Since the dawn of the IPL in 2008, it has attracted viewers all around the globe. A high level of uncertainty and last-minute nail-biters have urged fans to watch the matches. Within a short period, the IPL has become the highest revenue-generating league in cricket. In a cricket match, we often see the scoreline showing the probability of the team winning based on the current match situation. This prediction is usually done with the help of data analytics. Before, when there were no advancements in machine learning, predictions were usually based on intuition or some basic algorithms. The above picture clearly tells you how bad it is to take run rate as a single factor to predict the final score in a limited-overs cricket match.
We've harnessed the power of machine learning and Django to create a groundbreaking project focused on enhancing cricket match predictions. In the dynamic landscape of IPL cricket, where uncertainty and thrilling moments reign supreme, our project stands out by providing accurate score predictions based on sophisticated data analytics. Gone are the days of relying solely on intuition or basic algorithms. Our innovative approach showcases the limitations of using run rate as a single factor in predicting the final score of limited-overs cricket matches. Through this project, we aim to revolutionize how fans engage with the game, leveraging advanced technology to deliver more precise and insightful predictions.
