Fantasy football has trained us to believe identifying a good offense is useful information.
Find points. Draft players attached to points. Feel intelligent.
Green Bay spent much of 2025 demonstrating why this process occasionally needs adult supervision.
The Packers were 9-3-1 and leading the NFC North in December. Then they lost their final four regular-season games, entered the playoffs as the No. 7 seed and blew a 21-3 halftime lead against Chicago in the Wild Card round. Five straight losses. Season over. Please unplug the machine and try again next year.
Now the AutoDraftYears model expects the offense to improve.
Green Bay projects for 25.1 points per game, ninth in the NFL. Every positional environment ranks inside the top 10. Comparable offenses have produced 3.0 fantasy starters.
This sounds like exactly the sort of offense we should attack.
Except the fantasy market already ranks Green Bay as the 14th-most valuable roster in football.
The model ranks it 27th.
So the interesting question isn't whether Green Bay will be good.
It's this:
Can a good offense still be overpriced almost everywhere?
Apparently, yes.
2025 was good quarterback play surrounded by chaos
Green Bay's final scoring numbers weren't especially exciting. In the AutoDraftYears dataset, the Packers finished at 23.2 points per game, down from 26.1 in 2024.
But Jordan Love was hardly the problem.
Love finished with a 101.2 passer rating and the best touchdown-to-interception ratio of his career. Packers GM Brian Gutekunst called it his best statistical season as a passer.
The strange part was how little Green Bay leaned into it.
The Packers threw on just 50.9% of their snaps in the AutoDraftYears data.
That's the important number.
Because the passing game was also repeatedly asked to function while somebody was being escorted to the medical tent.
Jayden Reed broke his collarbone in Week 2 and ultimately missed 10 games. Christian Watson spent the first half of the season recovering from the ACL tear he suffered in January.
Then Tucker Kraft started looking like he might be the best player in the passing game.
Through eight games, Kraft had 32 catches, 489 yards and six touchdowns. He led Green Bay in all three categories.
Then he tore his ACL on Nov. 2. Season over.
Watson returned just in time to inherit the explosives department.
After coming back in late October, he finished with 35 catches for 611 yards and six touchdowns in 10 games, averaging 17.5 yards per reception.
Meanwhile, first-round rookie Matthew Golden never really established himself. He dealt with shoulder and wrist injuries, caught 29 passes for 361 yards without a regular-season touchdown, then finally flashed with 84 yards and a score in the playoff loss.
This was less a receiving corps and more a shift schedule.
Kraft available. Watson unavailable.
Watson returns. Kraft disappears.
Reed leaves. Golden gets hurt.
Everybody please check the group calendar before coming to work.
That context matters because the model isn't asking Green Bay to invent offensive talent in 2026.
It's mostly asking the Packers to put a healthier version of the offense in better situations.
The model is really betting on more passing
Green Bay's scoring history:
| Season | Points/Game |
|---|---|
| 2021 | 25.6 |
| 2022 | 21.8 |
| 2023 | 23.8 |
| 2024 | 26.1 |
| 2025 | 23.2 |
| 2026 forecast | 25.1 |
There isn't some enormous long-term growth trend hiding here.
The bigger change is philosophical.
Green Bay's pass rate fell from 57.2% in 2021 to 48.1% in 2024 before climbing slightly to 50.9% last season.
The model projects 55.7% in 2026.
That's a 4.8 percentage-point increase.
Snaps rise modestly from 58.3 to 59.2 per game.
So the forecast isn't asking Green Bay to become the 2013 Broncos.
It is essentially saying: You have Jordan Love. Perhaps let Jordan Love throw the football.
Revolutionary stuff.
The personnel is also less crowded. Romeo Doubs left in free agency and Dontayvion Wicks was traded, leaving Watson, Reed and Golden as the clear top three receivers.
Every 2026 positional environment grades well:
- QB: 8th
- RB: 8th
- WR: 9th
- TE: 6th
Comparable offenses agree.
The 30 closest historical team matches to Green Bay's 2026 profile produced:
| Outcome | Hit Rate |
|---|---|
| Top-12 QB | 57% |
| Two Top-24 RBs | 73% |
| Three Top-36 WRs | 83% |
| Top-12 TE | 40% |
Overall expectation: 3.0 fantasy starters.
The average offense across 320 historical team-seasons produced 2.6.
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.
So I am not bearish on Green Bay.
I'm bearish on what we're being charged for admission.
