Team Intelligence · NFC East · 2026 preseason

The Giants Have More Interesting Players Than Available Fantasy Points

The model forecasts a bottom-10 scoring offense — 18.7 points a game, 31st — with its best fantasy real estate at quarterback (29th), and the market has it priced about right — the two disagree by 4 places, inside the bar this series sets before calling anything mispriced. Comparable offenses have supported 1.5 fantasy starters.

ADY
Auto Draft Years
17 August 2026 · 9 min read
18.7
proj points/game (31st)
1.5
expected fantasy starters
QB 29th
relative strength
+4
market vs model, in places

The short version

  • The Giants went 4–13 in 2025, but their offense improved to 22.4 points per game.
  • Jaxson Dart showed real fantasy upside: 15 passing TDs, 487 rushing yards and nine rushing TDs.
  • Nabers' ACL tear and Skattebo's ankle injury made the offensive improvement harder to evaluate cleanly.
  • John Harbaugh and a revamped staff have built an offense that appears likely to emphasize the run.
  • AutoDraftYears nevertheless projects only 18.7 PPG, 31st in the NFL, with about 1.5 fantasy starters based on historical comps.
  • The model ranks the Giants' roster 7th while the market has it 20th — a rare team-level gap in their favour — and still fades the individual pieces.
  • Nabers, Dart and Likely remain model fades at current prices.
  • Skattebo and Tracy need a refreshed look after today's Najee Harris signing.
  • Don't evaluate every Giant independently. Eventually all the breakout cases have to fit inside the same offense.

For approximately five minutes last season, the New York Giants appeared to have found something.

Jaxson Dart looked like a quarterback.

Cam Skattebo looked like he had been created in a laboratory where scientists were attempting to make a running back entirely out of spite.

The offense was scoring again.

There was hope.

Naturally, Malik Nabers tore his ACL during Dart's first NFL start. Skattebo suffered a season-ending ankle injury four weeks later. Brian Daboll was fired in November. The Giants finished 4–13.

Being a Giants fan remains an unusually elaborate loyalty program.

But here's the important part for fantasy:

The offense actually got better in 2025.

And AutoDraftYears thinks it is about to get substantially worse.

That is the real question entering 2026:

Was last year's offensive improvement the beginning of something, or just one strange year before another Giants relapse?

2025: Bad team, surprisingly functional offense

The Giants finished 4–13, last in the NFC East.

That part was familiar.

The offense was not.

New York scored 381 points, or 22.4 per game, 17th in the NFL. A year earlier, the Giants had averaged only 16.1.

Going from 16.1 to 22.4 doesn't turn MetLife Stadium into Greatest Show on Turf East.

It does qualify as evidence of life.

And most of the optimism arrived with Dart.

The rookie eventually started 12 games and finished with 2,272 passing yards, 15 passing touchdowns and only five interceptions. More importantly for fantasy managers, he added 487 rushing yards and nine rushing touchdowns.

There it is.

The phrase capable of making fantasy managers temporarily lose access to the part of the brain responsible for price sensitivity:

rushing quarterback.

Dart's first start came in Week 4 against the Chargers. The Giants won 21–18.

It should have been the happiest day of their season.

Instead, Nabers tore his ACL in the second quarter while attempting to catch a deep ball from Dart. He finished 2025 with just 18 catches for 271 yards and two touchdowns in four games.

The Giants then discovered Skattebo.

Before his rookie season ended with a dislocated ankle against Philadelphia, he had rushed for 410 yards and five touchdowns and caught 24 passes for another 207 yards and two scores.

So the season became this odd combination of legitimate progress and falling furniture.

The Giants found their young quarterback.

They found an interesting running back.

The offense became watchable.

They also lost nine consecutive games during the second half of the season, fired Daboll, and somehow arrived at January with the fifth pick in the draft. They at least finished with consecutive 34-point wins over Las Vegas and Dallas, because apparently optimism needed one final opportunity to get itself hurt.

New York Giants: scoring, pass rate and volume, 2021–2026
Solid line is points per game against the left axis; dashed lines are pass rate (right axis) and snaps from scrimmage.
The 2026 point on each line is the model's forecast, not an actual.

