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@article{160167,
        author = {Samprathi.B.E and Vamshi K V and Naveen Kumar M N and C Anil Kumar and Dipti Patnayak},
        title = {Sports Data Predictive Analysis using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {12},
        pages = {1307-1312},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=160167},
        abstract = {A prediction system is critical for reducing curiosity about anything. Many sports prediction techniques are popular, and data analysis plays an important role in forecasting. Previous attempts in sports data analysis have resulted in the prediction of sports such as football, tennis next shot location prediction, Olympic athlete performance, basketball slam dunk shot frequency, and many more. Cricket prediction is tough due to the numerous variables that might affect the result or outcome of a cricket match. Previously, simple cricket match prediction systems focused just on the venue, ignoring aspects such as weather, stadium size, captaincy, and so on. Factors such as the match's location, pitch, weather conditions, first-pitch batting, and fielding all play a role in forecasting the match's outcome. To predict, suitable models are required, and data mining allows the required information to be extracted from data sets. This project is a review of techniques used for predicting the winners of three different games. The statistical data of the game can be exploited using various machine learning techniques to predict various information related to a particular match namely the result of a particular game, injury of a player, performance of a player in a particular match, spotting new talents in the game, etc. The aim is to accurately predict the winner of a particular game},
        keywords = {},
        month = {},
        }