  India's most popular sport is cricket and is played across all over the
nation in different formats like T20, ODI, and Test. The Indian Premier League
(IPL) is a national cricket match where players are drawn from regional teams
of India, National Team and also from international team. Many factors like
live streaming, radio, TV broadcast made this league as popular among cricket
fans. The prediction of the outcome of the IPL matches is very important for
online traders and sponsors. We can predict the match between two teams based
on various factors like team composition, batting and bowling averages of each
player in the team, and the team's success in their previous matches, in
addition to traditional factors such as toss, venue, and day-night, the
probability of winning by batting first at a specified match venue against a
specific team. In this paper, we have proposed a model for predicting outcome
of the IPL matches using Machine learning Algorithms namely SVM, Random Forest
Classifier (RFC), Logistic Regression and K-Nearest Neighbor. Experimental
results showed that the Random Forest algorithm outperforms other algorithms
with an accuracy of 88.10%.
