Mort's Report — Sports Data Analytics
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Week 2 · Sun, 1:00 PM EDT · FOX

Philadelphia Eagles at Tennessee Titans

Nissan Stadium, Nashville, TN

Philadelphia Eagles
Eagles
PHI
11-6 · #16
63%
PHI to win
PHI -4.0 · Lean
Tennessee Titans
Titans
TEN
3-14 · #28

Market line for comparison: PHI -7 · O/U 39.5 (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.

Philadelphia Eagles

InputRatingWeightContribution
Elo from results
11-6 in 2025, opponent-adjusted
150280%1201.7
Scoring strength
379–325 points (+54.0 differential) → 59.0% expected win rate
15635%78.2
Late-season form
same replay with the closing 6 weeks counted double
147315%220.9
Offense / defense split
22.3 PPG scored, 19.1 allowed → offense 1482, defense 1597
15790%0.0
Blended 2025 rating1500.8
Offseason regression
25% back toward the 1500 league mean
1500.6
Roster / QB adjustment
No offseason adjustment applied.
0.0
PHI 2026 starting rating1501

Tennessee Titans

InputRatingWeightContribution
Elo from results
3-14 in 2025, opponent-adjusted
142180%1136.5
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
141315%212.0
Offense / defense split
16.7 PPG scored, 28.1 allowed → offense 1342, defense 1372
12150%0.0
Blended 2025 rating1412.7
Offseason regression
25% back toward the 1500 league mean
1434.5
Roster / QB adjustment
No offseason adjustment applied.
0.0
TEN 2026 starting rating1435

The calculation

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

Tennessee Titans base rating
1400.7
2026 starting Elo, after offseason regression
Philadelphia Eagles base rating
− 1511.5
2026 starting Elo, after offseason regression
Rating edge (home perspective)
−110.8
PHI 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
−9.8
TEN is the more banged-up side — see the injury breakdown below
Adjusted Elo difference
−95.5

Win probability

1 / (1 + 10−(-95.5 / 400))

63.4% PHI

Model spread

-95.5 ÷ 25, rounded to the nearest half point

PHI -4.0

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

62.1%

PHI by 3.5

Injury term

−9.8 Elo

−0.4 pts of spread, home perspective

After injuries

63.4%

PHI by 4.0 · moved 1.3 pts of probability

Philadelphia Eagles

−0.9 pts

  • Lane Johnson OTOut−0.10
  • DeVonta Smith WROut−0.10
  • Nolan Smith Jr. LBOut−0.10
  • Jake Majors COut−0.10

Tennessee Titans

−0.3 pts

  • Calvin Ridley WROut−0.10
  • Tyjae Spears RBOut−0.10
  • Dorian Mausi LBOut−0.10
  • Tommy Townsend PQuestionable−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.

1401

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

1511

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

62.1% PHI

Model value

Model spread

PHI -3.5

Elo diff −85.8 · 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.

Philadelphia Eagles
Philadelphia Eagles
#16 of 32 · 11-6 in 2025
2025 final rating
1502.2
Regress 25% toward 1500
−1.5
2026 starting rating
1500.6

2025 Elo trail

Biggest swings

  • L 17–34 at NYG−52.9
  • L 17–24 vs WSH−46.7
  • L 15–24 vs CHI−35.6
Tennessee Titans
Tennessee Titans
#28 of 32 · 3-14 in 2025
2025 final rating
1420.6
Regress 25% toward 1500
+14.0
2026 starting rating
1434.5

2025 Elo trail

Biggest swings

  • W 26–9 vs KC+47.8
  • L 0–26 at HOU−37.4
  • L 19–33 vs LAR−35.3

Matchup factors

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

Home field

+25.0 pts

worth 3.3 points of win probability

TEN hosts at Nissan 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

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.

Philadelphia Eagles

1489

average opponent rating · 28th toughest of 32

vs above-average teams
3-3
vs below-average teams
8-3
Tennessee Titans

1523

average opponent rating · toughest of 32

vs above-average teams
0-11
vs below-average teams
3-3

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 →