
Away
Arizona Cardinals
1-2

Home
New York Giants
2-1
Model Win Probability
Arizona Cardinals · Away
43%
separation14%
New York Giants · Home
57%
- Elo component
- 42% ARI
- Efficiency component
- 46% ARI
- 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
0–100 league percentile across all 32 teams. Defensive ratings are inverted so a higher number always means a better unit.
Blended Team Metrics
| ARI | Metric | NYG |
|---|---|---|
| -0.008 | EPA / Play | 0.015 |
| 43.4% | Success Rate | 42.8% |
| 0.064 | Dropback EPA | 0.073 |
| -0.151 | Rush EPA | -0.061 |
| 10.0% | Explosive Play Rate | 11.4% |
| 42.8% | 3rd Down Conversion | 42.3% |
| 54.8% | Red Zone TD Rate | 50.0% |
| 0.102 | Def. EPA / Play Allowed | 0.103 |
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
- MetLife Stadium
- Kickoff
- Sun, Oct 4, 1:00 PM ET
- Roof
- outdoors
- Surface
- fieldturf
- Away rest
- 7 days
- Home rest
- 7 days
- Site
- New York Giants home game
Player Impact
Jacoby Brissett
QB2026 Weeks 1, 2, 3
- CMP/ATT
- 82/117
- Pass yds
- 652
- Pass TD
- 4
- INT
- 1
- Y/A
- 5.6
- Sacks
- 5
Jeremiyah Love
RB2026 Weeks 1, 2, 3
- Carries
- 41
- Rush yds
- 160
- YPC
- 3.9
- Rush TD
- 1
- Targets
- 12
- Rec
- 10
- Rush share
- 52.6%
Tyler Allgeier
RB2026 Weeks 1, 2, 3
- Carries
- 24
- Rush yds
- 70
- YPC
- 2.9
- Rush TD
- 0
- Targets
- 8
- Rec
- 8
- Rush share
- 30.8%
Trey McBride
TE2026 Weeks 1, 2, 3
- Targets
- 34
- Rec
- 26
- Rec yds
- 211
- YPR
- 8.1
- Rec TD
- 2
- Target share
- 30.1%
Michael Wilson
WR2026 Weeks 1, 2, 3
- Targets
- 31
- Rec
- 18
- Rec yds
- 163
- YPR
- 9.1
- Rec TD
- 1
- Target share
- 27.4%
Away · Arizona Cardinals
Jacoby Brissett
QB2026 Weeks 1, 2, 3
- CMP/ATT
- 82/117
- Pass yds
- 652
- Pass TD
- 4
- INT
- 1
- Y/A
- 5.6
- Sacks
- 5
Jeremiyah Love
RB2026 Weeks 1, 2, 3
- Carries
- 41
- Rush yds
- 160
- YPC
- 3.9
- Rush TD
- 1
- Targets
- 12
- Rec
- 10
- Rush share
- 52.6%
Tyler Allgeier
RB2026 Weeks 1, 2, 3
- Carries
- 24
- Rush yds
- 70
- YPC
- 2.9
- Rush TD
- 0
- Targets
- 8
- Rec
- 8
- Rush share
- 30.8%
Trey McBride
TE2026 Weeks 1, 2, 3
- Targets
- 34
- Rec
- 26
- Rec yds
- 211
- YPR
- 8.1
- Rec TD
- 2
- Target share
- 30.1%
Michael Wilson
WR2026 Weeks 1, 2, 3
- Targets
- 31
- Rec
- 18
- Rec yds
- 163
- YPR
- 9.1
- Rec TD
- 1
- Target share
- 27.4%
Home · New York Giants
Jameis Winston
QB2026 Weeks 2, 3
- CMP/ATT
- 25/49
- Pass yds
- 229
- Pass TD
- 0
- INT
- 1
- Y/A
- 4.7
- Sacks
- 5
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, 3
- Carries
- 50
- Rush yds
- 177
- YPC
- 3.5
- Rush TD
- 1
- Targets
- 8
- Rec
- 7
- Rush share
- 54.9%
Najee Harris
RB2026 Weeks 2, 3
- Carries
- 13
- Rush yds
- 58
- YPC
- 4.5
- Rush TD
- 0
- Targets
- 0
- Rec
- 0
- Rush share
- 14.3%
Isaiah Likely
TE2026 Weeks 1, 2, 3
- Targets
- 23
- Rec
- 15
- Rec yds
- 124
- YPR
- 8.3
- Rec TD
- 2
- Target share
- 28%
Malik Nabers
WR2026 Weeks 1, 2, 3
- Targets
- 19
- Rec
- 12
- Rec yds
- 96
- YPR
- 8
- Rec TD
- 0
- Target share
- 23.2%
Injuries & Availability
Home · New York Giants
Jaxson DartQB
IRSeason-ending knee injury; placed on injured reserve.
Jameis Winston started Week 3. The model has no explicit quarterback adjustment.
Scoring by Quarter
Sample · 3 gamesAway · Arizona Cardinals
Home · New York Giants
Small sample — treat quarter splits as descriptive context, not a trend.
Latest News
- Giants' J.J. McCarthy gamble shows they're not giving up after Jaxson Dart's injury
Yahoo Sports NFL · 1h ago · NYG
- Brian Burns confirmed to have torn ACL
Yahoo Sports NFL · 3h ago · NYG
- Does Giants' trade for J.J. McCarthy make sense? Coaches, execs explain 2 key reasons
Yahoo Sports NFL · 3h ago · NYG
- Giants trade for Vikings QB McCarthy, but say Winston remains QB1
ESPN NFL · 3h ago · MIN / NYG
- Giants pass rusher Burns has torn ACL, Harbaugh confirms
ESPN NFL · 7h ago · NYG / TEN
Analytical Angles
Passing profile · ARI
passingArizona Cardinals ranks in the 52th league percentile in blended dropback EPA entering Week 4.
Defense profile · ARI
efficiencyArizona Cardinals ranks in the 16th league percentile in blended defensive EPA allowed; higher percentile means less EPA conceded.
Passing profile · NYG
passingNew York Giants ranks in the 55th league percentile in blended dropback EPA entering Week 4.
Defense profile · NYG
efficiencyNew York Giants ranks in the 10th 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 New York Giants at 57.8%.
- Rolling efficiency favors New York Giants at 54.4%.
- The calibrated estimate is 57%; it is a probability, not a certainty.
What Could Flip It
- The statistical sample includes 3 current-season games for Arizona Cardinals and 3 for New York Giants; 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
Arizona Cardinals at New York Giants: the v0.3 ensemble places New York Giants at 57% 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 Arizona Cardinals and 3 for New York Giants; prior-season form is still blended in. No odds, moneylines, spreads, public picks or market consensus are model inputs.
Forecast
Model pick: New York Giants (57%). Signal: Unrated; 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.