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Cincinnati Bengals at Pittsburgh Steelers

Sunday Early · Sun, Sep 27, 1:00 PM ETCIN @ PIT
Cincinnati Bengals

Away

Cincinnati Bengals

2-0

Pittsburgh Steelers

Home

Pittsburgh Steelers

1-1

Model Win Probability

Cincinnati Bengals · Away

45%

Model
separation10%

Pittsburgh Steelers · Home

55%

Signal: Lean· components agree · 100% feature coverage
Elo component
44% CIN
Efficiency component
46% CIN
Feature coverage
100%
Data cutoff
2026-09-21T03:30:00Z
Model
pt-nfl-ensemble-v0.3

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

Team Efficiency Comparison

47
31
Offense
25
22
Passing
88
72
Rushing
25
59
Defense
47
88
Pass Rush
94
28
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

CINMetricPIT
-0.008EPA / Play-0.040
44.9%Success Rate42.5%
-0.011Dropback EPA-0.027
-0.013Rush EPA-0.046
12.3%Explosive Play Rate11.1%
45.0%3rd Down Conversion40.3%
23.0%Red Zone TD Rate16.1%
0.061Def. EPA / Play Allowed-0.020
5.9%Pressure Rate7.7%

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

Kickoff
Sun, Sep 27, 1:00 PM ET
Roof
outdoors
Surface
grass
Away rest
7 days
Home rest
7 days
Site
Pittsburgh Steelers home game

Player Impact

Joe Burrow

QB

2026 Weeks 1–2

CMP/ATT
45/66
Pass yds
461
Pass TD
3
INT
1
Y/A
7
Sacks
6

Chase Brown

RB

2026 Weeks 1–2

Carries
36
Rush yds
136
YPC
3.8
Rush TD
1
Targets
11
Rec
8
Rush share
72%

Samaje Perine

RB

2026 Weeks 1–2

Carries
7
Rush yds
26
YPC
3.7
Rush TD
0
Targets
4
Rec
4
Rush share
14%

Tee Higgins

WR

2026 Weeks 1–2

Targets
16
Rec
8
Rec yds
154
YPR
19.2
Rec TD
0
Target share
24.6%

Ja'Marr Chase

WR

2026 Weeks 1–2

Targets
13
Rec
9
Rec yds
87
YPR
9.7
Rec TD
2
Target share
20%

Injuries & Availability

Away · Cincinnati Bengals

B.J. HillDL

QUESTIONABLE

Achilles · Did Not Participate In Practice

Joe BurrowQB

QUESTIONABLE

Back · Full Participation in Practice

Home · Pittsburgh Steelers

Joey Porter Jr.CB

OUT

Back · Limited Participation in Practice

Michael PittmanWR

QUESTIONABLE

Foot · Did Not Participate In Practice

Troy FautanuOL

QUESTIONABLE

Ankle · Full Participation in Practice

Scoring by Quarter

Sample · 2 games

Away · Cincinnati Bengals

Q1
14
Q2
17
Q3
13
Q4
9

Home · Pittsburgh Steelers

Q1
3
Q2
13
Q3
0
Q4
7

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

Latest News

Analytical Angles

Passing profile · CIN

passing

Cincinnati Bengals is at the 25th league percentile in blended passing efficiency entering Week 3.

Defense profile · CIN

efficiency

Cincinnati Bengals is at the 25th league percentile in blended defensive efficiency; higher values reflect fewer EPA allowed.

Passing profile · PIT

passing

Pittsburgh Steelers is at the 22th league percentile in blended passing efficiency entering Week 3.

Defense profile · PIT

efficiency

Pittsburgh Steelers is at the 59th league percentile in blended defensive efficiency; higher values reflect fewer EPA allowed.

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

Keys to the Game

  • Blended model gives Cincinnati Bengals 45% and Pittsburgh Steelers 55%.
  • Elo puts Cincinnati Bengals at 44.4% and the efficiency model at 45.8%.
  • Both components favour Pittsburgh Steelers, a 1.4 point difference between them.

What Could Flip It

  • A 1.4 point split between rating and efficiency views leaves room for the Cincinnati Bengals side.
  • Ratings carry into Week 3 from a two-game sample, so single-game variance still dominates.

Model Analysis

pt-nfl-ensemble-v0.3 rates Cincinnati Bengals (2-0) at 45% to win at Pittsburgh Steelers (1-1). Elo puts Cincinnati Bengals at 44.4% and the efficiency model at 45.8%; the blend lands at 45%. Both components agree on Pittsburgh Steelers.

Forecast

Pittsburgh Steelers projected to win, 55% of the time in the model.

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.