And then they changed basically everything

New York hired John Harbaugh in January after his 18-year run in Baltimore.

The Giants then built an offensive staff featuring Matt Nagy, Brian Callahan and Greg Roman, signed former Ravens tight end Isaiah Likely and fullback Patrick Ricard, and used the No. 10 pick on offensive lineman Francis Mauigoa.

This does not exactly scream:

Throw 48 times and see what happens.

Giants.com's own offseason analysis has repeatedly suggested the new offense will emphasize the running game, with Roman's influence, Ricard's arrival and Skattebo's style all pointing that direction.

Which makes what AutoDraftYears sees next particularly interesting.

The model does not believe in the progress

Here is 2025 versus the 2026 forecast:

Metric20252026 Model
Points/game22.418.7
Plays/game61.059.8
Pass rate50.7%57.5%
Red-zone trips/game3.52.6
2025 to 2026
Where the forecast moves
Percentage change against last season's actuals.
Bars are the forecast's own movement; the roster changes above are what the model is responding to.

AutoDraftYears projects New York 31st in scoring.

Its positional environments rank:

  • QB: 29th
  • RB: 30th
  • WR: 30th
  • TE: 30th
Position environment
New York Giants 2026 grades by position
Bars are inverted league rank, so taller is better. Green is top-10, red is bottom-10.
An environment grade is a thumb on the scale for a close call, not a ranking of the players in it.
Offensive pie against opportunity concentration
New York Giants — small pie, concentrated
Horizontal: how many fantasy points this offense has to give out. Vertical: how tightly its projected points sit on its top two skill players.
Small pieconcentratedLarge pieconcentratedSmall piedistributedLarge piedistributedNYG
67% of this offense's projected skill points sit on its top two players, against a league median of 63%. Worth being precise about what this axis does: across 320 historical team-seasons concentration has almost no relationship with how many fantasy starters an offense produces (r = −0.07). The size of the pie decides how many; concentration only decides who.

The 30 historical offenses most similar to this forecast produced only 1.5 fantasy starters per season on average. The bear/base/bull outcome was basically one/two/two starters.

1.5
expected fantasy starters
Bear1
Base2
Bull2

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.

That is the part I care about.

Because fantasy managers rarely draft the Giants offense.

We draft Malik Nabers.

Then Jaxson Dart looks fun.

Then Skattebo falls half a round.

Then Isaiah Likely is sitting there.

Then Tyrone Tracy becomes interesting late.

Suddenly we have constructed the 2007 Patriots out of a team our model expects to score 18.7 points per game.

Somebody eventually has to account for the touchdowns.

One number actually likes the Giants

Here's the wrinkle.

Convert every NFL roster into expected fantasy value and the market puts New York 20th.

AutoDraftYears puts them 7th.

Thirteen places, which clears the eight the model needs before it will call a roster mispriced at all.

So at the team level this is one of the larger disagreements in the league, and it lands in the Giants' favor.

Then you open the board and the model wants approximately none of it.

Nabers: fade.

Dart: fade.

Likely: fade.

That isn't a contradiction. It's this entire page compressed into one paragraph.

A roster can hold real value in aggregate and still be priced badly one player at a time.

The Giants have the players.

The market has already charged for each of them.

And the offense underneath still only supports about 1.5 fantasy starters.

Interesting collection.

Inconvenient prices.

Malik Nabers is where this gets uncomfortable

The current model snapshot has:

PlayerMarketModelAdjusted EdgeCall
Malik NabersWR13WR49-32Fade
Cam SkatteboRB19RB19-2Fair
Jaxson DartQB12QB21-12Fade
Isaiah LikelyTE12TE28-18Fade
Tyrone TracyRB47RB27+8Fair

Nabers is the hardest one.

His role score is 78/100. His risk grade is low. And as of August 17, he had returned to team drills and was catching passes during competitive periods as he works back from the ACL injury.

So the model isn't really making an injury argument.

It is making a price plus environment argument.

The market wants WR13.

The model sees WR49 inside its 30th-ranked receiver environment.

Could Nabers ignore the offense and command 150 targets?

Absolutely.

But WR13 prices require more than "he's talented enough to survive this."

You're paying for the survival in advance.

