesses of each system. Statistical analyses are made for each match for result predictions. Although in many respects this application is very limited. These are prime factors which important to examine machine learning algorithms in these situations to see if the application can give the nearest results in analysis. This research aims to give solutions that will help to make predictions more accurate and precise than previous methods, using more accurate data and machine learning. 2024, Taru Publications. All rights reserved. Creator An entity primarily responsible for making the resource Preety; Ray S.K.; Yadav M.; Khare A.; Mishra V. Source A related resource from which the described resource is derived Journal of Interdisciplinary Mathematics, Vol-27, No. 2, pp. 245-258. Publisher An entity responsible for making the resource available Taru Publications Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.47974/JIM-1819" target="_blank" rel="noreferrer noopener">https://doi.org/10.47974/JIM-1819</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188539125&amp;doi=10.47974%2FJIM-1819&amp;partnerID=40&amp;md5=44273e83e4dd30c8839e4fb2646fd185" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188539125&amp;doi=10.47974%2fJIM-1819&amp;partnerID=40&amp;md5=44273e83e4dd30c8839e4fb2646fd185</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 9720502 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Preety, Department of Computer Science, Christ University, Uttar Pradesh, Ghaziabad, India; Ray S.K., Department of Mathematics and Statistics, Dr. Akhilesh Das Gupta Institute of Technology &amp; Management, Delhi, India; Yadav M., Department of Information Technology, Galgotias College of Engineering and Technology, Uttar Pradesh, India; Khare A., Department of Computer Science and Engineering, Galgotias University, Uttar Pradesh, India; Mishra V., Department of Computer Science, Christ University, Uttar Pradesh, Ghaziabad, India