Green Bay Packers scored 23.2 points a game in 2025, 14th in the league. The model forecasts 25.1 for 2026, 9th. Every page in this series then asks the same two questions of that forecast — how many fantasy starters does an offense like this actually support, and is the market charging the right price for them — and answers both from the data rather than from the shape of the template. So the question for Green Bay is a pricing question: the model and the market disagree about this whole offense by 21 league places, and someone is wrong.
Who this offense actually is
Over 2021–2025 this offense scored 25.6/21.8/23.8/26.1/23.2 points a game and threw on 57.2/55.3/55.9/48.1/50.9 percent of its snaps. Two separate readings come out of that. Its level: 23.2 in 2025, 0.9 points below its own five-year mean of 24.1. Its trend: a five-year slope of -0.1 points a season, which is flat.
Across the same window it has leaned further into the run (-2 points of pass rate a season). In 2025 it ran 58.3 snaps from scrimmage a game, 20th in the league. That is play volume, not pace: it counts snaps, and snaps are driven as much by first downs, turnovers and game script as by how fast a team chooses to play. Genuine situation-neutral pace is not in this dataset, so this series does not claim it.
What changed, and why
Receiver moves from Romeo Doubs to Christian Watson and quarterback, running back and tight end stay where they were. The model's scoring forecast moves +1.9 points a game against 2025, with pass rate +4.8 points and snaps +0.9 a game. The forecast delta is the result of those changes; the job changes above are the cause.
The roster moves behind it: Romeo Doubs leaves to NE (165 PPR points) and Emanuel Wilson leaves to SEA (94 PPR points).
Coordinator, scheme and offensive-line movement are not in this dataset and are not recorded for this team. They are left blank rather than guessed at.
Where the fantasy points go
For 2026 the model grades this offense QB 8th, RB 8th, WR 9th, TE 6th. Its relative strength is tight end — 6th, a top-10 environment. Its relative weakness is receiver — 9th, a top-10 environment. Note what that does not mean: receiver is this team's relative weakness and still ranks 9th in the league. Relative weakness is not weakness.
What the market believes, and whether it is wrong
Every roster in the league is priced twice: once at the market's ranks and once at the model's, both converted to expected fantasy points a game through the empirical price curve — what a player at that rank has actually returned, 2016–2025. Ranks are not linear in value, so summing them would flatter deep rosters and undersell top-heavy ones; points are.
The claim runs the other way here. Priced at market ranks this roster is the 7th most valuable in the league; the model has it 28th. The market is paying 21 places ahead of the model. This offense is expensive.
The biggest individual disagreements on this roster: Christian Watson (-24), Matthew Golden (-14) and Jordan Love (-8).
What offenses like this one have produced
Take the 2026 forecast — 25.1 points, 55.7% pass rate, 59.2 snaps, 3.7 red-zone trips — and find the 30 most similar offenses among all 320 team-seasons from 2016 to 2025. Closest matches: Green Bay Packers 2023 (23.8 PPG, 2 starters); Minnesota Vikings 2024 (24.5 PPG, 4 starters); Kansas City Chiefs 2024 (23.1 PPG, 3 starters); San Francisco 49ers 2024 (22.9 PPG, 2 starters).
Those offenses produced a top-12 quarterback 57% of the time, two top-24 backs 73%, three top-36 receivers 83%, and a top-12 tight end 40%. That is where the starter count below comes from — it is measured off comparable offenses, not asserted.
Read off the 30 most similar offenses in 2016–2025, not asserted. A starter is a QB1, an RB2, a WR3 or a TE1 — top 12, 24, 36 and 12 at the position. Across all 320 team-seasons the average offense produced 2.6.
The player board
Tucker Kraft on one side, Christian Watson, Matthew Golden and Jordan Love on the other.
| Player | ADP | Market | Model | Edge | PPG | Role | Risk | Call |
|---|---|---|---|---|---|---|---|---|
| Josh JacobsRB | 38 | RB17 | RB14 | 0 | 13 | 83 | Medium | FAIR PRICE |
| Christian WatsonWR | 63 | WR28 | WR48 | -24 | 11 | 67 | High | FADE |
| Tucker KraftTE | 76 | TE6 | TE1 | +5 | 15 | 77 | Low | BUY |
| Jayden ReedWR | 111 | WR49 | WR38 | +7 | 6 | 60 | Low | FAIR PRICE |
| Matthew GoldenWR | 125 | WR54 | WR64 | -14 | 5 | 63 | Low | FADE |
| Jordan LoveQB | 127 | QB20 | QB25 | -8 | 14 | 65 | Medium | FADE |
Market and Model are ranks within the position. Edge is the model's position rank against the market's, after removing the drift that affects every player at that price — so it reads as “the model likes him this many places more than it likes the typical player who costs this much.” A call needs the edge to clear the position's bar (QB 7, RB 13, WR 11, TE 5 places), set at two-thirds of that position's own spread.
The three decisions
What would make this page wrong
- The scoring move doesn't happen. The forecast asks this offense for +1.9 points a game against 2025. If it simply repeats last season, the starter count below falls back toward what a 23.2-point offense supports.
- The pass-run balance doesn't move. The forecast has pass rate going +4.8 points to 55.7%. That shift is doing real work in the tight end grade above.
- The price gap closes before you draft. The 21-place gap is measured against today's board; ADP moves through August.
The one thing to watch in-season
Watch pass rate. The forecast has it at 55.7 against 50.9 last season, and it is the input moving furthest from what this offense actually did. If it holds through the first month, the starter count on this page holds with it. If it snaps back, everything downstream of the forecast — the environment grades, the capacity number, the calls — moves with it.
Sources: Auto Draft Years FF Model workbook — Team Data By Year, Team Stat Ranking, 2026 Team Context; Auto Draft Years 2026 consensus board (16 authoritative market sources); Player outcomes 2016–2025, Pro Football Reference via the project dataset. Team environment grades, forecasts and player model ranks are proprietary. Every figure on this page is generated from the dataset at build time; none is typed in by hand.