Robot teams are an effective tool for communicating data in unstructured environments (e.g., data collection). Since robot teams can rearrange themselves, they can ferry data through physical motion rather than only wireless transmissions, potentially increasing network throughput. We construct a Robot Network Graph that represents throughput due to both physical motion and wireless communication, and use the Robot Network Graph to find a polynomial time upper bound on network throughput. We combine the upper bound with an optimization formulation for maximizing network throughput, producing a bounded-optimal solution. We analyze the performance of our bounded-optimal solution and show our bound is at least 3x tighter than a bound derived from the maximum flow across a graph for large ( \(>20\) robots) teams in our tested scenarios.