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

New Orleans Saints at Detroit Lions

Ford Field, Detroit, MI

New Orleans Saints
Saints
NO
6-11 · #14
53%
DET to win
DET -1.0 · Coin flip
Detroit Lions
Lions
DET
9-8 · #17

Market line for comparison: DET -7 · O/U 49.5 (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 Orleans Saints

InputRatingWeightContribution
Elo from results
6-11 in 2025, opponent-adjusted
151280%1209.4
Scoring strength
306–383 points (-77.0 differential) → 37.0% expected win rate
14085%70.4
Late-season form
same replay with the closing 6 weeks counted double
155215%232.8
Offense / defense split
18.0 PPG scored, 22.5 allowed → offense 1375, defense 1512
13870%0.0
Blended 2025 rating1512.6
Offseason regression
25% back toward the 1500 league mean
1509.4
Roster / QB adjustment
No offseason adjustment applied.
0.0
NO 2026 starting rating1509

Detroit Lions

InputRatingWeightContribution
Elo from results
9-8 in 2025, opponent-adjusted
149380%1194.8
Scoring strength
481–413 points (+68.0 differential) → 58.9% expected win rate
15635%78.1
Late-season form
same replay with the closing 6 weeks counted double
149415%224.1
Offense / defense split
28.3 PPG scored, 24.3 allowed → offense 1632, defense 1468
16000%0.0
Blended 2025 rating1496.9
Offseason regression
25% back toward the 1500 league mean
1497.7
Roster / QB adjustment
No offseason adjustment applied.
0.0
DET 2026 starting rating1498

The calculation

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

Detroit Lions base rating
1497.7
2026 starting Elo, after offseason regression
New Orleans Saints base rating
− 1509.4
2026 starting Elo, after offseason regression
Rating edge (home perspective)
−11.7
NO 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
+6.8
NO is the more banged-up side — see the injury breakdown below
Adjusted Elo difference
+20.0

Win probability

1 / (1 + 10−(20.0 / 400))

52.9% DET

Model spread

20.0 ÷ 25, rounded to the nearest half point

DET -1.0

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

51.9%

DET by 0.5

Injury term

+6.8 Elo

+0.3 pts of spread, home perspective

After injuries

52.9%

DET by 1.0 · moved 1.0 pts of probability

New Orleans Saints

−0.2 pts

  • Jordyn Tyson WROut−0.10
  • CJ Donaldson RBQuestionable−0.03
  • Cesar Ruiz GQuestionable−0.03
  • Nathan Shepherd DTQuestionable−0.03

Detroit Lions

−0.5 pts

  • Devin White LBOut−0.10
  • Ben Bartch GOut−0.10
  • Kerby Joseph SOut−0.10
  • Tom Kennedy WROut−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.

1498

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

1509

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

51.9% DET

Model value

Model spread

DET -0.5

Elo diff +13.3 · 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.

New Orleans Saints
New Orleans Saints
#14 of 32 · 6-11 in 2025
2025 final rating
1511.8
Regress 25% toward 1500
−2.4
2026 starting rating
1509.4

2025 Elo trail

Biggest swings

  • W 17–7 at CAR+48.3
  • L 10–24 vs ATL−45.0
  • W 26–14 vs NYG+37.6
Detroit Lions
Detroit Lions
#17 of 32 · 9-8 in 2025
2025 final rating
1493.4
Regress 25% toward 1500
+4.3
2026 starting rating
1497.7

2025 Elo trail

Biggest swings

  • W 52–21 vs CHI+46.5
  • L 17–30 at KC−42.5
  • W 44–30 vs DAL+38.4

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

DET hosts at Ford Field. 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.

New Orleans Saints

1496

average opponent rating · 21st toughest of 32

vs above-average teams
0-8
vs below-average teams
6-3
Detroit Lions

1496

average opponent rating · 22nd toughest of 32

vs above-average teams
3-5
vs below-average teams
6-3

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 →