Mort's Report — Sports Data Analytics
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Week 4 · Sun, 1:00 PM EDT · CBS

Jacksonville Jaguars at Cincinnati Bengals

Paycor Stadium, Cincinnati, OH

Jacksonville Jaguars
Jaguars
JAX
13-4 · #2
60%
JAX to win
JAX -3.0 · Lean
Cincinnati Bengals
Bengals
CIN
6-11 · #18

Market line for comparison: CIN -2.5 · O/U 51.5 (Draft Kings). 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.

Jacksonville Jaguars

InputRatingWeightContribution
Elo from results
13-4 in 2025, opponent-adjusted
163080%1303.6
Scoring strength
474–336 points (+138.0 differential) → 69.3% expected win rate
16425%82.1
Late-season form
same replay with the closing 6 weeks counted double
170215%255.3
Offense / defense split
27.9 PPG scored, 19.8 allowed → offense 1622, defense 1581
17030%0.0
Blended 2025 rating1641.0
Offseason regression
25% back toward the 1500 league mean
1605.8
Roster / QB adjustment
No offseason adjustment applied.
0.0
JAX 2026 starting rating1606

Cincinnati Bengals

InputRatingWeightContribution
Elo from results
6-11 in 2025, opponent-adjusted
149480%1195.4
Scoring strength
414–492 points (-78.0 differential) → 39.9% expected win rate
14295%71.4
Late-season form
same replay with the closing 6 weeks counted double
150515%225.7
Offense / defense split
24.4 PPG scored, 28.9 allowed → offense 1534, defense 1352
13850%0.0
Blended 2025 rating1492.5
Offseason regression
25% back toward the 1500 league mean
1494.4
Roster / QB adjustment
No offseason adjustment applied.
0.0
CIN 2026 starting rating1494

The calculation

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

Cincinnati Bengals base rating
1530.4
2026 starting Elo, after offseason regression
Jacksonville Jaguars base rating
− 1606.9
2026 starting Elo, after offseason regression
Rating edge (home perspective)
−76.5
JAX 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
−18.3
CIN is the more banged-up side — see the injury breakdown below
Adjusted Elo difference
−69.7

Win probability

1 / (1 + 10−(-69.7 / 400))

59.9% JAX

Model spread

-69.7 ÷ 25, rounded to the nearest half point

JAX -3.0

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

57.4%

JAX by 2.0

Injury term

−18.3 Elo

−0.7 pts of spread, home perspective

After injuries

59.9%

JAX by 3.0 · moved 2.5 pts of probability

Jacksonville Jaguars

−0.2 pts

  • Anton Harrison OTOut−0.10
  • Ross Matiscik LSQuestionable−0.03
  • Antonio Johnson SQuestionable−0.03
  • Montaric Brown CBQuestionable−0.03

Cincinnati Bengals

−0.3 pts

  • Kyle Dugger SOut−0.10
  • Tanner Hudson TEOut−0.10
  • Swayze Bozeman LBOut−0.10
  • Erick All Jr. TEQuestionable−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.

1530

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

1607

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

57.4% JAX

Model value

Model spread

JAX -2.0

Elo diff −51.5 · 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.

Jacksonville Jaguars
Jacksonville Jaguars
#2 of 32 · 13-4 in 2025
2025 final rating
1629.5
Regress 25% toward 1500
−23.8
2026 starting rating
1605.8

2025 Elo trail

Biggest swings

  • W 35–6 vs LAC+57.7
  • L 7–35 vs LAR−43.8
  • W 34–20 at DEN+42.5
Cincinnati Bengals
Cincinnati Bengals
#18 of 32 · 6-11 in 2025
2025 final rating
1494.2
Regress 25% toward 1500
+0.2
2026 starting rating
1494.4

2025 Elo trail

Biggest swings

  • W 32–14 at BAL+67.5
  • W 45–21 at MIA+62.0
  • L 10–48 at MIN−56.5

Matchup factors

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

Home field

+25.0 pts

worth 3.4 points of win probability

CIN hosts at Paycor Stadium. 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 2: CIN won 31–27 (CIN at home)

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.

Jacksonville Jaguars

1490

average opponent rating · 27th toughest of 32

vs above-average teams
4-3
vs below-average teams
9-1
Cincinnati Bengals

1509

average opponent rating · 8th toughest of 32

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

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 →