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NFL · Week 15 · 2026 Upcoming Division game

Saints at Buccaneers

Sun, 20 Dec 2026 · 18:00 UTC
New Orleans Saints logo
New Orleans
Saints
2-5 · L5
@
Tampa Bay Buccaneers logo
Tampa Bay
Buccaneers
2-5 · W2
Tampa Bay Buccaneers to win 62% win probability · projected 20–24 · Solid

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.

NO 38%
TB 62%
Projected score
20–24
NO at TB
Projected margin
+3.9
home perspective
Projected total
44.5
combined points
Confidence
Solid
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
Raymond James Stadium
Roof
Outdoors
Surface
Grass
Rest · NO
7 days
Rest · TB
7 days

Recent Form

Last five completed games this season, most recent first.

New Orleans Saints

L vs PIT 10–16
W @ NYG 34–27
L vs MIN 13–23
L vs ATL 24–45
L vs LV 27–35

Tampa Bay Buccaneers

W @ CAR 43–13
L vs PIT 19–26
W @ DAL 24–16
L vs GB 14–17
L vs MIN 16–23

Season Scoring

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

NO · scored
23.1
per game · 7 played
NO · allowed
27.7
per game
TB · scored
23.1
per game · 7 played
TB · allowed
21.6
per game

How The Model Sees It

Our rating has Tampa Bay Buccaneers as the stronger side by 62 rating points, which on its own is worth about 2.5 points on the scoreboard (NO 1,406, TB 1,468).

Home field adds 1.4 points to TB — 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.

That lands on a projected margin of +3.9, and running that through the historical spread of actual results against projections gives Tampa Bay Buccaneers at 62%.

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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