Cricket Score Forecasting using Neural Networks
Prateek Gupta1, Navya Sanjna Joshi2, Raghuvansh Tahlan3, Darpan Gupta4, Saakshi Agrawal5

1Prateek Gupta*, Department of Computer Science & Engineering, Dr Akhilesh Das Gupta Institute of Technology & Management, New Delhi, India.
2Navya Sanjna Joshi, Department of Computer Science & Engineering, Dr Akhilesh Das Gupta Institute of Technology & Management, New Delhi, India.
3Raghuvansh Tahlan, Department of Computer Science & Engineering, Dr Akhilesh Das Gupta Institute of Technology & Management, New Delhi, India.
4Darpan Gupta, Department of Computer Science & Engineering, Dr Akhilesh Das Gupta Institute of Technology & Management, New Delhi, India.
5Ms. Saakshi Agrawal, Assistant Professor Department of Computer Science & Engineering, Dr Akhilesh Das Gupta Institute of Technology & Management, New Delhi, India.

Manuscript received on June 03, 2021. | Revised Manuscript received on June 10, 2021. | Manuscript published on June 30, 2021. | PP: 366-369 | Volume-10 Issue-5, June 2021. | Retrieval Number: 100.1/ijeat.E28210610521 | DOI: 10.35940/ijeat.E2821.0610521
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Abstract: 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. 
Keywords: Cricket analytics, Cricket Score Prediction, LSTM, Neural Network, Sports Analytics, RNN, Cricket Score Forecasting