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Week 15 · Sat, Dec 19, 5:00 PM

SEAatPHI
Low confidencethis band has been right 57.3% of the time
SEAPHI

Model picks

PHI

Model spread

PHI -3.2

Market spread

n/a

the market forecasts these games better than this model

How the teams compare

heaviest model weight first · 0–100, oriented so higher is always better

Expected Points Added per play· weight 11.8

Offense

SEA76
PHI53

EPA allowed

SEA98
PHI84

Passing efficiency· weight 8.0

Offense

SEA75
PHI51

EPA allowed

SEA98
PHI87

Drive-sustaining rate· weight 6.6

Offense

SEA79
PHI40

EPA allowed

SEA82
PHI71

Position-weighted availability score· weight 6.6

No data yet for this metric. Nothing has been published for these teams at this point in the week. It will fill in once it exists.

Sacks taken per dropback· weight 5.7

Offense

SEA42
PHI75

defensive rate

SEA67
PHI71

Rushing efficiency

Offense

SEA64
PHI75

EPA allowed

SEA64
PHI49

Completion % Over Expected

Offense

SEA73
PHI52

EPA allowed

SEA66
PHI90

Giveaways per play

Offense

SEA95
PHI90

defensive rate

SEA87
PHI64

20+ yard completions per attempt

Offense

SEA26
PHI12

EPA allowed

SEA47
PHI56

This chart is not the model. It shows the inputs that read well as a side-by-side. 7 of the model’s heaviest-weighted inputs have no head-to-head form and are not drawn here: point differential, overall matchup, team win rate, pass matchup among them. The full list of all 55 is on the methodology tab.

Around the game

  • Recent formPHI

    PHI +2.3 pts/game trend

    Over the last 10 games (exponentially weighted), PHI has been outscoring opponents by 2.3 points per game.

  • Recent formSEA

    SEA +13.9 pts/game trend

    Over the last 10 games (exponentially weighted), SEA has been outscoring opponents by 13.9 points per game.

  • VenuePHI

    PHI at home

    Home teams have won 54.7% of games in the training window; the model prices this in rather than applying a fixed bonus.

  • Weather

    High wind expected

    22 mph winds suppress deep passing and kicking.

Every figure here comes from Calibrated Logistic Regression (core + market features), validated walk-forward by season (train on all prior seasons, test on the next). For how the model is built, what the metrics mean and how it has actually performed, read the methodology.