Mort's Report — Sports Data Analytics
← Back to the schedule

Week 6 · Sun, 1:00 PM EDT · CBS

New York Jets at New England Patriots

Gillette Stadium, Foxborough, MA

New York Jets
Jets
NYJ
3-14 · #30
71%
NE to win
NE -6.0 · Confident
New England Patriots
Patriots
NE
14-3 · #4

Market line for comparison: NE -7.5 · O/U 43.5 (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.

New York Jets

InputRatingWeightContribution
Elo from results
3-14 in 2025, opponent-adjusted
137380%1098.6
Scoring strength
300–503 points (-203.0 differential) → 22.7% expected win rate
12875%64.4
Late-season form
same replay with the closing 6 weeks counted double
132415%198.6
Offense / defense split
17.6 PPG scored, 29.6 allowed → offense 1366, defense 1336
12010%0.0
Blended 2025 rating1361.6
Offseason regression
25% back toward the 1500 league mean
1396.2
Roster / QB adjustment
No offseason adjustment applied.
0.0
NYJ 2026 starting rating1396

New England Patriots

InputRatingWeightContribution
Elo from results
14-3 in 2025, opponent-adjusted
160780%1285.9
Scoring strength
490–320 points (+170.0 differential) → 73.3% expected win rate
16755%83.8
Late-season form
same replay with the closing 6 weeks counted double
164115%246.1
Offense / defense split
28.8 PPG scored, 18.8 allowed → offense 1645, defense 1605
17500%0.0
Blended 2025 rating1615.8
Offseason regression
25% back toward the 1500 league mean
1586.8
Roster / QB adjustment
No offseason adjustment applied.
0.0
NE 2026 starting rating1587

The calculation

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

New England Patriots base rating
1582.6
2026 starting Elo, after offseason regression
New York Jets base rating
− 1449.3
2026 starting Elo, after offseason regression
Rating edge (home perspective)
+133.3
NE 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
−6.5
NE is the more banged-up side — see the injury breakdown below
Adjusted Elo difference
+151.8

Win probability

1 / (1 + 10−(151.8 / 400))

70.5% NE

Model spread

151.8 ÷ 25, rounded to the nearest half point

NE -6.0

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

71.3%

NE by 6.5

Injury term

−6.5 Elo

−0.3 pts of spread, home perspective

After injuries

70.6%

NE by 6.0 · moved 0.8 pts of probability

New York Jets

−0.3 pts

  • Kiko Mauigoa LBOut−0.10
  • Joseph Ossai DEQuestionable−0.03
  • Breece Hall RBQuestionable−0.03
  • Dylan Parham GQuestionable−0.03

New England Patriots

−0.6 pts

  • Karon Prunty CBOut−0.10
  • Ben Brown COut−0.10
  • Channing Canada CBOut−0.10
  • Carlton Davis III CBOut−0.10

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.

1583

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

1449

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

71.3% NE

Model value

Model spread

NE -6.5

Elo diff +158.3 · Confident

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.

New York Jets
New York Jets
#30 of 32 · 3-14 in 2025
2025 final rating
1373.3
Regress 25% toward 1500
+22.9
2026 starting rating
1396.2

2025 Elo trail

Biggest swings

  • L 10–30 vs BUF−42.9
  • L 10–34 vs MIA−39.8
  • L 22–37 vs DAL−37.1
New England Patriots
New England Patriots
#4 of 32 · 14-3 in 2025
2025 final rating
1607.4
Regress 25% toward 1500
−20.5
2026 starting rating
1586.8

2025 Elo trail

Biggest swings

  • W 42–13 vs CAR+49.9
  • L 14–21 vs PIT−34.4
  • L 13–20 vs LV−31.6

Matchup factors

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

Home field

+25.0 pts

worth 3.1 points of win probability

NE hosts at Gillette 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 11: NE won 27–14 (NE at home)
  • Week 17: NE won 42–10 (NE 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.

New York Jets

1518

average opponent rating · 3rd toughest of 32

vs above-average teams
1-9
vs below-average teams
2-5
New England Patriots

1477

average opponent rating · 30th toughest of 32

vs above-average teams
4-2
vs below-average teams
10-1

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 →