In fantasy cricket, which is based on actual cricket matches, points are awarded based on how well players perform in exact matches. This study was written to fill the literature gap by introducing an iterative methodology for automating team creation in the fantasy cricket framework. In order to create teams within predetermined parameters, the model combines a credit and point system. Our approach can efficiently generate all feasible or optimal team configurations by automating the process of team generation and allowing circumstances and user-selected criteria to be used. We put these artificial intelligence-generated teams to the test in a real-time setting against user-created ones. In a real-time setting, we tested these teams produced by the machine versus teams that were created by the user. In contrast to manually constructed teams, our results show that the teams assembled by the algorithm not only follow the given constraints but also exhibit better performance prediction accuracy.