Journal article Open Access

Cricket Score Forecasting using Neural Networks

Prateek Gupta; Navya Sanjna Joshi; Raghuvansh Tahlan; Darpan Gupta; Saakshi Agrawal

Blue Eyes Intelligence Engineering and Sciences Publication(BEIESP)

Today, Sports is not what it used to be a decade ago. Technologies like Machine Learning and Artificial Intelligence have dominated it. Now there are sensors in all types of sports equipment like cricket bats, stumps, flannels, etc., which analyse the data and provide analytics, which may or may not be helpful, but we, as spectators, thoroughly enjoy the game. The terms such as Cric-Science (Cricket + Data Science) and Cricket Analytics are the fruit of ML/AI. In the last decade alone, cricket has witnessed many changes, such as the addition of a new format like T10, which is yet to be recognised by ICC, along with the introduction of many other international leagues such as IPL, BBL, PSL, CPL, apart from the widely recognised formats like Test Match, One day International and T20. With so much cricket played, the data generated is also massive. But even with these technological advancements, run rate is conventionally used to predict a team’s score in the upcoming overs. So, in this research paper, we aim to predict a team’s score using Neural Network by using the data from past balls.

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