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NFL · Week 14 · 2026 Upcoming

Giants at Seahawks

Sun, 13 Dec 2026 · 21:25 UTC
New York Giants logo
New York
Giants
4-2-1 · W4
@
Seattle Seahawks logo
Seattle
Seahawks
4-3 · W4
Seattle Seahawks to win 78% win probability · projected 18–28 · Strong

Win Probabilities

From the engine's power ratings, adjusted for home field and rest, then mapped through the margin distribution. Not a blend of the market — this is our own number.

NYG 22%
SEA 78%
Projected score
18–28
NYG at SEA
Projected margin
+10.0
home perspective
Projected total
45.6
combined points
Confidence
Strong
published before kickoff

Matchup Facts

Venue and rest come from the schedule feed and feed directly into the model; surface and weather are context we show but don't yet model.

Venue
Lumen Field
Roof
Outdoors
Surface
Fieldturf
Rest · NYG
7 days
Rest · SEA
6 days

Recent Form

Last five completed games this season, most recent first.

New York Giants

W @ HOU 27–21
L vs NO 27–34
T @ WAS 27–27
W vs ARI 36–24
W vs TEN 12–7

Seattle Seahawks

W vs KC 20–3
L @ DEN 14–17
L vs SF 29–32
W vs LAC 30–23
L @ WAS 31–33

Season Scoring

Points per game either side of the ball, 2026 season to date.

NYG · scored
23.3
per game · 7 played
NYG · allowed
23.0
per game
SEA · scored
24.0
per game · 7 played
SEA · allowed
17.9
per game

How The Model Sees It

Our rating has Seattle Seahawks as the stronger side by 218 rating points, which on its own is worth about 8.7 points on the scoreboard (NYG 1,465, SEA 1,683).

Home field adds 1.4 points to SEA — a measured figure from our backtest, not the traditional three, because home advantage in the modern NFL is considerably smaller than it used to be. Rest shifts it a further -0.1 points (NYG 7 days, SEA 6).

That lands on a projected margin of +10.0, and running that through the historical spread of actual results against projections gives Seattle Seahawks at 78%.

No betting line has been posted for this game yet — books typically price about three weeks ahead. Until one appears, this page shows the engine's number with nothing to compare it against, which is exactly the situation the model is most useful in.

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