An agent attempting to model market conditions may benefit from considering how various combinations of competitor strategies would impact these conditions. We give an illustration using a prediction task faced by our agent for the Supply Chain Management scenerio of the Trading Agent Competition(TAC SCM). We present the learning approach taken, evaluate its effectiveness, and then explore methods of improving predictions through combining multiple sources of data reflecting various combinations of competitor behaviors.