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Week 15 · Sun, Dec 20, 1:00 PM

ATLatWAS
Low confidencethis band has been right 57.3% of the time
ATLWAS

Model picks

WAS

Model spread

WAS -3.6

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

ATL46
WAS46

EPA allowed

ATL49
WAS3

Passing efficiency· weight 8.0

Offense

ATL48
WAS38

EPA allowed

ATL65
WAS11

Drive-sustaining rate· weight 6.6

Offense

ATL43
WAS64

EPA allowed

ATL61
WAS6

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

ATL75
WAS48

defensive rate

ATL94
WAS79

Rushing efficiency

Offense

ATL42
WAS81

EPA allowed

ATL23
WAS2

Completion % Over Expected

Offense

ATL19
WAS57

EPA allowed

ATL81
WAS51

Giveaways per play

Offense

ATL76
WAS40

defensive rate

ATL58
WAS3

20+ yard completions per attempt

Offense

ATL36
WAS50

EPA allowed

ATL25
WAS60

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 formWAS

    WAS -5.7 pts/game trend

    Over the last 10 games (exponentially weighted), WAS has been being outscored by opponents by 5.7 points per game.

  • Recent formATL

    ATL -1.1 pts/game trend

    Over the last 10 games (exponentially weighted), ATL has been being outscored by opponents by 1.1 points per game.

  • VenueWAS

    WAS 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.

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.