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Week 18 · Sun, Jan 10, 1:00 PM

LVatKC
Coin flip, no callthis band has been right 52.8% of the time
LVKC

Model leans

KC

this band is 49.8% accurate, so treat it as no call

Model spread

KC -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

LV0
KC7

EPA allowed

LV67
KC82

Passing efficiency· weight 8.0

Offense

LV2
KC5

EPA allowed

LV43
KC76

Drive-sustaining rate· weight 6.6

Offense

LV1
KC8

EPA allowed

LV71
KC94

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

LV2
KC5

defensive rate

LV85
KC58

Rushing efficiency

Offense

LV1
KC60

EPA allowed

LV63
KC77

Completion % Over Expected

Offense

LV18
KC10

EPA allowed

LV34
KC73

Giveaways per play

Offense

LV43
KC77

defensive rate

LV9
KC12

20+ yard completions per attempt

Offense

LV5
KC18

EPA allowed

LV88
KC65

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 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.

  • Recent formLV

    LV -11.4 pts/game trend

    Over the last 10 games (exponentially weighted), LV has been being outscored by opponents by 11.4 points per game.

  • VenueKC

    KC 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.

  • Context

    Divisional matchup

    Familiar opponents; historically tighter margins.

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.