We explore the evaluation (ranking) of point forecasts by a “stochastic loss distance” (SLD) criterion, under which we prefer forecasts with loss distributions F(L(e)) “close” to the unit step function at 0. We show that, surprisingly, ranking by SLD corresponds to ranking by expected loss.