Abstract
This research paper focuses on the use of natural language processing techniques for extracting insights from cricket commentary. This study proposes a framework that considers the commentary text, evaluates each player’s performance, and gives valuebased scores to define their impacts. This research relies on sentiment analysis, topic modeling, and NER to analyze a large corpus of cricket commentary data and develop a model for calculating the impacts of the players. The findings of this study will be of great interest to sports analysts, coaches, players, and fans of the game. This research explores cricket analytics and performance evaluation evolution, utilizing advanced textual analysis on cricket commentary to uncover hidden dimensions of player performance. This study has the potential to revolutionize player performance evaluation in cricket by identifying ”hidden gems” that may have been overlooked based on conventional statistics alone.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
