5523616
doi
10.35940/ijeat.E2821.0610521
oai:zenodo.org:5523616
Blue Eyes Intelligence Engineering and Sciences Publication(BEIESP)
Publisher
Navya Sanjna Joshi
Department of Computer Science & Engineering, Dr Akhilesh Das Gupta Institute of Technology & Management, New Delhi, India
Raghuvansh Tahlan
Department of Computer Science & Engineering, Dr Akhilesh Das Gupta Institute of Technology & Management, New Delhi, India
Darpan Gupta
Department of Computer Science & Engineering, Dr Akhilesh Das Gupta Institute of Technology & Management, New Delhi, India
Saakshi Agrawal
Assistant Professor Department of Computer Science & Engineering, Dr Akhilesh Das Gupta Institute of Technology & Management, New Delhi, India.
Cricket Score Forecasting using Neural Networks
Prateek Gupta
Department of Computer Science & Engineering, Dr Akhilesh Das Gupta Institute of Technology & Management, New Delhi, India
issn:2249-8958
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Cricket analytics, Cricket Score Prediction, LSTM, Neural Network, Sports Analytics, RNN, Cricket Score Forecasting
<p>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.</p>
Zenodo
2021-06-30
info:eu-repo/semantics/article
5523615
1632404914.246856
677967
md5:f56aa3d73b341f3552998df7a31111d9
https://zenodo.org/records/5523616/files/E28210610521.pdf
public
2249-8958
Is cited by
issn
International Journal of Engineering and Advanced Technology (IJEAT)
10
5
366-369
2021-06-30