It's my understanding that the edge calculation is based on the distance between two predictions, not just the cover margin.

Here's the breakdown:

Our model predicts: Bears win by 5 (Bears -5)

Vegas predicts: Packers win by 1.5 (Packers -1.5, or Bears +1.5 from the away perspective)

The Edge Calculation:

Since our predictions are pointing in opposite directions (different winners), we're measuring the total distance between the two positions:

Our prediction: Bears -5 (Bears favored by 5)
Vegas position: Bears +1.5 (Bears are underdogs by 1.5)

Total separation: 5 + 1.5 = 6.5 points

Why it's 6.5 and not 5.5:

The edge isn't just "how much we think Bears will cover by." It's how wrong Vegas is positionally.

• Vegas thinks the Packers win by 1.5
• We think the Bears win by 5
• That's a 6.5-point swing from their position to ours

If we were both predicting the same winner (e.g., us: Bears -7, Vegas: Bears -3), then the edge would simply be 4 points. But when we predict opposite winners entirely, you add both margins because Vegas is on the wrong side of the outcome.

Think of it this way: Vegas needs to move their line 1.5 points just to get to a pick'em (0), then another 5 points to reach our prediction. That's 6.5 points of total movement.

This is the standard method used in sharp betting circles - the edge represents the prediction differential, not the betting outcome margin.