Mort's Report — Sports Data Analytics
← Back to the schedule

Week 5 · Thu, 8:15 PM EDT · Prime Video

Tampa Bay Buccaneers at Dallas Cowboys

AT&T Stadium, Arlington, TX

Tampa Bay Buccaneers
Buccaneers
TB
8-9 · #22
77%
DAL to win
DAL -8.5 · Strong
Dallas Cowboys
Cowboys
DAL
7-9-1 · #27

Market line for comparison: DAL -9.5 · O/U 47.5 (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.

Tampa Bay Buccaneers

InputRatingWeightContribution
Elo from results
8-9 in 2025, opponent-adjusted
145280%1161.3
Scoring strength
380–411 points (-31.0 differential) → 45.4% expected win rate
14685%73.4
Late-season form
same replay with the closing 6 weeks counted double
142415%213.5
Offense / defense split
22.4 PPG scored, 24.2 allowed → offense 1484, defense 1471
14540%0.0
Blended 2025 rating1448.3
Offseason regression
25% back toward the 1500 league mean
1461.2
Roster / QB adjustment
No offseason adjustment applied.
0.0
TB 2026 starting rating1461

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

The calculation

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

Dallas Cowboys base rating
1489.3
2026 starting Elo, after offseason regression
Tampa Bay Buccaneers base rating
− 1410.4
2026 starting Elo, after offseason regression
Rating edge (home perspective)
+78.9
DAL 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
+105.0
TB is the more banged-up side — see the injury breakdown below
Adjusted Elo difference
+208.9

Win probability

1 / (1 + 10−(208.9 / 400))

76.9% DAL

Model spread

208.9 ÷ 25, rounded to the nearest half point

DAL -8.5

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

64.5%

DAL by 4.0

Injury term

+105.0 Elo

+4.2 pts of spread, home perspective

After injuries

76.9%

DAL by 8.5 · moved 12.4 pts of probability

Tampa Bay Buccaneers

−0.2 pts

  • Christian Rozeboom LBOut−0.10
  • Antoine Winfield Jr. SQuestionable−0.03
  • Luke Goedeke OTQuestionable−0.03
  • Emeka Egbuka WRQuestionable−0.03

Dallas Cowboys

−0.3 pts

  • P.J. Locke SOut−0.10
  • Marist Liufau LBOut−0.10
  • Dee Winters LBQuestionable−0.03
  • Drew Shelton OTQuestionable−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.

1489

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

1410

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

64.5% DAL

Model value

Model spread

DAL -4.0

Elo diff +103.9 · 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.

Tampa Bay Buccaneers
Tampa Bay Buccaneers
#22 of 32 · 8-9 in 2025
2025 final rating
1451.7
Regress 25% toward 1500
+9.5
2026 starting rating
1461.2

2025 Elo trail

Biggest swings

  • L 9–24 at DET−37.6
  • W 23–3 at NO+34.0
  • W 30–19 vs SF+32.8
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

Matchup factors

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

Home field

+25.0 pts

worth 2.7 points of win probability

DAL hosts at AT&T 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.

Tampa Bay Buccaneers

1511

average opponent rating · 5th toughest of 32

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

1476

average opponent rating · 31st toughest of 32

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

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 →