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Detroit Lions at Carolina Panthers

Sunday Night · Sun, Oct 4, 8:20 PM ETDET @ CAR
Detroit Lions

Away

Detroit Lions

2-1

Carolina Panthers

Home

Carolina Panthers

1-2

Model Win Probability

Detroit Lions · Away

63%

Model
separation26%

Carolina Panthers · Home

37%

Signal: Lean· components agree · 100% feature coverage
Elo component
70% DET
Efficiency component
58% DET
Feature coverage
100%
Data cutoff
2026-09-29T03:18:28.737160Z
Model
pt-nfl-ensemble-v0.3

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

Team Efficiency Comparison

87
39
Offense
87
42
Passing
48
29
Rushing
26
32
Defense
65
0
Pass Rush
66
42
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

DETMetricCAR
0.092EPA / Play-0.022
46.8%Success Rate42.8%
0.212Dropback EPA0.045
-0.088Rush EPA-0.130
13.8%Explosive Play Rate11.8%
40.7%3rd Down Conversion38.3%
69.7%Red Zone TD Rate61.0%
0.064Def. EPA / Play Allowed0.040

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
Bank of America Stadium
Kickoff
Sun, Oct 4, 8:20 PM ET
Roof
outdoors
Surface
grass
Away rest
7 days
Home rest
7 days
Site
Carolina Panthers home game

Player Impact

Jared Goff

QB

2026 Weeks 1, 2, 3

CMP/ATT
77/109
Pass yds
802
Pass TD
8
INT
0
Y/A
7.4
Sacks
7

Jahmyr Gibbs

RB

2026 Weeks 1, 2, 3

Carries
65
Rush yds
307
YPC
4.7
Rush TD
4
Targets
21
Rec
18
Rush share
78.3%

Sione Vaki

RB

2026 Weeks 1, 2, 3

Carries
9
Rush yds
40
YPC
4.4
Rush TD
0
Targets
3
Rec
3
Rush share
10.8%

Amon-Ra St. Brown

WR

2026 Weeks 1, 2, 3

Targets
35
Rec
23
Rec yds
228
YPR
9.9
Rec TD
5
Target share
32.4%

Sam LaPorta

TE

2026 Weeks 1, 2, 3

Targets
19
Rec
14
Rec yds
144
YPR
10.3
Rec TD
1
Target share
17.6%

Scoring by Quarter

Sample · 3 games

Away · Detroit Lions

Q1
7
Q2
20
Q3
28
Q4
31

Home · Carolina Panthers

Q1
17
Q2
30
Q3
27
Q4
15

Small sample — treat quarter splits as descriptive context, not a trend.

Latest News

Analytical Angles

Passing profile · DET

passing

Detroit Lions ranks in the 87th league percentile in blended dropback EPA entering Week 4.

Defense profile · DET

efficiency

Detroit Lions ranks in the 26th league percentile in blended defensive EPA allowed; higher percentile means less EPA conceded.

Passing profile · CAR

passing

Carolina Panthers ranks in the 42th league percentile in blended dropback EPA entering Week 4.

Defense profile · CAR

efficiency

Carolina Panthers ranks in the 32th league percentile in blended defensive EPA allowed; higher percentile means less EPA conceded.

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

Keys to the Game

  • Margin-aware Elo favors Detroit Lions at 70.1%.
  • Rolling efficiency favors Detroit Lions at 57.7%.
  • The calibrated estimate is 63%; it is a probability, not a certainty.

What Could Flip It

  • The statistical sample includes 3 current-season games for Detroit Lions and 3 for Carolina Panthers; prior-season form is still blended in.
  • The components agree, but a single game still has substantial variance.
  • The first official Week 4 practice/game-status report was unavailable at this cutoff; documented quarterback news is listed separately and is not explicitly priced into this statistical model.

Model Analysis

Detroit Lions at Carolina Panthers: the v0.3 ensemble places Detroit Lions at 63% after a 70% margin-aware Elo and 30% rolling efficiency blend with strictly out-of-fold calibration. The statistical sample includes 3 current-season games for Detroit Lions and 3 for Carolina Panthers; prior-season form is still blended in. No odds, moneylines, spreads, public picks or market consensus are model inputs.

Forecast

Model pick: Detroit Lions (63%). Signal: Lean; model agreement and coverage, 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.