Mort's Report — Sports Data Analytics
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Week 6 · Sun, 8:20 PM EDT · NBC

Dallas Cowboys at Green Bay Packers

Lambeau Field, Green Bay, WI

Dallas Cowboys
Cowboys
DAL
7-9-1 · #27
59%
GB to win
GB -2.5 · Lean
Green Bay Packers
Packers
GB
9-7-1 · #21

Market line for comparison: GB -1.5 · O/U 52.5 (DraftKings). The model never sees this.

Rating inputs

Each starting rating is a weighted blend of five real football inputs, not just wins and losses. Every term below is measured from the 2025 season.

Dallas Cowboys

InputRatingWeightContribution
Elo from results
7-9-1 in 2025, opponent-adjusted
143780%1149.9
Scoring strength
471–511 points (-40.0 differential) → 45.2% expected win rate
14665%73.3
Late-season form
same replay with the closing 6 weeks counted double
138615%207.9
Offense / defense split
27.7 PPG scored, 30.1 allowed → offense 1617, defense 1324
14410%0.0
Blended 2025 rating1431.1
Offseason regression
25% back toward the 1500 league mean
1448.3
Roster / QB adjustment
No offseason adjustment applied.
0.0
DAL 2026 starting rating1448

Green Bay Packers

InputRatingWeightContribution
Elo from results
9-7-1 in 2025, opponent-adjusted
146180%1168.7
Scoring strength
391–360 points (+31.0 differential) → 54.9% expected win rate
15345%76.7
Late-season form
same replay with the closing 6 weeks counted double
140615%210.9
Offense / defense split
23.0 PPG scored, 21.2 allowed → offense 1500, defense 1546
15460%0.0
Blended 2025 rating1456.3
Offseason regression
25% back toward the 1500 league mean
1467.2
Roster / QB adjustment
No offseason adjustment applied.
0.0
GB 2026 starting rating1467

The calculation

Every term the model applies, in order, from both teams' starting ratings to the number on the card.

Green Bay Packers base rating
1509.9
2026 starting Elo, after offseason regression
Dallas Cowboys base rating
− 1452.9
2026 starting Elo, after offseason regression
Rating edge (home perspective)
+57.0
GB is the better-rated side on neutral ground
Home-field advantage
+25.0
Flat 25 points for every host
Rest differential
−15.0
5 Elo per day of extra rest, capped at 25
Analyst override
+0.0
No manual adjustment on this game
Injury adjustment
−4.3
GB is the more banged-up side — see the injury breakdown below
Adjusted Elo difference
+62.8

Win probability

1 / (1 + 10−(62.8 / 400))

58.9% GB

Model spread

62.8 ÷ 25, rounded to the nearest half point

GB -2.5

Confidence band

Coin flip · under 55%Lean · 55–65%Confident · 65–75%Strong · 75% and up

Injury adjustment

Report pulled 2026-10-27 13:20 UTC

Ratings describe a team over a whole season. Who is actually available on Sunday is a separate question, so the injury adjustment is applied last, after home field and rest. Each listed player costs a share of a point of spread based on his position, whether he starts, and how likely he is to play.

Before injuries

59.5%

GB by 2.5

Injury term

−4.3 Elo

−0.2 pts of spread, home perspective

After injuries

58.9%

GB by 2.5 · moved 0.6 pts of probability

Dallas Cowboys

−0.3 pts

  • P.J. Locke SOut−0.10
  • Marist Liufau LBOut−0.10
  • KaVontae Turpin WRQuestionable−0.03
  • Drew Shelton OTQuestionable−0.03

Green Bay Packers

−0.4 pts

  • Zaire Franklin LBOut−0.10
  • Jacob Monk COut−0.10
  • Sean Rhyan GDoubtful−0.08
  • Matthew Golden WRQuestionable−0.03

Statuses come straight from the league injury report: out and injured reserve count in full, doubtful three quarters, questionable roughly a third, probable a tenth. Starters are identified from the depth chart; anyone the model cannot place is treated as a backup.

Move the factors yourself

Every term feeds one number: the adjusted Elo difference. Drag any of them and watch the spread and confidence follow.

1510

Drag to see how much a stronger or weaker host changes the call.

1453

The two ratings only matter through their difference.

+25 pts

The tuned value is a flat 25 points for every host.

−15 pts

5 Elo per extra day of rest, capped at 25 either way.

+0 pts

A manual thumb on the scale, in the home team's direction.

Win probability

59.5% GB

Model value

Model spread

GB -2.5

Elo diff +67.0 · Lean

Probability curve

The logistic curve from −600 to +600 Elo, home perspective. The dot is your current setting; the faint vertical line is where the model itself sits. Notice the curve is flattest at the extremes — near a coin flip, every point of Elo moves the number most.

Where the ratings came from

Each rating is the end state of a full 2025 season of Elo updates, regressed toward the league mean for the new season.

Dallas Cowboys
Dallas Cowboys
#27 of 32 · 7-9-1 in 2025
2025 final rating
1437.3
Regress 25% toward 1500
+11.0
2026 starting rating
1448.3

2025 Elo trail

Biggest swings

  • W 44–22 vs WSH+46.9
  • L 14–31 at CHI−44.9
  • L 17–34 at NYG−41.6
Green Bay Packers
Green Bay Packers
#21 of 32 · 9-7-1 in 2025
2025 final rating
1460.9
Regress 25% toward 1500
+6.3
2026 starting rating
1467.2

2025 Elo trail

Biggest swings

  • L 24–41 vs BAL−48.3
  • W 27–13 vs DET+34.8
  • W 35–25 at PIT+32.8

Matchup factors

Everything beyond the two base ratings that moved this specific number.

Home field

+25.0 pts

worth 3.5 points of win probability

GB hosts at Lambeau Field. Every host gets the same flat 25 points — the model does not rate crowds individually.

Rest

−15.0 pts

worth 2.1 points of win probability

5 Elo points per extra day of rest, capped at 25 either way.

Analyst override

+0.0 pts

No manual adjustment. The number here is pure model output.

2025 head to head

  • Week 4: tied 40–40

Strength of schedule

Who each team actually played in 2025, measured by their opponents' current ratings. This is context for reading the ratings — it is not an input to the prediction above, because beating good teams already raises a team's Elo more.

Dallas Cowboys

1476

average opponent rating · 31st toughest of 32

vs above-average teams
1-5
vs below-average teams
6-4-1
Green Bay Packers

1498

average opponent rating · 19th toughest of 32

vs above-average teams
3-5
vs below-average teams
6-2-1

What the model does not know

  • · How an injury actually plays out — the adjustment above prices availability, not how well a replacement performs.
  • · Coaching and roster turnover between seasons.
  • · Weather, travel distance and short-week fatigue beyond raw rest days.
  • · Anything a betting market has priced in since the season ended.
Read the full methodology →