There are two classes of mistakes one can make when using models – one can either be using the wrong model, or using the correct model but assigning an erroneous solution. It is important to differentiate between the two types of mistakes, because doing so would allow you to better modularize reality, detect the places in which that reality repeats, and apply the ideas one has.
When using the wrong model, the elementary objects in reality do not actually have the properties required for the model to be relevant. When solving a given model wrongly, the space of possibilities and consequences represented by the model are not searched thoroughly enough to find the best solution.
For a given level of simplicity, models that apply to many different situations are more profitable to solve. For models that apply to the same number of situations, I prefer to solve the simpler models first, with the strength of the preference proportional to my model-specific intelligence. Therefore, if I feel like my comparative (not competitive?) advantage is in intelligence, I will be constantly trying to search for models of wide applicability and high complexity. I will value the ability to generalize primitives to identify common games.