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

Pittsburgh Steelers at New England Patriots

Gillette Stadium, Foxborough, MA

Pittsburgh Steelers
Steelers
PIT
10-7 · #11
58%
NE to win
NE -2.0 · Lean
New England Patriots
Patriots
NE
14-3 · #4

Market line for comparison: NE -4.5 · O/U 41.5 (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.

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 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
1563.9
2026 starting Elo, after offseason regression
Pittsburgh Steelers base rating
− 1540.2
2026 starting Elo, after offseason regression
Rating edge (home perspective)
+23.7
NE is the better-rated side on neutral ground
Home-field advantage
+25.0
Flat 25 points for every host
Rest differential
+20.0
5 Elo per day of extra rest, capped at 25
Analyst override
+0.0
No manual adjustment on this game
Injury adjustment
−13.8
NE is the more banged-up side — see the injury breakdown below
Adjusted Elo difference
+54.9

Win probability

1 / (1 + 10−(54.9 / 400))

57.8% NE

Model spread

54.9 ÷ 25, rounded to the nearest half point

NE -2.0

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

59.8%

NE by 2.5

Injury term

−13.8 Elo

−0.6 pts of spread, home perspective

After injuries

57.8%

NE by 2.0 · moved 1.9 pts of probability

Pittsburgh Steelers

−0.3 pts

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

New England Patriots

−0.6 pts

  • Carlton Davis III CBOut−0.10
  • Alijah Vera-Tucker GOut−0.10
  • Marcus Bryant OTOut−0.10
  • Ben Brown COut−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.

1564

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

1540

The two ratings only matter through their difference.

+25 pts

The tuned value is a flat 25 points for every host.

+20 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

59.8% NE

Model value

Model spread

NE -2.5

Elo diff +68.7 · 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 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 3.5 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

+20.0 pts

worth 2.8 points of win probability

5 Elo points per extra day of rest, capped at 25 either way.

Analyst override

+0.0 pts

No manual adjustment. The number here is pure model output.

2025 head to head

  • Week 3: PIT won 21–14 (NE at home)

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 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 →