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Week 3 · Sun, Sep 27, 4:05 PM

MINatTB
Medium confidencethis band has been right 63.4% of the time
MINTB

Model picks

TB

Model spread

TB -1.3

Market spread

1.5

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

MIN11
TB52

EPA allowed

MIN99
TB20

Passing efficiency· weight 8.0

Offense

MIN4
TB45

EPA allowed

MIN100
TB16

Drive-sustaining rate· weight 6.6

Offense

MIN38
TB48

EPA allowed

MIN88
TB27

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

MIN1
TB37

defensive rate

MIN100
TB23

Rushing efficiency

Offense

MIN71
TB77

EPA allowed

MIN84
TB80

Completion % Over Expected

Offense

MIN22
TB43

EPA allowed

MIN100
TB10

Giveaways per play

Offense

MIN31
TB64

defensive rate

MIN69
TB56

20+ yard completions per attempt

Offense

MIN13
TB68

EPA allowed

MIN99
TB41

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 formTB

    TB -2.1 pts/game trend

    Over the last 10 games (exponentially weighted), TB has been being outscored by opponents by 2.1 points per game.

  • Recent formMIN

    MIN +4.5 pts/game trend

    Over the last 10 games (exponentially weighted), MIN has been outscoring opponents by 4.5 points per game.

  • VenueTB

    TB 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.