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@article{164471,
        author = {Shivansh Singhal and Dr. Manoj Kumar Singh and Siddhant Chaurasiya and Vishal Gupta and Shwetansh Srivastava and Shiva Sharma},
        title = {IPL Score Prediction Using Machine Learning },
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {12},
        pages = {2894-2899},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=164471},
        abstract = {Cricket holds the title of being the most favoured sport in India, with matches being played across all regions in formats like T20, ODI, and Test. The Indian Premier League (IPL) sees participation from Indian regional teams, the national squad, and international teams, making it a highly anticipated national cricket competition. The IPL has gained immense popularity among cricket fans due to its live streaming, radio coverage, and TV broadcasts. Predicting the outcomes of IPL matches is of great importance for online traders and sponsors. Apart from traditional factors like the toss, venue, and day-night conditions, we can analyse various team characteristics such as composition, batting and bowling averages of players, and past match performances to anticipate the results of a match between two teams.},
        keywords = {Cricket Prediction, Cricket analysis, Lasso Regression, Naive Bayes, Logistic Regression, Random Forest Classifier.},
        month = {},
        }