The market already bought the comeback
Here is the problem:
| Player | ADP | Market | Model | Adj. Edge | Role | Risk |
|---|---|---|---|---|---|---|
| Josh Jacobs | 38 | RB17 | RB14 | 0 | 83 | Medium |
| Christian Watson | 63 | WR28 | WR48 | -24 | 67 | High |
| Tucker Kraft | 76 | TE6 | TE1 | +5 | 77 | Low |
| Jayden Reed | 111 | WR49 | WR38 | +7 | 60 | Low |
| Matthew Golden | 125 | WR54 | WR64 | -14 | 63 | Low |
| Jordan Love | 127 | QB20 | QB25 | -8 | 65 | Medium |
| Player | ADP | Market | Model | Edge | PPG | Role | Risk | Call |
|---|---|---|---|---|---|---|---|---|
| Josh JacobsRB | 39 | RB17 | RB14 | 0 | 13 | 83 | Medium | FAIR PRICE |
| Christian WatsonWR | 59 | WR28 | WR47 | -22 | 11 | 67 | High | FADE |
| Tucker KraftTE | 74 | TE6 | TE1 | +5 | 15 | 77 | Low | BUY |
| Jayden ReedWR | 108 | WR46 | WR39 | +4 | 6 | 60 | Low | FAIR PRICE |
| Matthew GoldenWR | 116 | WR50 | WR63 | -16 | 5 | 63 | Low | FADE |
| Jordan LoveQB | 131 | QB20 | QB25 | -9 | 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 5, RB 15, WR 11, TE 5 places), set at two-thirds of that position's own spread.
The market ranks Green Bay's fantasy roster 14th.
The model ranks it 27th.
That's a 13-place disagreement, past the eight the model needs before it will call a roster mispriced — and it lands against the Packers.
The neighborhood is lovely.
The Zillow estimates have simply become aggressive.
Tucker Kraft is the exception
Kraft is TE6 in the market and TE1 in the model.
That one makes sense.
Before the ACL injury, Kraft wasn't producing theoretical breakout statistics. He was producing actual ones: 489 yards and six touchdowns in eight games.
The model gives him a 77 role score, projects 15 PPG and puts him in the league's sixth-best tight end environment.
There is, however, an obvious asterisk the spreadsheet cannot politely slide under the couch.
He tore his ACL in November.
The encouraging news is that Kraft has progressed far enough to return to team drills this August; on Aug. 16, he participated in 11-on-11 work for the first time this camp and immediately caught a touchdown.
So I'm willing to buy the upside.
I just wouldn't interpret a model designation of Low risk as meaning his knee has been granted diplomatic immunity.
Kraft is my favorite Packers target at cost.
Christian Watson is where optimism gets expensive
Watson is harder.
His 2025 return was legitimately impressive. He averaged 17.5 yards per catch after coming back from the ACL and again looked like Green Bay's most dangerous vertical weapon.
That is exactly why WR28 bothers me.
The market already knows the fun part.
AutoDraftYears has Watson at WR48, leaving a -24 adjusted positional edge even after accounting for normal disagreement around his draft range.
His risk grade is High.
Could he smash if Green Bay throws substantially more?
Absolutely.
But at WR28, you're no longer buying that possibility cheaply. You're paying the bartender before you've seen the cocktail.
I'd rather let someone else make that transaction.
Jacobs is fine. Golden and Love can wait.
Josh Jacobs might be the least dramatic player on the roster.
Market: RB17.
Model: RB14.
Role: 83.
Green Bay RB environment: 8th.
He rushed for 929 yards and 13 touchdowns in 15 games last season, a step down from his 1,329-yard Packers debut but still enough touchdown equity to keep the fantasy case intact.
Draft him around cost.
No manifesto required.
Golden is more tempting emotionally than statistically.
Green Bay just cleared targets ahead of him. He's a former first-round pick. His best professional game came the last time we saw him.
This is normally where August begins whispering terrible financial advice into our ear.
The model still has him WR64 versus WR54 in the market, a -14 adjusted edge.
I want him cheaper.
Jordan Love is similar. A higher pass rate could help, but the model still sees QB25 versus a QB20 market price.
A rising tide can lift boats.
It does not mean you need to purchase every boat.
What I would actually do
Green Bay should be a better fantasy environment in 2026.
The model projects 25.1 points per game, a significant shift back toward passing and roughly three fantasy starters.
I buy that general story.
I just don't think Green Bay's offensive improvement is a secret.
Draft Tucker Kraft.
Take Josh Jacobs around market price.
Jayden Reed is interesting if his price stays depressed.
I would want discounts on Christian Watson, Matthew Golden and Jordan Love.
And the number I'm watching in September is simple:
Pass rate.
If Green Bay really jumps from 50.9% toward the model's 55.7% expectation, there will be enough passing volume to make this crowded fantasy thesis work.
If Matt LaFleur returns to last year's run-heavy approach, the market has a problem.
Because fantasy managers are already paying for the offensive rebound.
Green Bay doesn't need to disappoint for those prices to be wrong.
It merely needs to be good in a way everyone already expected.
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.