• Abhishek Ganesh Naik
• Sahil Mulani
• Minakshee Naik
• Shivanee Pawar

Cricket prediction can be viewed as one of the objectives of sports analytics, which aims at helping decision makers to gain competitive advantage. The difficulty of this task depends on many factors, like the availability of data for the past events, the ability to gather data for future events, the knowledge needed to interpret gathered data, and others. Various techniques for modeling a cricket match exist that yield different result prediction algorithms. The modeling can be put under the four generic categories: empirical models, dynamic systems, statistical techniques and artificial intelligence (including expert systems). In the artificial intelligence category, there are several approaches that focus on Bayesian network modeling. The Matrix factorization technique became very popular in the field of multimedia content recommender systems where it showed good scalability and predictive accuracy. The idea behind using the latent features in our case is to be able to build a successful model over existing matrix factorization.

Neural Network, Linear Regression, Clustering, Decision Tree.

"Winning Prediction in One Day International (ODI) Cricket using Machine Learning Techniques.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 5, page no.104-107, May-2018, Available :http://www.jetir.org/papers/JETIR1805445.pdf

"Winning Prediction in One Day International (ODI) Cricket using Machine Learning Techniques.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 5, page no. pp104-107, May-2018, Available at : http://www.jetir.org/papers/JETIR1805445.pdf