Across 64 English authorities and six 2026 scenarios, even the strongest scenario shock was only 13% of the median uncertainty band. In plain English: the model’s assumptions moved the result less than historical forecast error did. The most aggressive challenger surge I could parameterise sits inside the noise the model has produced in past elections. That is not a defect. It is the result. I built this scenario model expecting clean separation between assumptions. I expected S3, the challenger surge, to dominate. I expected rankings I could defend. What I got was an envelope where the strongest shock sits inside calibrated uncertainty, and where rankings dissolve when intervals are plotted on top of them. This is the second instalment of a project on English local electoral data. Part 1 corrected a categorical-normalisation bug that reversed the original headline.…