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Week 1 · Sun, 1:00 PM EDT · CBS

New York Jets at Tennessee Titans

Nissan Stadium, Nashville, TN

New York Jets logo
Jets
NYJ
3-14 · #31
61%
TEN to win
TEN -3.0 · Lean
Tennessee Titans logo
Titans
TEN
3-14 · #29

Market line for comparison: TEN -1.5 · O/U 38.5 (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
128480%1027.4
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
124015%186.0
Offense / defense split
17.6 PPG scored, 29.6 allowed → offense 1366, defense 1336
12010%0.0
Blended 2025 rating1277.8
Offseason regression
25% back toward the 1500 league mean
1333.4
Roster / QB adjustment
No offseason adjustment applied.
0.0
NYJ 2026 starting rating1333

Tennessee Titans

InputRatingWeightContribution
Elo from results
3-14 in 2025, opponent-adjusted
133780%1069.8
Scoring strength
284–478 points (-194.0 differential) → 22.6% expected win rate
12865%64.3
Late-season form
same replay with the closing 6 weeks counted double
136215%204.3
Offense / defense split
16.7 PPG scored, 28.1 allowed → offense 1342, defense 1372
12150%0.0
Blended 2025 rating1338.4
Offseason regression
25% back toward the 1500 league mean
1378.8
Roster / QB adjustment
No offseason adjustment applied.
0.0
TEN 2026 starting rating1379

The calculation

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

Tennessee Titans base rating
1378.8
2026 starting Elo, after offseason regression
New York Jets base rating
− 1333.4
2026 starting Elo, after offseason regression
Rating edge (home perspective)
+45.5
TEN is the better-rated side on neutral ground
Home-field advantage
+30.0
Flat 35 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
Adjusted Elo difference
+75.5

Win probability

1 / (1 + 10−(75.5 / 400))

60.7% TEN

Model spread

75.5 ÷ 25, rounded to the nearest half point

TEN -3.0

Confidence band

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

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 logo
New York Jets
#31 of 32 · 3-14 in 2025
2025 final rating
1284.3
Regress 25% toward 1500
+49.1
2026 starting rating
1333.4

2025 Elo trail

Biggest swings

  • L 1030 vs BUF48.9
  • L 2237 vs DAL40.9
  • L 1034 vs MIA38.8
Tennessee Titans logo
Tennessee Titans
#29 of 32 · 3-14 in 2025
2025 final rating
1337.3
Regress 25% toward 1500
+41.5
2026 starting rating
1378.8

2025 Elo trail

Biggest swings

  • W 269 vs KC+74.4
  • L 026 at HOU40.3
  • L 1933 vs LAR39.5

Matchup factors

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

Home field

+30.0 pts

worth 4.2 points of win probability

TEN hosts at Nissan Stadium. Every host gets the same flat 35 points — the model does not rate crowds individually.

Rest

+0.0 pts

Week 1: both teams come off the same offseason, 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

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.

New York Jets

1522

average opponent rating · 4th toughest of 32

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

1544

average opponent rating · toughest of 32

vs above-average teams
0-10
vs below-average teams
3-4

What the model does not know

  • · Injuries, suspensions and depth-chart changes.
  • · 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 →