• Srinivasa Reddy gajjala
• Deepika Gonnabattula
• Manideep kanakam
• Sai Swaroop Maddipudi

Cricket is a very familiar and exciting sport that people of all age groups are insane to see and play. For many it's a billion-dollar market as they speculate financially, hoping to be able to earn profit in the form of gambling and various other ways. In this project, a model using machine learning algorithms is proposed to predict the score of each match and winning team based on past datasets available from 2008 to 2019 IPL matches in Kaggle. This proposed methodology includes the following steps like Pre-processing of collected datasets, Feature selection from raw data, Conversion of categorical data into numerical data, Partitioning of samples into training and test samples, Training, and classification. Few machine learning algorithms like Support Vector Machine, Random Forest, Naive Bayes were already used in previous papers. In this project, algorithms like Lasso Regression, Ridge Regression, and Random Forest regression models are proposed for a score prediction, and SVM(Linear, RBF), Logistic Regression classifier is for the match-winning prediction. The accuracy of the above machine learning algorithms is used to predict the winner of an IPL match along with its Precision, Recall and F-Measure measured and the model with better accuracy is considered.

Cricket, IPL, Machine Learning, Regression, Classification

"Prediction of IPL Match Score and Winner Using Machine Learning Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.c437-c444, June-2021, Available :http://www.jetir.org/papers/JETIR2106333.pdf

"Prediction of IPL Match Score and Winner Using Machine Learning Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppc437-c444, June-2021, Available at : http://www.jetir.org/papers/JETIR2106333.pdf