AI-generated feedback is often judged by quality ratings or preference rankings but rarely both. Comparing a multi-agent system, a single-agent system, and human feedback on student writing, we show that the two evaluation approaches can support different reported conclusions even when their underlying effects are nearly identical. These differences have consequences for how AI-generated feedback should be evaluated.