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Green Bay Packers at Detroit Lions

Sunday Late · Sun, Oct 25, 4:25 PM ETGB @ DET
Green Bay Packers

Away

Green Bay Packers

4-2

Detroit Lions

Home

Detroit Lions

3-2

Model Win Probability

Green Bay Packers · Away

41%

Model
separation18%

Detroit Lions · Home

59%

Signal: Lean· components agree · 100% feature coverage
Elo component
42% GB
Efficiency component
37% GB
Feature coverage
100%
Data cutoff
2026-10-20T20:24:22.518Z
Model
pt-nfl-ensemble-v0.3

Signal strength describes model agreement and data quality, not certainty or wagering value.

Team Efficiency Comparison

77
97
Offense
87
94
Passing
6
61
Rushing
42
16
Defense
48
90
Pass Rush
29
65
Situational

0–100 league percentile across all 32 teams. Defensive ratings are inverted so a higher number always means a better unit.

Blended Team Metrics

GBMetricDET
0.071EPA / Play0.113
44.4%Success Rate46.7%
0.215Dropback EPA0.234
-0.191Rush EPA-0.073
13.4%Explosive Play Rate14.1%
35.9%3rd Down Conversion38.8%
54.2%Red Zone TD Rate82.0%
0.009Def. EPA / Play Allowed0.077

Prior-season form is blended with current-season play and its weight decays as the current sample grows. Metrics without enough data are shown as “—”, never as zero.

Game Context

Venue
Ford Field
Kickoff
Sun, Oct 25, 4:25 PM ET
Roof
dome
Surface
fieldturf
Away rest
7 days
Home rest
14 days
Site
Detroit Lions home game

Player Impact

Jordan Love

QB

2026 Weeks 1–6; 6 games

CMP/ATT
135/226
Pass yds
1684
Pass TD
11
INT
4
Y/A
7.5
Sacks
13

MarShawn Lloyd

RB

2026 Weeks 1–6; 6 games

Carries
48
Rush yds
122
YPC
2.5
Rush TD
2
Targets
14
Rec
10

Kaleb Johnson

RB

2026 Weeks 1–6; 6 games

Carries
28
Rush yds
104
YPC
3.7
Rush TD
0
Targets
3
Rec
1

Matthew Golden

WR

2026 Weeks 1–6; 6 games

Targets
57
Rec
30
Rec yds
501
YPR
16.7
Rec TD
3

Christian Watson

WR

2026 Weeks 1–6; 6 games

Targets
48
Rec
29
Rec yds
538
YPR
18.6
Rec TD
6

Injuries & Availability

Away · Green Bay Packers

Micah ParsonsEDGE

PUP

Knee; coach said he would not practice this week; remains on PUP.

Checked Tue, Oct 20, 2026; game designation pending unless IR/PUP.

Scoring by Quarter

Sample · 6 games

Away · Green Bay Packers

Q1
30
Q2
44
Q3
22
Q4
28

Home · Detroit Lions

Q1
10
Q2
57
Q3
45
Q4
45

Latest News

Analytical Angles

Passing profile · GB

passing

Green Bay Packers: 87/100 league percentile in blended 2025–26 passing EPA entering Week 7.

Passing profile · DET

passing

Detroit Lions: 94/100 league percentile in blended 2025–26 passing EPA entering Week 7.

Defensive profile · GB / DET

efficiency

Defense EPA percentiles: Green Bay Packers 42/100; Detroit Lions 16/100. Lower EPA allowed rates better.

Availability watch

availability

Availability checked Tuesday, October 20. 1 named item in game notes; final designations remain subject to change. The forecast applies no separate injury, trade or lineup adjustment.

Statistical context only. Picks Terminal publishes matchup analysis, not wagering advice.

Keys to the Game

  • Margin-aware Elo: Green Bay Packers 42.4%.
  • Rolling efficiency: Green Bay Packers 36.6%.
  • rushing: Detroit Lions 61/100, Green Bay Packers 6/100.
  • passRush: Detroit Lions 90/100, Green Bay Packers 48/100.

What Could Flip It

  • defense: Green Bay Packers 42/100 versus Detroit Lions 16/100.
  • Green Bay Packers have 6 completed 2026 games; Detroit Lions have 5. Prior-season form is blended into efficiency.
  • The model applies no explicit player-availability adjustment.

Model Analysis

Green Bay Packers at Detroit Lions: the v0.3 ensemble places Detroit Lions at 59%, using a 70% margin-aware Elo and 30% rolling-efficiency blend with saved strictly out-of-fold calibration. Both sides have 6 and 5 current-season games, respectively, with 2025 prior form. The model applies no explicit player-availability adjustment. This is a pregame statistical estimate, not a certainty or wagering recommendation.

Forecast

Model pick: Detroit Lions (59%). Signal: Lean; model agreement and data quality, not wagering value.

Sources & Methodology

Win probability: pt-nfl-ensemble-v0.3 — a deterministic ensemble of a margin-aware Elo component and a regularized efficiency component built from pregame team differentials (EPA per play, dropback and rush EPA, success rate, explosive rate, sack performance, home field and rest). The blended probability is calibrated on training seasons only and validated by walk-forward backtest against completed results. All inputs come from public play-by-play and schedule data. No external market data of any kind is used anywhere on this page.