The purpose of this research is to develop models that could help team owners to build talented teams with minimum possible spending. The models are developed using Python and R tools. Models such as Multiple Linear Regression (Backward Elimination Rule), K-Nearest Neighbour, Support Vector Machine, Linear Regression and Neural Networks have been used to predict the performances of the players. The models would provide the probability measure of the selection of players which can be used by the team owners during bidding. It would also help decision makers during auction by calculating the value of each player and help set the salaries for the players.