How will the Giants’ 2024 season shake out?

Pro Football Network recently released its NFL Playoff Predictor for the 2024-2025 season. So, being a normal and well-adjusted person, I decided to take a brief break from a couple other longer-term projects I’m woking on and simulate the New York Giants season.

One hundred times.

You know, for science.

Before I get to the data set and what I found, I want to state the methods. First, I didn’t have any input into the simulations beyond selecting the Giants to be the team simulated. I didn’t pick any games and relied on PFN’s algorithm to simulate all 544 games of the 2024-2025 season. Unfortunately, I can’t really speak to HOW their algorithm predicts the outcomes. It’s obviously proprietary and therefore pretty opaque. This is their “How It Works” description:

The Pro Football Network NFL Playoff Machine is updated in near-real time at the conclusion of every NFL game. From there, you can opt to pick every remaining game yourself or only select the games that are of interest to you. Once you make your picks, you can choose to simulate that week only or the rest of the season. PFN’s Playoff Predictor includes a proprietary, state-of-the-art algorithm will simulate and predict the outcomes of the games you have not already selected.

I suspect that they’re using things like strength of schedule, betting odds, and perhaps an aggregate of expected win-loss totals. But there’s no way to be sure.

Second I chose to run the season 100 times for a specific reason. That’s typically the amount of instances where random “noise” starts to get minimized and data falls into line. I would have preferred to run the simulation 500 or 1,000 times to really minimize outliers and get close to a 95 or 99 precent confidence interval. But since I had to reset and re-run the simulation manually every time, I felt like 100 times was enough.

While I wasn’t able to run the simulation enough to get a data set suitable for an academic paper, a pretty clear trend emerged. In fact, I was pretty surprised at how neat of a Gaussian (bell curve) the data formed.

The Data

The Giants’ record

As you can see, the most common outcome for the Giants was a 4-13 record (21 instances). Their average record of was 4.77-12.23 across 100 simulations. We’ll just say that their average record was a 5-12 season.

That’s slightly interesting, because based on this data set, a range of 4-13 to 6-11 seems to be the most likely outcomes. However, the 5-12 “average” was the least common of those three outcomes. We could have seen the those 4-13 and 6-11 outcomes regress toward the mean if the simulation was run more times. But … I already didn’t do that.

Generally, the results suggest that the Giants are expected to be poor, but unlikely to have truly catastrophic outcomes. While there were more simulations that ended with 3-14 (13) seasons than 7-10 (9) or 8-9 (7) records, there were more of the less-bad outcomes.

So there’s that.

There were a couple big outliers on either end of the bell curve for the Giants. The first came on the 12th simulation, in which the Giants finished with a 9-8 record (one of two such seasons). That season they squeaked into the playoffs as the seventh seed on a tiebreaker. However, they were quickly shown the door by the second seed San Francisco 49ers.

The second was a nightmare 1-16 season which came on the 23rd simulation. I can only assume the Giants were beset by injuries, bad luck, and several of their opponents were stronger than expected.

PFN’s prediction machine also includes draft position, so let’s see how that shook out for the Giants.

Draft position

Where the final record charts out a pretty clean normal distribution, the Giants’ draft position is pretty wild. Given their most common records, it isn’t surprising that none of the seasons resulted in them drafting 17th or 18th overall, but the hole at 10th overall is weird. The drop-offs at second, sixth, and eighth overall also stand out. But again, those could be the result of tiebreakers and not running the simulation enough times to fully control outliers.

You can see something like a regression curve sketched out if you squint a bit, but there’s a fair amount of noise here. I suspect that it’s likely due to the role of tiebreakers in determining draft position, but I can’t be sure.

The major takeaway is that PFN currently expects the Giants to be drafting highly, which is more apparent when we view the results as a whole.

More than two-thirds (69 percent) of the simulations had the Giants finishing with a Top-6 pick.

Surprisingly, the most common result was for the Giants to wind up with the first pick in the draft. They got the first pick 21 times, despite having three or fewer wins 18 times. That’s nearly as often as they got the third or fourth pick combined (25 times). Meanwhile, the Giants only finished with a pick outside of the Top 10 (well, Top 9 in this case) in 11 out of 100 simulations.

There were several interesting aspects to the draft slots awarded by the prediction machine. The biggest is how often relatively strong records resulted in high draft picks — or perhaps the prediction machine was loath to give truly bad records. There were relatively few 1-16 or 2-15 records in any of the simulations, and quite a few 4-13, 5-12, and 6-11 records every “year”.

