Mort's Report — Sports Data Analytics
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Week 8 · Mon, 8:15 PM EST · ESPN

Chicago Bears at Seattle Seahawks

Lumen Field, Seattle, WA

Chicago Bears
Bears
CHI
11-6 · #12
54%
SEA to win
SEA -1.5 · Coin flip
Seattle Seahawks
Seahawks
SEA
14-3 · #1

Market line for comparison: SEA -3 · O/U 46.5 (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

Seattle Seahawks

InputRatingWeightContribution
Elo from results
14-3 in 2025, opponent-adjusted
164380%1314.2
Scoring strength
483–292 points (+191.0 differential) → 76.7% expected win rate
17075%85.4
Late-season form
same replay with the closing 6 weeks counted double
172415%258.6
Offense / defense split
28.4 PPG scored, 17.2 allowed → offense 1635, defense 1646
17810%0.0
Blended 2025 rating1658.2
Offseason regression
25% back toward the 1500 league mean
1618.6
Roster / QB adjustment
No offseason adjustment applied.
0.0
SEA 2026 starting rating1619

The calculation

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

Seattle Seahawks base rating
1576.0
2026 starting Elo, after offseason regression
Chicago Bears base rating
− 1558.2
2026 starting Elo, after offseason regression
Rating edge (home perspective)
+17.8
SEA 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
+3.5
CHI is the more banged-up side — see the injury breakdown below
Adjusted Elo difference
+31.3

Win probability

1 / (1 + 10−(31.3 / 400))

54.5% SEA

Model spread

31.3 ÷ 25, rounded to the nearest half point

SEA -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

54.0%

SEA by 1.0

Injury term

+3.5 Elo

+0.1 pts of spread, home perspective

After injuries

54.5%

SEA by 1.5 · moved 0.5 pts of probability

Chicago Bears

−0.5 pts

  • Anthony Johnson Jr. SOut−0.10
  • Cole Kmet TEOut−0.10
  • T.J. Edwards LBOut−0.10
  • Jack Sanborn LBOut−0.10

Seattle Seahawks

−0.4 pts

  • Jadarian Price RBOut−0.10
  • Charles Cross OTDoubtful−0.08
  • Zach Charbonnet RBQuestionable−0.03
  • Rashid Shaheed 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.

1576

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

1558

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

54.0% SEA

Model value

Model spread

SEA -1.0

Elo diff +27.8 · Coin flip

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
Seattle Seahawks
Seattle Seahawks
#1 of 32 · 14-3 in 2025
2025 final rating
1642.8
Regress 25% toward 1500
−24.1
2026 starting rating
1618.6

2025 Elo trail

Biggest swings

  • W 31–17 at PIT+45.9
  • W 20–12 at JAX+36.3
  • W 44–13 vs NO+34.4

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

SEA hosts at Lumen 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

These teams did not meet in 2025. Past meetings carry no weight in the model anyway — they are already baked into each team's rating.

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
Seattle Seahawks

1503

average opponent rating · 13th toughest of 32

vs above-average teams
8-2
vs below-average teams
6-1

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 →