
Away
Tennessee Titans
0-2

Home
New York Giants
1-0
Model Win Probability
Tennessee Titans · Away
30%
separation40%
New York Giants · Home
70%
- Elo component
- 29% TEN
- Efficiency component
- 27% TEN
- 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
0–100 league percentile across all 32 teams. Defensive ratings are inverted so a higher number always means a better unit.
Blended Team Metrics
| TEN | Metric | NYG |
|---|---|---|
| -0.137 | EPA / Play | 0.077 |
| 38.7% | Success Rate | 44.8% |
| -0.149 | Dropback EPA | 0.156 |
| -0.111 | Rush EPA | -0.027 |
| 9.8% | Explosive Play Rate | 12.3% |
| 34.1% | 3rd Down Conversion | 47.2% |
| 18.5% | Red Zone TD Rate | 17.4% |
| 0.105 | Def. EPA / Play Allowed | 0.115 |
| 6.1% | Pressure Rate | 5.2% |
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
- fieldturf
- Away rest
- 7 days
- Home rest
- 6 days
- Site
- New York Giants home game
Player Impact
Cam Ward
QB2026 Weeks 1–2
- CMP/ATT
- 32/52
- Pass yds
- 323
- Pass TD
- 1
- INT
- 0
- Y/A
- 6.2
- Sacks
- 5
Tony Pollard
RB2026 Weeks 1–2
- Carries
- 21
- Rush yds
- 99
- YPC
- 4.7
- Rush TD
- 0
- Targets
- 3
- Rec
- 2
- Rush share
- 48.8%
Tyjae Spears
RB2026 Weeks 1–2
- Carries
- 10
- Rush yds
- 53
- YPC
- 5.3
- Rush TD
- 0
- Targets
- 6
- Rec
- 4
- Rush share
- 23.3%
Carnell Tate
WR2026 Weeks 1–2
- Targets
- 11
- Rec
- 7
- Rec yds
- 65
- YPR
- 9.3
- Rec TD
- 0
- Target share
- 24.4%
Gunnar Helm
TE2026 Weeks 1–2
- Targets
- 7
- Rec
- 6
- Rec yds
- 41
- YPR
- 6.8
- Rec TD
- 0
- Target share
- 15.6%
Away · Tennessee Titans
Cam Ward
QB2026 Weeks 1–2
- CMP/ATT
- 32/52
- Pass yds
- 323
- Pass TD
- 1
- INT
- 0
- Y/A
- 6.2
- Sacks
- 5
Tony Pollard
RB2026 Weeks 1–2
- Carries
- 21
- Rush yds
- 99
- YPC
- 4.7
- Rush TD
- 0
- Targets
- 3
- Rec
- 2
- Rush share
- 48.8%
Tyjae Spears
RB2026 Weeks 1–2
- Carries
- 10
- Rush yds
- 53
- YPC
- 5.3
- Rush TD
- 0
- Targets
- 6
- Rec
- 4
- Rush share
- 23.3%
Carnell Tate
WR2026 Weeks 1–2
- Targets
- 11
- Rec
- 7
- Rec yds
- 65
- YPR
- 9.3
- Rec TD
- 0
- Target share
- 24.4%
Gunnar Helm
TE2026 Weeks 1–2
- Targets
- 7
- Rec
- 6
- Rec yds
- 41
- YPR
- 6.8
- Rec TD
- 0
- Target share
- 15.6%
Home · New York Giants
Jaxson Dart
QB2026 Weeks 1–2
- CMP/ATT
- 26/34
- Pass yds
- 250
- Pass TD
- 3
- INT
- 0
- Y/A
- 7.4
- Sacks
- 2
Cam Skattebo
RB2026 Weeks 1–2
- Carries
- 30
- Rush yds
- 117
- YPC
- 3.9
- Rush TD
- 1
- Targets
- 4
- Rec
- 4
- Rush share
- 51.7%
Devin Singletary
RB2026 Weeks 1–2
- Carries
- 9
- Rush yds
- 25
- YPC
- 2.8
- Rush TD
- 0
- Targets
- 5
- Rec
- 4
- Rush share
- 15.5%
Isaiah Likely
TE2026 Weeks 1–2
- Targets
- 18
- Rec
- 13
- Rec yds
- 111
- YPR
- 8.5
- Rec TD
- 2
- Target share
- 29.5%
Malik Nabers
WR2026 Weeks 1–2
- Targets
- 13
- Rec
- 7
- Rec yds
- 70
- YPR
- 10
- Rec TD
- 0
- Target share
- 21.3%
Injuries & Availability
Away · Tennessee Titans
Cordale FlottCB
QUESTIONABLEQuadricep · Did Not Participate In Practice
James WilliamsLB
QUESTIONABLEElbow · Limited Participation in Practice
Cedric GrayLB
QUESTIONABLEConcussion · Full Participation in Practice
Home · New York Giants
Jaxson DartQB
QUESTIONABLELeft knee injury during the Week 2 Monday game
Week 3 availability was unresolved at the data cutoff.
Micah McFaddenLB
QUESTIONABLENeck · Limited Participation in Practice
Deonte BanksCB
QUESTIONABLECalf · Did Not Participate In Practice
Scoring by Quarter
Sample · 2 gamesAway · Tennessee Titans
Home · New York Giants
Small sample — treat quarter splits as descriptive context, not a trend.
Latest News
- Dart's injury hinders Giants as Stafford, Rams pick up MNF win
ESPN NFL · just now · LA / NYG
- 😈 Rams poking fun at Giants after win tops Week 2 trolls
ESPN NFL · just now · LA / NYG / PHI
- Sources: Giants QB Dart believed to have sprained MCL; more tests to come
ESPN NFL · just now · NYG
- Donald's return fires up Rams, who bounce back with rout of Giants
ESPN NFL · just now · LA / NYG
- Time will tell if Jaxson Dart’s injury sinks Giants’ season, or they survive
Yahoo Sports NFL · 1h ago · LA / NYG
Analytical Angles
Passing profile · TEN
passingTennessee Titans is at the 6th league percentile in blended passing efficiency entering Week 3.
Defense profile · TEN
efficiencyTennessee Titans is at the 12th league percentile in blended defensive efficiency; higher values reflect fewer EPA allowed.
Passing profile · NYG
passingNew York Giants is at the 72th league percentile in blended passing efficiency entering Week 3.
Defense profile · NYG
efficiencyNew York Giants is at the 9th 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 Tennessee Titans 30% and New York Giants 70%.
- Elo puts Tennessee Titans at 28.9% and the efficiency model at 27.1%.
- Both components favour New York Giants, a 1.8 point difference between them.
What Could Flip It
- A 1.8 point split between rating and efficiency views leaves room for the Tennessee Titans side.
- The Giants' Week 3 quarterback status is unresolved (Jaxson Dart).
Model Analysis
pt-nfl-ensemble-v0.3 rates Tennessee Titans (0-2) at 30% to win at New York Giants (1-0). Elo puts Tennessee Titans at 28.9% and the efficiency model at 27.1%; the blend lands at 30%. Both components agree on New York Giants. The Giants' Week 3 quarterback status is unresolved (Jaxson Dart).
Forecast
New York Giants projected to win, 70% 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.