Automated Cricket Shot Detection: Enhancing Performance and Engagement Through Real-Time Analysis

As a dynamic sport, Cricket provides various complex shots which are extremely precise to execute and hard to classify. Shot identification or classification is based on the manual method which prone to error and time consuming. For improving the performance and coaching the cricket players, this paper purpose a system which can detect the shots for different games. In this research, by using advanced algorithm properties for analyzing the player movements and shot patter, the authors propose an automated shot detection and classifying model that provide a data driven way for highlighting the cricket performance. Moreover, it responds to the perpetual challenges in terms of the lack of access to high-quality data and elevated costs that current systems present. Such a solution can be scaled and utilized at various levels of the sport. The system's real-time classification feature that can be linked to broadcasts has the potential of creating a more in-depth understanding of players' performance, which may attract more spectators to the sport, as they would have a chance to differentiate between different types of shots. This research responds to the increasing interest in sports analytics and writes a chapter in the field by offering a new approach to automatic shot detection in cricket.