A Comprehensive Analysis of Predicting Individual Cricket Players' Performance: A Survey (original) (raw)

The growth of automated machine learning by guessing and forecasting is significant in cricket. Player selection is one of the essential jobs in any sport, and cricket is no exception. The players' performance is influenced by a variety of variables such as the opposing team, the venue, his present form, and so on. The team management, coach, and captain choose eleven players from 15 to 20 players from a roster. Because cricket is so highly respected and popular, no one can predict who will win until the game's last over-the-top ball. And many variables, including individual performance, team performance, and environmental conditions, must be considered while developing a game strategy. As a result, we decided to create a machine learning model to forecast the outcome of its games; in this Survey, a thorough study of predicting player performance and score prediction is provided. According to the study's findings, the player's handedness (batsman) and the team's rank have a substantial impact on player performance.