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Jitendra Sai Kota,Mamatha Vayelapelli 대한전자공학회 2020 IEIE Transactions on Smart Processing & Computing Vol.9 No.3
With the advent of the Twenty20 format in cricket, the game has become more competitive. The number of nail-biting finishes that go to the last over has also increased as a result. As the game goes to the last over, the match result is mostly dependent on the effectiveness of batsmen at the crease and the player who is bowling the last over. This gave rise to an interesting idea for predicting the game result before the start of the final over based on the capabilities of the batsmen and the bowler. We used data from the first eight Indian Premier League (IPL) seasons as the training data, and from the last two IPL seasons as the test data. We trained and tested our model using Random Forest, Support Vector Machine (SVM) and k-nearest neighbors algorithms, and obtained the best accuracy using the SVM (89.36%).