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 Conference Papers Conference Paper Faculty Publications- Conference Papers 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 Utilizing Machine Learning for Sport Data Analytics in Cricket: Score Prediction and Player Categorization Subject The topic of the resource Cricket analytics; Cricket prediction; Machine Learning; Player Classification; Regression and Classification; Score prediction Description An account of the resource Cricket is a popular sport with complex gameplay and numerous variables that contribute to team performance. In recent years, sports analytics has gained significant attention, aiming to extract valuable insights from large volumes of cricket data. Cricket has many fans in India. With a strong fan following, many try to use their cricket intuition to predict the outcome of a match. A set of rules and a points system govern the game. The venue and the performance of each player greatly affect the outcome of the match. The game is difficult to predict accurately as the various components are closely related. The CRR (Current Run Rate) approach is used to predict the final score of the first innings of a cricket match. Total points are calculated by multiplying the average number of runs scored in each over by the total number of overs. For ODI cricket, these methods are useless as the game can change very quickly regardless of the current run rate. The game may be decided by 1 or 2 overs. For more accurate score predictions, a system is needed that can more accurately predict the outcome of an inning. This research paper explores the application of machine learning techniques to predict scores and classify players based on their roles in the squad. The study utilizes a comprehensive dataset comprising various attributes of cricket matches, including player statistics, match conditions, and historical performance. Linear Regression, Logistic Regression, Naive Bayes, Support Vector Machines (SVM), Decision Tree, and Random Forest regression models are employed to predict scores. Additionally, player categorization is performed using a classification approach. The results demonstrate the effectiveness of machine learning techniques in enhancing performance analysis and decision-making in the game of cricket. 2023 IEEE. Creator An entity primarily responsible for making the resource Suguna R.; Praveen Kumar Y.; Suriya Prakash J.; Neethu P.S.; Kiran S. Source A related resource from which the described resource is derived 2023 IEEE 3rd Mysore Sub Section International Conference, MysuruCon 2023 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/MysuruCon59703.2023.10396955" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/MysuruCon59703.2023.10396955</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184821608&amp;doi=10.1109%2FMysuruCon59703.2023.10396955&amp;partnerID=40&amp;md5=69cf6c86786d9dc70ec4b7a34b10ed00" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184821608&amp;doi=10.1109%2fMysuruCon59703.2023.10396955&amp;partnerID=40&amp;md5=69cf6c86786d9dc70ec4b7a34b10ed00</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835034035-8 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 Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Suguna R., Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, Department of Computer Science and Engineering, Chennai, India; Praveen Kumar Y., Vidhya Jyothi Institute of Technology, Department of Computer Science and Engineering, Hyderabad, India; Suriya Prakash J., JAIN (Deemed-to-be-University), Department of Computer Science and Engineering, Bengaluru, India; Neethu P.S., CHRIST (Deemed to Be University), School of Engineering and Technology, Bengaluru, India; Kiran S., Nitte Meenakshi Institute of Technology, Department of Mathematics, Bangalore, India