Dart is exciting. QB12 already knows that.

Dart's rushing isn't theoretical.

We watched him run for 487 yards and nine touchdowns as a rookie.

That gives him exactly the kind of fantasy cheat code capable of making a mediocre passing environment irrelevant.

The problem is that the market has noticed.

He's already QB12.

AutoDraftYears has him QB21, and similar historical offenses produced a top-12 quarterback only 7% of the time.

I like Dart.

I just like him more when I'm not required to pay for the Year 2 breakout before Year 2 happens.

Isaiah Likely may be the best test of the model

Likely is TE12 in the market and TE28 in AutoDraftYears.

That is a substantial fade.

But this one deserves nuance.

The Giants did not accidentally acquire Likely. They signed him immediately in free agency, reunited him with Harbaugh, and training-camp reporting has suggested the tight ends could be a major part of the passing game.

That's the bull case.

The problem?

TE12 is already charging admission to see it.

If Likely were TE20, I'd be much more interested in finding out how prominently Nagy and Roman plan to use him.

At TE12, we're paying for the answer before the exam.

The running backs need one fresh model run

Skattebo had returned from his ankle injury and played in the preseason opener, carrying four times for 19 yards.

The model snapshot has him almost perfectly priced at RB19 and Tracy as an interesting-but-not-actionable value at RB47 versus model RB27.

But there is now a new variable.

On August 18, the Giants signed Najee Harris.

That doesn't automatically destroy either player's fantasy value.

It does mean I would rerun the workload assumptions before treating the current RB rankings as final.

Fantasy football changes quickly.

Occasionally it has the courtesy to change while you're literally writing the article.

PlayerADPMarketModelEdgePPGRoleRiskCall
Malik NabersWR29WR12WR48-321178LowFADE
Cam SkatteboRB41RB19RB18-21574HighFAIR PRICE
Jaxson DartQB101QB12QB21-131761LowFADE
Isaiah LikelyTE119TE12TE28-17365LowFADE
Tyrone TracyRB133RB45RB27+91057LowFAIR PRICE
Greg DulcichTE196TE26TE71—565HighTHIN MARKET

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.

Model against market
Disagreement, in position places
Bars are the de-drifted edge — the same number the calls in the table are made from.

What should fantasy managers do?

The Giants aren't a team I want to avoid entirely.

They're a team where I want to stop granting every player his own separate optimistic future.

Dart can break out.

Nabers can overcome the environment.

Skattebo can command the backfield.

Likely can become a featured target.

All of those statements are individually reasonable.

The problem starts when we assume all four happen together.

AutoDraftYears sees an offense producing 18.7 points per game and historical teams like it supporting around 1.5 fantasy starters.

So make New York beat you on price.

Don't pay WR13 because Nabers is too talented to fail.

Don't pay QB12 because Dart has rushing upside.

Don't pay TE12 because Likely finally has opportunity.

Those stories may all be true.

They just have to share one football.

NO BUY
Nobody clears the bar
The closest is Tyrone Tracy at +9 position places, short of the threshold. Forcing a buy here would be the template writing, not the model.
FAIR PRICE
Cam Skattebo
Cam Skattebo is priced at pick 41 (RB19); the model has him RB18. What fired: the model and the market land within a few position places of each other, a 30th-ranked RB environment behind him and a high risk grade.
FADE
Malik Nabers
Malik Nabers is priced at pick 29 (WR12); the model has him WR48. What fired: the market pays for 32 position places more than the model gives him and a 30th-ranked WR environment behind him. Cutting against it: a projected role scoring 78 of 100 and a low risk grade.

What I'm watching in September

Two numbers.

Red-zone trips: 3.5 last year versus a model forecast of 2.6.

And pass rate: 50.7% last year versus the model's 57.5%, despite an offseason that appears designed to emphasize the run.

If the Giants are generating red-zone trips closer to 2025 levels, the model's 18.7-point forecast may be too pessimistic.

If the new Harbaugh offense is also more efficient than expected?

Then I'll happily admit the spreadsheet ruined a perfectly good Giants breakout party for no reason.

Until then, I'm not drafting four separate success stories and pretending they don't all live at the same address.

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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.