In this paper we have compared and evaluated two different representations used in search based procedural content generation (PCG). The comparison was based on the differences in performance, quality of the generated content and the complexity of the final artifacts. This was accomplished by creating two artifacts, each of which used one of the representations in combination with a genetic algorithm. This was followed up with individual testing sessions in which 21 test subjects participated. The evaluated results were then presented in a manner of relevance for both search based PCG as a whole, and for further exploration within the area of representations used in this field.