Green Bay Packers vs Minnesota Vikings — Win Probability

Model underestimated Minnesota's dominance in Week 1 win over Green Bay

The model projected a one-score game. Minnesota won by 17 points, and that gap tells the story of how thoroughly the Vikings outplayed the Packers in Week 1.

Before kickoff, the model's simulation gave Minnesota a 55% win probability and projected a final score of 24.1 to 22.5—a margin of just 1.6 points. The market agreed it was close: the published spread had Minnesota favored by 1.5 points. Both suggested a competitive division matchup.

Instead, Minnesota dominated. The Vikings scored 39 points to Green Bay's 22, winning by 17 points and covering the model's expectation by 15.4 points. That's not a near miss. It's a substantial underestimation of Minnesota's performance.

The model correctly identified Minnesota as the probable winner—the Vikings were favored, and they won—but it severely misjudged the margin. A one-score projection versus a 17-point actual result is the kind of miss that signals either Minnesota played significantly better than simulated, Green Bay played significantly worse, or both. The model's 55% win probability meant it gave Minnesota less than a 1-in-2 chance to win outright; they not only won but dominated.

For a brand built on factual honesty, this is instructive: the model and the market were largely aligned pregame, and both were wrong in the same direction. Minnesota's 39 points exceeded the model's projected total for both teams combined (46.6). Whether this was an outlier performance, a failure to account for a personnel or scheme change, or simply Minnesota playing at a level the simulation didn't capture remains unanswered by the numbers alone. What's clear is that the projection missed significantly on the game's competitive balance.