Mort's Report — Sports Data Analytics
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Week 7 · Sun, 9:30 AM EDT · NFL Net

Pittsburgh Steelers at New Orleans Saints

Neutral site · Stade de France, Saint-Denis

Pittsburgh Steelers
Steelers
PIT
10-7 · #11
61%
PIT to win
PIT -3.0 · Lean
New Orleans Saints
Saints
NO
6-11 · #14

Market line for comparison: PIT -3.5 · O/U 44.5 (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.

Pittsburgh Steelers

InputRatingWeightContribution
Elo from results
10-7 in 2025, opponent-adjusted
152380%1218.6
Scoring strength
397–387 points (+10.0 differential) → 51.5% expected win rate
15115%75.5
Late-season form
same replay with the closing 6 weeks counted double
153515%230.3
Offense / defense split
23.4 PPG scored, 22.8 allowed → offense 1509, defense 1506
15150%0.0
Blended 2025 rating1524.4
Offseason regression
25% back toward the 1500 league mean
1518.3
Roster / QB adjustment
No offseason adjustment applied.
0.0
PIT 2026 starting rating1518

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

The calculation

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

New Orleans Saints base rating
1479.1
2026 starting Elo, after offseason regression
Pittsburgh Steelers base rating
− 1550.5
2026 starting Elo, after offseason regression
Rating edge (home perspective)
−71.4
PIT is the better-rated side on neutral ground
Home-field advantage
+0.0
Neutral site (Saint-Denis) — no home-field points applied
Rest differential
+0.0
Both teams open the season equally rested
Analyst override
+0.0
No manual adjustment on this game
Injury adjustment
−5.8
NO is the more banged-up side — see the injury breakdown below
Adjusted Elo difference
−77.2

Win probability

1 / (1 + 10−(-77.2 / 400))

60.9% PIT

Model spread

-77.2 ÷ 25, rounded to the nearest half point

PIT -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

60.1%

PIT by 3.0

Injury term

−5.8 Elo

−0.2 pts of spread, home perspective

After injuries

60.9%

PIT by 3.0 · moved 0.8 pts of probability

Pittsburgh Steelers

−0.3 pts

  • Sebastian Joseph-Day DTOut−0.10
  • Ben Skowronek WROut−0.10
  • Brandin Echols CBOut−0.10

New Orleans Saints

−0.2 pts

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

1479

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

1550

The two ratings only matter through their difference.

+0 pts

Neutral site, so the model applies 0. The tuned value elsewhere is 25.

+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

60.1% PIT

Model value

Model spread

PIT -3.0

Elo diff −71.4 · 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.

Pittsburgh Steelers
Pittsburgh Steelers
#11 of 32 · 10-7 in 2025
2025 final rating
1523.3
Regress 25% toward 1500
−5.0
2026 starting rating
1518.3

2025 Elo trail

Biggest swings

  • L 17–31 vs SEA−45.9
  • L 7–26 vs BUF−42.7
  • L 6–13 at CLE−40.9
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

Matchup factors

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

Home field

Neutral

Played at Stade de France, Saint-Denis. Neither side gets the 25-point host bonus.

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.

Pittsburgh Steelers

1506

average opponent rating · 10th toughest of 32

vs above-average teams
4-4
vs below-average teams
6-3
New Orleans Saints

1496

average opponent rating · 21st toughest of 32

vs above-average teams
0-8
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 →