Predictive Analysis of IPL Match Winner using Machine Learning Techniques
Ch Sai Abhishek1, Ketaki V Patil2, P Yuktha3, Meghana K S4, MV Sudhamani5
1Chakka Sai Abhishek, Pursued Bachelor, Department of Technology Information Science Engineering, RNS Institute of Technology, Bengaluru (Karnataka), India.
2Ketaki Vinod Patil, Pursued Bachelor, Department of Technology Information Science Engineering, RNS Institute of Technology, Bengaluru (Karnataka), India.
3Yuktha P, Pursued Bachelor, Department of Technology Information Science Engineering, RNS Institute of Technology, Bengaluru (Karnataka), India.
4Meghana K S, Pursued Bachelor, Department of Technology Information Science Engineering, RNS Institute of Technology, Bengaluru (Karnataka), India.
5Dr. M V Sudhamani, Professor and HOD, Department of ISE, RNSIT, Bengaluru (Karnataka), India.
Manuscript received on 05 December 2019 | Revised Manuscript received on 13 December 2019 | Manuscript Published on 31 December 2019 | PP: 430-435 | Volume-9 Issue-2S December 2019 | Retrieval Number: B10431292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1043.1292S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Artificial intelligence (AI) can be implemented using Machine Learning which allows the computing to potentially robotically study and improve from its previous experiences without being manually typed. Data can be accessed and used by the computer programs developed using Machine learning. This paper mainly focused on implementation of machine learning in the arena of sports to predict the captivating team of an IPL match. Cricket is a popular uncertain sport, particularly the T-20 format, there’s a possibility of the complete game play to change with the effect of any single over. Millions of spectators watch the Indian Premier League (IPL) every year, hence it becomes a real-time problem to compose a technique that will forecast the conclusion of matches. Many aspects and features determine the result of a cricket match each of which has a weighted impact on the result of a T20 cricket match. This paper describes all those features in detail. A multivariate regression-based approach is proposed to measure the team’s points in the league. The past performance of every team determines its probability of winning a match against a particular opponent. Finally, a set of seven factors or attributes is identified that can be used for predicting the IPL match winner. Various machine learning models were trained and used to perform within the time lapse between the toss and initiation of the match, to predict the winner. The performance of the model developed are evaluated with various classification techniques where Random Forest and Decision Tree have given good results.
Keywords: Cricket Prediction, Decision Trees, KNN, Logistic Regression, Multivariate Regression, Random Forest, SVM, Sports Analysis.
Scope of the Article: Machine Learning