Mort's Report — Sports Data Analytics
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Week 5 · Sun, 1:00 PM EDT · Fox

Chicago Bears at Green Bay Packers

Lambeau Field, Green Bay, WI

Chicago Bears
Bears
CHI
11-6 · #12
55%
GB to win
GB -1.5 · Coin flip
Green Bay Packers
Packers
GB
9-7-1 · #21

Market line for comparison: CHI -3 · O/U 45.5 (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.

Chicago Bears

InputRatingWeightContribution
Elo from results
11-6 in 2025, opponent-adjusted
152380%1218.0
Scoring strength
441–415 points (+26.0 differential) → 53.6% expected win rate
15255%76.3
Late-season form
same replay with the closing 6 weeks counted double
150915%226.3
Offense / defense split
25.9 PPG scored, 24.4 allowed → offense 1573, defense 1465
15380%0.0
Blended 2025 rating1520.6
Offseason regression
25% back toward the 1500 league mean
1515.5
Roster / QB adjustment
No offseason adjustment applied.
0.0
CHI 2026 starting rating1515

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
1452.5
2026 starting Elo, after offseason regression
Chicago Bears base rating
− 1565.0
2026 starting Elo, after offseason regression
Rating edge (home perspective)
−112.5
CHI is the better-rated side on neutral ground
Home-field advantage
+25.0
Flat 25 points for every host
Rest differential
+0.0
Both teams open the season equally rested
Analyst override
+0.0
No manual adjustment on this game
Injury adjustment
+120.5
CHI is the more banged-up side — see the injury breakdown below
Adjusted Elo difference
+33.0

Win probability

1 / (1 + 10−(33.0 / 400))

54.7% GB

Model spread

33.0 ÷ 25, rounded to the nearest half point

GB -1.5

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

37.7%

GB by 3.5

Injury term

+120.5 Elo

+4.8 pts of spread, home perspective

After injuries

54.7%

GB by 1.5 · moved 17.1 pts of probability

Chicago Bears

−0.5 pts

  • Kyle Monangai RBOut−0.10
  • Cole Kmet TEOut−0.10
  • T.J. Edwards LBOut−0.10
  • Jack Sanborn LBOut−0.10

Green Bay Packers

−0.4 pts

  • Jacob Monk COut−0.10
  • Zaire Franklin LBOut−0.10
  • Sean Rhyan GDoubtful−0.08
  • Anthony Campbell DTQuestionable−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.

1452

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

1565

The two ratings only matter through their difference.

+25 pts

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

+0 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

62.3% CHI

Model value

Model spread

CHI -3.5

Elo diff −87.5 · 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.

Chicago Bears
Chicago Bears
#12 of 32 · 11-6 in 2025
2025 final rating
1522.5
Regress 25% toward 1500
−7.1
2026 starting rating
1515.5

2025 Elo trail

Biggest swings

  • L 16–30 at BAL−49.8
  • L 21–52 at DET−46.5
  • W 31–14 vs DAL+44.9
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 3.6 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

+0.0 pts

Both teams come in on equal rest, so there is no rest edge to give.

Analyst override

+0.0 pts

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

2025 head to head

  • Week 14: GB won 28–21 (GB at home)
  • Week 16: CHI won 22–16 (GB on the road)

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.

Chicago Bears

1494

average opponent rating · 25th toughest of 32

vs above-average teams
4-3
vs below-average teams
7-3
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 →