In this paper, aiming to solve the TSLCP of large-scale, we propose two kinds of stochastic methods, namely the stochastic approximation  method based on the projection (SAP) and the dynamic sampling stochastic approximation  method based on the projection (DS-SAP), both of which offer inexpensive computational costs in solving subproblems, especially compared with PHA. In particular, the linear complementarity subproblems are solved inexactly during each iteration, and the convergence analysis of both SAP and DS-SAP with inexactness criterion is rigorously presented. Moreover, numerical implementations and practical applications demonstrate the efficiency of our proposed methods.