← All games

Week 4 · Thu, Oct 1, 8:15 PM

PITatCLE
Low confidencethis band has been right 57.3% of the time
PITCLE

Model picks

PIT

Model spread

PIT -4.6

Market spread

-2.5

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

PIT24
CLE3

EPA allowed

PIT34
CLE80

Passing efficiency· weight 8.0

Offense

PIT19
CLE1

EPA allowed

PIT41
CLE97

Drive-sustaining rate· weight 6.6

Offense

PIT23
CLE1

EPA allowed

PIT56
CLE54

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

PIT54
CLE3

defensive rate

PIT85
CLE88

Rushing efficiency

Offense

PIT64
CLE59

EPA allowed

PIT35
CLE9

Completion % Over Expected

Offense

PIT27
CLE11

EPA allowed

PIT48
CLE60

Giveaways per play

Offense

PIT84
CLE18

defensive rate

PIT70
CLE11

20+ yard completions per attempt

Offense

PIT13
CLE16

EPA allowed

PIT17
CLE76

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

  • RestCLE

    CLE on a short week

    Only 4 days of rest.

  • RestPIT

    PIT on a short week

    Only 4 days of rest.

  • SchemeCLE

    CLE faces a 4-3 front

    PIT's roster profiles as a 4-3 base defense.

    Base front is inferred from roster composition (agrees with snap data at Spearman 0.50). Most teams play nickel by default, so this is a weak descriptor: measured defensive efficiency carries far more weight in the model.

  • SchemePIT

    PIT faces a 4-3 front

    CLE's roster profiles as a 4-3 base defense.

    Base front is inferred from roster composition (agrees with snap data at Spearman 0.50). Most teams play nickel by default, so this is a weak descriptor: measured defensive efficiency carries far more weight in the model.

  • Recent formCLE

    CLE -4.2 pts/game trend

    Over the last 10 games (exponentially weighted), CLE has been being outscored by opponents by 4.2 points per game.

  • Recent formPIT

    PIT -3.9 pts/game trend

    Over the last 10 games (exponentially weighted), PIT has been being outscored by opponents by 3.9 points per game.

  • VenueCLE

    CLE 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.