Near-Real-Time Data Collection

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The collection of near-real-time data could utilize and incorporate various sources in cricket. Wearable technologies, tracking technologies, and cameras could help capture data on player performance, like biometric information, ball-ball statistics, and movements. Moreover, stadium infrastructure could utilize IoT devices and sensors to monitor spectator engagement, environmental conditions, and pitch quality. Cloud-based technology and data management systems could help effectively process, analyze, and store enormous amounts of data collected during a cricket match. Such developed analytics algorithms as artificial intelligence and machine learning could help extract significant insights from the data. Near-real-time big data could motivate coaches and athletes with comprehensive performance, facilitating enhanced player performance and data-driven decisions. For instance, batters could receive immediate feedback on bat speed, shot selection, and footwork while considering the collected data from equipment sensors. Such data could stem from corporate internal sources, personal thoughts and opinions, external sources, and new sources like sensor tags (Rainer et al., 2021). Also, Bowlers could have the ability to evaluate ...