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Artificial Intelligence for Smart in Match Winning Prediction in Twenty20 Cricket League Using Machine Learning Model

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Artificial Intelligence for Smart Healthcare

Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

Abstract

Artificial intelligence (AI) in cricket, particularly in the T20 series, has the most extreme vulnerability, where a one-over can change the force of the game. With many players in the Indian Premier League (IPL), building up a classic for foreseeing the result of IPL games is a genuine issue. A cricket coordinate relies on different elements, and in this work, the components that impact the consequences of T20 cricket matches are recognised. Every player’s execution on the field is measured to discover the total weight of the playing 11. A multivariate regression-based methodology is needed because each player measures points within the Indian Premier League. The pressure on an entire 11-player roster is controlled by the player’s experience, who has proven to be the best for the crew. Ultimately, a test log is displayed depending on the distinct variables that impact an IPL match. The participating teams decide a match’s fate, the venue, the city, the number of wickets, runs, etc. The IPL also depends on the toss; the team that wins and decides to bat or field is also crucial. These insights can be drawn by applying ML to our tested training dataset. ML is affecting our day-to-day lives in a fast and unimaginable way. AI was possible for everyday people to predict things that were always left to God or destiny.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India

    Maheswari Subburaj

  2. Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India

    Ganga Rama Koteswara Rao

  3. Department of Computer Science and Engineering, Ajay Kumar Garg Engineering College, Ghaziabad, Uttar Pradesh, India

    Binayak Parashar

  4. Department of Mechatronics Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, Tamil Nadu, India

    Indirapriyadharshini Jeyabalan

  5. Department of Computer Science and Engineering, Sri Shakthi Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India

    Hemalatha Semban

  6. Department of Computer Science and Engineering, PSN College of Engineering and Technology, Tirunelveli, Tamil Nadu, India

    Sudhakar Sengan

Authors
  1. Maheswari Subburaj
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  2. Ganga Rama Koteswara Rao
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  3. Binayak Parashar
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  4. Indirapriyadharshini Jeyabalan
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  5. Hemalatha Semban
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  6. Sudhakar Sengan
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Correspondence to Maheswari Subburaj .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, Jamia Hamdard, New Delhi, India

    Parul Agarwal

  2. Delhi Skill and Entrepreneurship University, Dwarka, Delhi, India

    Kavita Khanna

  3. Faculty of Computers and Artificial Intelligence, Beni-Suef University, Beni-Suef City, Egypt

    Ahmed A Elngar

  4. Faculty of Computer Science and Mathematics, University of Kufa, Najaf, Iraq

    Ahmed J. Obaid

  5. Jan Wyzykowski University, Polkowice, Poland

    Zdzislaw Polkowski

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Subburaj, M., Rao, G.R.K., Parashar, B., Jeyabalan, I., Semban, H., Sengan, S. (2023). Artificial Intelligence for Smart in Match Winning Prediction in Twenty20 Cricket League Using Machine Learning Model. In: Agarwal, P., Khanna, K., Elngar, A.A., Obaid, A.J., Polkowski, Z. (eds) Artificial Intelligence for Smart Healthcare. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-23602-0_3

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  • DOI: https://doi.org/10.1007/978-3-031-23602-0_3

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