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Week 7 · Sun, Oct 25, 8:20 PM

KCatSEA
High confidencethis band has been right 74.1% of the time
KCSEA

Model picks

SEA

Model spread

SEA -5.0

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

KC7
SEA76

EPA allowed

KC82
SEA98

Passing efficiency· weight 8.0

Offense

KC5
SEA75

EPA allowed

KC76
SEA98

Drive-sustaining rate· weight 6.6

Offense

KC8
SEA79

EPA allowed

KC94
SEA82

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

KC5
SEA42

defensive rate

KC58
SEA67

Rushing efficiency

Offense

KC60
SEA64

EPA allowed

KC77
SEA64

Completion % Over Expected

Offense

KC10
SEA73

EPA allowed

KC73
SEA66

Giveaways per play

Offense

KC77
SEA95

defensive rate

KC12
SEA87

20+ yard completions per attempt

Offense

KC18
SEA26

EPA allowed

KC65
SEA47

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 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.

  • Recent formKC

    KC -3.2 pts/game trend

    Over the last 10 games (exponentially weighted), KC has been being outscored by opponents by 3.2 points per game.

  • VenueSEA

    SEA 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.

  • RestSEA

    SEA holds a rest advantage

    3 more days of recovery than the opponent.

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.