Course Content

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.

So we proposed a system in our project to predict IPL Match Winning Team with the help of machine learning techniques and algorithms like Logistic Regression, KNN, SVC, Decision Tree and Random Forest based on different parameters entered by the user in the front end.

Introduction:

The main aim is to use Machine learning to develop the computer programs which will be capable of retrieving data and using it for self-learning. The procedure of learning commences with observations of data, such as instances, direct experience, or training, in order to identify some patterns in statistics and take improved decisions in the future built on the samples that are provided. Machine Learning primarily aims at eliminating the human intervention or assistance by allowing the computers learn automatically and adjust its actions accordingly. The advancement in computing in the recent years, has made it increasingly easy to acquire in-depth information. As a consequence, the fact of having both live and historic data has made Machine Learning quite popular in the fields of sports analytics. Sports Analytics is a method of collecting and analyzing historical game information to derive essential knowledge from it, with the aim that it will promote successful decision-making. Indian Premier League is a T20 League which was started in 2008 and now became the most irresistible T20 cricket carnival. Since the IPL has large popularity, predicting the results of it is really important and to be more effective

So we proposed a system in our project to predict IPL Match Winning Team with the help of machine learning techniques and algorithms like Logistic Regression, KNN, SVC, Decision Tree and Random Forest based on different parameters entered by the user in the front end.

Objective:

The main aim of this project to predict the IPL match winner using machine learning techniques and algorithms like Logistic Regression, KNN, SVC, Random Forest, Decision Tree and Naïve Bayes based on different parameters entered by the user in the front end.

Problem Statement

Cricket is one of the most popular sports in the whole world, and also one of the most popular sports in India. Cricketing events such as the Indian Premier League (IPL) are thoroughly enjoyed by fans all across the country. Fans of the game love predicting the ongoing match results, and this is something that has ended up being a hobby for several people who follow the game. This is a sport with abundant amount of data and using this data, we can make an evaluation on whether a team can win an ongoing IPL match or not.

Proposed System:

We proposed a system in our project to predict IPL Match Winning Team with the help of machine learning techniques and algorithms like Logistic Regression, KNN, SVC, Decision Tree and Random Forest based on different parameters entered by the user in the front end.