Mort's Report — Sports Data Analytics
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Week 8 · Sun, 1:00 PM EST · CBS

Cleveland Browns at Pittsburgh Steelers

Acrisure Stadium, Pittsburgh, PA

Cleveland Browns
Browns
CLE
5-12 · #20
59%
PIT to win
PIT -2.5 · Lean
Pittsburgh Steelers
Steelers
PIT
10-7 · #11

Market line for comparison: PIT -3.5 · 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.

Cleveland Browns

InputRatingWeightContribution
Elo from results
5-12 in 2025, opponent-adjusted
147780%1181.3
Scoring strength
279–379 points (-100.0 differential) → 32.6% expected win rate
13745%68.7
Late-season form
same replay with the closing 6 weeks counted double
150515%225.8
Offense / defense split
16.4 PPG scored, 22.3 allowed → offense 1335, defense 1518
13530%0.0
Blended 2025 rating1475.8
Offseason regression
25% back toward the 1500 league mean
1481.8
Roster / QB adjustment
No offseason adjustment applied.
0.0
CLE 2026 starting rating1482

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

The calculation

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

Pittsburgh Steelers base rating
1564.4
2026 starting Elo, after offseason regression
Cleveland Browns base rating
− 1523.1
2026 starting Elo, after offseason regression
Rating edge (home perspective)
+41.3
PIT 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
−1.0
PIT is the more banged-up side — see the injury breakdown below
Adjusted Elo difference
+65.3

Win probability

1 / (1 + 10−(65.3 / 400))

59.3% PIT

Model spread

65.3 ÷ 25, rounded to the nearest half point

PIT -2.5

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

59.4%

PIT by 2.5

Injury term

−1.0 Elo

−0.0 pts of spread, home perspective

After injuries

59.3%

PIT by 2.5 · moved 0.1 pts of probability

Cleveland Browns

−0.3 pts

  • Teven Jenkins GOut−0.10
  • Mike Hall Jr. DTOut−0.10
  • Tytus Howard OTQuestionable−0.03
  • Myles Harden CBQuestionable−0.03

Pittsburgh Steelers

−0.3 pts

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

1564

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

1523

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

59.4% PIT

Model value

Model spread

PIT -2.5

Elo diff +66.3 · 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.

Cleveland Browns
Cleveland Browns
#20 of 32 · 5-12 in 2025
2025 final rating
1476.6
Regress 25% toward 1500
+5.2
2026 starting rating
1481.8

2025 Elo trail

Biggest swings

  • W 31–6 vs MIA+44.1
  • L 17–41 at BAL−41.1
  • W 13–6 vs PIT+40.9
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

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

PIT hosts at Acrisure 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

  • Week 6: PIT won 23–9 (PIT at home)
  • Week 17: CLE won 13–6 (PIT on the road)

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.

Cleveland Browns

1499

average opponent rating · 17th toughest of 32

vs above-average teams
1-8
vs below-average teams
4-4
Pittsburgh Steelers

1506

average opponent rating · 10th toughest of 32

vs above-average teams
4-4
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 →