This paper proposes a more comprehensive look at the ideas of KS and Area Under the Curve (AUC) of a cumulative gains chart to develop a model quality statistic which can be used agnostically to evaluate the quality of a wide range of models in a standardized fashion. It can be either used holistically on the entire range of the model or at a given decision threshold of the model. Further it can be extended into the model learning process.