Outcome

A machine learning model that can accurately predict pitch behaviors in cricket using computer vision.

A better understanding of how pitch behavior is influenced by various factors, such as weather, soil type, and grass cover.

Umpires could use pitch behavior data to make more informed decisions about play, such as when to declare the pitch unfit for play or when to reduce the number of overs in a match.

Coaches could use pitch behavior data to develop strategies for their teams and to help their players prepare for different pitch conditions.

Players could use pitch behavior data to adjust their batting and bowling techniques accordingly.

Spectators could use pitch behavior data to better understand the game and to make more informed predictions about the outcome of matches.