We’re obviously a long way away from the 2025 NFL Draft, though Draft Season never truly ends for NFL teams themselves. Right now, teams’ BLESTO scouts are hard at work getting preseason reports ready to guild college scouts through the regular season.

If these simulations hold true (and things could, or will, change a lot by January), we might want to keep an eye on the prospects projected to be at the top of their respective position groups.

Superlatives

“Worst Bad Season”
This is obviously their 1-16 season. A year like that would almost certainly result in wholesale changes in the roster, coaching staff, and front office. Even if it was a true nightmare season like 2017 where everything that could go wrong did go wrong, John Mara wouldn’t stand idly by and say “we’ll get ‘em next year.”

“Best Bad Season”
This one came on the fourth simulation. That year the Giants finished with a 5-12 record, but still managed to come away with the first overall pick. That’s not a good year by any stretch of the imagination, however a 5-12 record is defensible and there could be enough good to come out to give hope for 2025. It’s extraordinarily unlikely that a five-win team would get the 1st overall pick without trading for it, so we can chalk this up to being a lucky break.

“Worst Good Season”
This one is up for debate, not the least reason is that the Giants only finished with a winning record twice.

The most disappointing year would probably be the fifth simulation, which ended with an 8-9 season (one of seven such seasons) and the Giants getting the 16th overall pick. An 8-9 season isn’t a particularly “good” outcome on its own, and the resulting draft pick would be a bit tough.

There would likely be issues with the team that need to be resolved to get off the “rebuilding” hamster wheel and into the “building” phase. However, if the Giants need to get a premium position (likely quarterback, offensive (right) tackle, or cornerback) they’d probably have to trade up to do so.

“Best Good Season”
The 9-8 season that culminated in the playoffs could be great.

At least, if the Giants truly took steps forward and didn’t just back into the postseason.

On offense, that would mean something like Evan Neal and John Michael Schmitz developing while Malik Nabers unlocked the passing attack. On defense, it could look like Kayvon Tibodeaux, Brian Burns, and Dexter Lawrence becoming the core of an elite line, or the young players in the secondary exceeding expectations.

Final Thoughts

This, obviously, doesn’t mean much of anything. It’s really just a representation of how the NFL media (and probably betting public) at large view the Giants in the context of the rest of the NFL.

Tony recently took his own stab at predicting the Giants’ 2024 season and had them finishing with an 8-9 record.

We can look at the results of all these simulations and conclude that the Giants aren’t being respected. Personally, my view is that they still need to earn the right to be respected given the way the last decade has gone.

There’s also a lot we don’t know about the NFL in general for 2024 and the Giants in particular. There are going to be a lot of rookie quarterbacks this year. Some may have “C.J. Stroud” seasons, while others may need three years to find their footing, and others will indeed be over-drafted busts.

There’s no way to tell yet and we won’t know for a while yet.

There has been plenty of coaching turnover all over the league, and the NFL is constantly changing and evolving. Even within the NFC East, the Washington Commanders could look remarkably different from previous years, while the Eagles and Cowboys will have new schemes and wrinkles thanks to new coordinators.

As for the Giants themselves, they have almost as many moving parts as the Commanders. Joe Schoen, Brian Daboll, Mike Kafka, and Daniel Jones remain, but there’s questions to be answered all over the team.

• Will the Giants hold an open quarterback competition after pursuing Drake Maye in the 2024 NFL Draft?
• If Jones is the starter, how will he play coming back from a torn ACL?
• Will the Giants alter their scheme to restrict his opportunities to run, or will he still have the green light on every play?
• How will the additions of Jon Runyan Jr. and Jermaine Eluemunor impact the offensive line, and how will John Michael Schmitz and Evan Neal develop under Carmen Bricillo?
• How will the offense as a whole change with the shift from Saquon Barkley to Malik Nabers?
• What will the defense look like under Shane Bowen after being built for Wink Martindale?
• How will the Giants’ very young secondary gel?

Right now, the Giants are (currently) predicted to have the sixth hardest schedule in the NFL. And given how the Giants have performed lately, as well as how much we don’t know (for better or worse), it makes sense to be conservative with predictions.

We’ll find out soon enough whether the Giants will exceed the expectations at large.