Week 1 · Sun, 1:00 PM EDT · CBS
Buffalo Bills at Houston Texans
Reliant Stadium, Houston, TX
Market line for comparison: BUF -1.5 · O/U 44.5 (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.
Buffalo Bills
| Input | Rating | Weight | Contribution |
|---|---|---|---|
Elo from results 12-5 in 2025, opponent-adjusted | 1577 | 80% | 1261.8 |
Scoring strength 481–365 points (+116.0 differential) → 65.8% expected win rate | 1614 | 5% | 80.7 |
Late-season form same replay with the closing 6 weeks counted double | 1619 | 15% | 242.8 |
Offense / defense split 28.3 PPG scored, 21.5 allowed → offense 1632, defense 1539 | 1671 | 0% | 0.0 |
| Blended 2025 rating | 1585.4 | ||
Offseason regression 25% back toward the 1500 league mean | 1564.0 | ||
Roster / QB adjustment No offseason adjustment applied. | 0.0 | ||
| BUF 2026 starting rating | 1564 | ||
Houston Texans
| Input | Rating | Weight | Contribution |
|---|---|---|---|
Elo from results 12-5 in 2025, opponent-adjusted | 1608 | 80% | 1286.6 |
Scoring strength 404–295 points (+109.0 differential) → 67.8% expected win rate | 1629 | 5% | 81.5 |
Late-season form same replay with the closing 6 weeks counted double | 1661 | 15% | 249.1 |
Offense / defense split 23.8 PPG scored, 17.4 allowed → offense 1519, defense 1642 | 1660 | 0% | 0.0 |
| Blended 2025 rating | 1617.1 | ||
Offseason regression 25% back toward the 1500 league mean | 1587.8 | ||
Roster / QB adjustment No offseason adjustment applied. | 0.0 | ||
| HOU 2026 starting rating | 1588 | ||
The calculation
Every term the model applies, in order, from both teams' starting ratings to the number on the card.
Win probability
1 / (1 + 10−(48.8 / 400))
57.0% HOU
Model spread
48.8 ÷ 25, rounded to the nearest half point
HOU -2.0
Confidence band
Move the factors yourself
Every term feeds one number: the adjusted Elo difference. Drag any of them and watch the spread and confidence follow.
Drag to see how much a stronger or weaker host changes the call.
The two ratings only matter through their difference.
The tuned value is a flat 25 points for every host.
5 Elo per extra day of rest, capped at 25 either way.
A manual thumb on the scale, in the home team's direction.
Win probability
57.0% HOU
Model value
Model spread
HOU -2.0
Elo diff +48.8 · 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.
- 2025 final rating
- 1577.3
- Regress 25% toward 1500
- −13.3
- 2026 starting rating
- 1564.0
2025 Elo trail
Biggest swings
- L 13–30 at MIA−57.0
- W 40–9 at CAR+55.2
- W 30–10 at NYJ+42.9
- 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 3.6 points of win probability
HOU hosts at Reliant Stadium. Every host gets the same flat 25 points — the model does not rate crowds individually.
2025 head to head
- Week 12: HOU won 23–19 (HOU 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.
1492
average opponent rating · 26th toughest of 32
- vs above-average teams
- 4-4
- vs below-average teams
- 8-1
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
- · Injuries, suspensions and depth-chart changes.
- · 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.