Week 1 · Sun, 4:25 PM EDT · FOX
Washington Commanders at Philadelphia Eagles
Lincoln Financial Field, Philadelphia, PA
Market line for comparison: PHI -4.5 · O/U 45.5 (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.
Washington Commanders
| Input | Rating | Weight | Contribution |
|---|---|---|---|
Elo from results 5-12 in 2025, opponent-adjusted | 1448 | 80% | 1158.2 |
Scoring strength 356–451 points (-95.0 differential) → 36.3% expected win rate | 1403 | 5% | 70.1 |
Late-season form same replay with the closing 6 weeks counted double | 1452 | 15% | 217.8 |
Offense / defense split 20.9 PPG scored, 26.5 allowed → offense 1448, defense 1412 | 1360 | 0% | 0.0 |
| Blended 2025 rating | 1446.1 | ||
Offseason regression 25% back toward the 1500 league mean | 1459.6 | ||
Roster / QB adjustment No offseason adjustment applied. | 0.0 | ||
| WSH 2026 starting rating | 1460 | ||
Philadelphia Eagles
| Input | Rating | Weight | Contribution |
|---|---|---|---|
Elo from results 11-6 in 2025, opponent-adjusted | 1502 | 80% | 1201.7 |
Scoring strength 379–325 points (+54.0 differential) → 59.0% expected win rate | 1563 | 5% | 78.2 |
Late-season form same replay with the closing 6 weeks counted double | 1473 | 15% | 220.9 |
Offense / defense split 22.3 PPG scored, 19.1 allowed → offense 1482, defense 1597 | 1579 | 0% | 0.0 |
| Blended 2025 rating | 1500.8 | ||
Offseason regression 25% back toward the 1500 league mean | 1500.6 | ||
Roster / QB adjustment No offseason adjustment applied. | 0.0 | ||
| PHI 2026 starting rating | 1501 | ||
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−(66.0 / 400))
59.4% PHI
Model spread
66.0 ÷ 25, rounded to the nearest half point
PHI -2.5
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
59.4% PHI
Model value
Model spread
PHI -2.5
Elo diff +66.0 · 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
- 1447.8
- Regress 25% toward 1500
- +11.8
- 2026 starting rating
- 1459.6
2025 Elo trail
Biggest swings
- W 27–10 at LAC+48.4
- L 22–44 at DAL−46.9
- W 24–17 at PHI+46.7
- 2025 final rating
- 1502.2
- Regress 25% toward 1500
- −1.5
- 2026 starting rating
- 1500.6
2025 Elo trail
Biggest swings
- L 17–34 at NYG−52.9
- L 17–24 vs WSH−46.7
- L 15–24 vs CHI−35.6
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
PHI hosts at Lincoln Financial Field. Every host gets the same flat 25 points — the model does not rate crowds individually.
2025 head to head
- Week 16: PHI won 29–18 (PHI on the road)
- Week 18: WSH won 24–17 (PHI 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.
1494
average opponent rating · 23rd toughest of 32
- vs above-average teams
- 2-6
- vs below-average teams
- 3-6
1489
average opponent rating · 28th toughest of 32
- vs above-average teams
- 3-3
- vs below-average teams
- 8-3
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.