Mort's Report — Sports Data Analytics
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Week 4 · Sun, 1:00 PM EDT · FOX

Dallas Cowboys at Houston Texans

Reliant Stadium, Houston, TX

Dallas Cowboys
Cowboys
DAL
7-9-1 · #27
58%
HOU to win
HOU -2.5 · Lean
Houston Texans
Texans
HOU
12-5 · #3

Market line for comparison: HOU -2.5 · O/U 47.5 (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.

Dallas Cowboys

InputRatingWeightContribution
Elo from results
7-9-1 in 2025, opponent-adjusted
143780%1149.9
Scoring strength
471–511 points (-40.0 differential) → 45.2% expected win rate
14665%73.3
Late-season form
same replay with the closing 6 weeks counted double
138615%207.9
Offense / defense split
27.7 PPG scored, 30.1 allowed → offense 1617, defense 1324
14410%0.0
Blended 2025 rating1431.1
Offseason regression
25% back toward the 1500 league mean
1448.3
Roster / QB adjustment
No offseason adjustment applied.
0.0
DAL 2026 starting rating1448

Houston Texans

InputRatingWeightContribution
Elo from results
12-5 in 2025, opponent-adjusted
160880%1286.6
Scoring strength
404–295 points (+109.0 differential) → 67.8% expected win rate
16295%81.5
Late-season form
same replay with the closing 6 weeks counted double
166115%249.1
Offense / defense split
23.8 PPG scored, 17.4 allowed → offense 1519, defense 1642
16600%0.0
Blended 2025 rating1617.1
Offseason regression
25% back toward the 1500 league mean
1587.8
Roster / QB adjustment
No offseason adjustment applied.
0.0
HOU 2026 starting rating1588

The calculation

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

Houston Texans base rating
1488.7
2026 starting Elo, after offseason regression
Dallas Cowboys base rating
− 1461.6
2026 starting Elo, after offseason regression
Rating edge (home perspective)
+27.1
HOU 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
+5.3
DAL is the more banged-up side — see the injury breakdown below
Adjusted Elo difference
+57.4

Win probability

1 / (1 + 10−(57.4 / 400))

58.2% HOU

Model spread

57.4 ÷ 25, rounded to the nearest half point

HOU -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

57.4%

HOU by 2.0

Injury term

+5.3 Elo

+0.2 pts of spread, home perspective

After injuries

58.2%

HOU by 2.5 · moved 0.7 pts of probability

Dallas Cowboys

−0.3 pts

  • Marist Liufau LBOut−0.10
  • P.J. Locke SOut−0.10
  • Dee Winters LBQuestionable−0.03
  • KaVontae Turpin WRQuestionable−0.03

Houston Texans

−0.4 pts

  • David Montgomery RBOut−0.10
  • Jalen Pitre SOut−0.10
  • Blake Fisher OTOut−0.10
  • Reed Blankenship SOut−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.

1489

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

1462

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

57.4% HOU

Model value

Model spread

HOU -2.0

Elo diff +52.1 · 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.

Dallas Cowboys
Dallas Cowboys
#27 of 32 · 7-9-1 in 2025
2025 final rating
1437.3
Regress 25% toward 1500
+11.0
2026 starting rating
1448.3

2025 Elo trail

Biggest swings

  • W 44–22 vs WSH+46.9
  • L 14–31 at CHI−44.9
  • L 17–34 at NYG−41.6
Houston Texans
Houston Texans
#3 of 32 · 12-5 in 2025
2025 final rating
1608.2
Regress 25% toward 1500
−20.4
2026 starting rating
1587.8

2025 Elo trail

Biggest swings

  • W 44–10 at BAL+49.0
  • W 26–0 vs TEN+37.4
  • W 26–15 vs SF+34.7

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

HOU hosts at Reliant 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.

Dallas Cowboys

1476

average opponent rating · 31st toughest of 32

vs above-average teams
1-5
vs below-average teams
6-4-1
Houston Texans

1503

average opponent rating · 14th toughest of 32

vs above-average teams
5-4
vs below-average teams
7-1

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 →