Methods were initiated by Mark Kac and Richard Feynman to evaluate random functionals of the form $\int^t_0V(X_s)ds$ for a nonnegative $V$ and a Markov process $X_t$. Their results evolved into the well known Feynman Kac formula. Functionals of this type appear in both theoretical and applied applications in partial differential equations, quantum physics, mathematical finance, control theory, etc. Here the time average of one such functional associated with the Feynman Kac formula is studied. In real time applications where only the path is observed, the time average often is a better predictor than the functional at its last observation point.. It represents quantities, e.g., the long term average cost or wealth, the long term average velocity. As a statistic, it is of interest to determine if it has an asymptotic limit and to determine that limit. An expression is derived for its asymptotic time average.