NFL statistics are… weird.
Unlike a sport such as baseball, where most of what happens is definitive and lacks subjectivity, there is a ton of subjectivity on a football field.
Was that a drop?
Was that a pressure by the edge rusher?
Was that an allowed pressure by the guard?
Was that a “turnover-worthy throw” by the QB?
Should that 30-yard touchdown catch be blamed on the corner or the safety?
Two different people can offer two different answers to each of those questions, whereas on the diamond, an RBI double is an RBI double.
This is before getting into the numerous variables that can affect our perception of a player’s performance on a given play.
What did the scheme ask of him, and can we even know the answer without being in the locker room? How was he affected by the players around him? Should there have been a penalty called? Did he actually do anything noteworthy, or did the scheme cook up an easy play for him?
The list goes on forever. In baseball, the result itself pretty much tells the whole story about the player’s performance—little context is necessary.
Quantifying what happens on a football field is extremely difficult compared to other sports, and this is why the NFL remains far behind when it comes to analytics. More and more metrics continue to emerge each year, but with each new revelation comes more flaws that only further complicate the questions that the metrics are intended to answer. Ultimately, there may never be football metrics that could capture the entire picture any better than the good old “eye test”.
Then again, relying on the eye test is susceptible to its own issues. No film junkie has the time to watch every player and every play in the league to truly compare them all; that’s where data comes in, because the data can evaluate every snap from every player in the NFL. Plus, humans are prone to remembering only the greatest peaks and valleys of a player, whereas the data will give every play, even those that make up the boring middle-80%, the equal weight that it deserves.
The eye test may also cause people to lose sight of a player’s actual impact on winning in favor of fundamentals or eye-catching traits that might not have actually translated to much tangible impact. The value of data is that we can compare every player in the NFL on the same plane in metrics that aim to capture the one thing that matters most: how much are you helping your team win?
The obvious limitations of merely eye-testing the entire league have prompted teams to continue pushing the analytics wave. But since the analytics wave remains limited by the sport’s inherent subjectivity, we are still seeing the widespread promotion of highly flawed metrics.
So, what does all of this have to do with the New York Jets and Joseph Ossai?
Joseph Ossai’s two-faced metrics
This offseason, the Jets signed Ossai to a three-year, $34.5 million deal. His $11.5 million salary ranks 37th among edge rushers.
Essentially, New York is paying the former Cincinnati Bengals third-round pick as if they expect him to be a middle-of-the-pack starting edge rusher.
Ossai, 25, took a while to become a core piece of the Bengals’ defensive line rotation. He only played 32% of the defensive snaps as a rookie and dropped to 20% in his second season. But he jumped to 51% in 2024, and in 2025, he hit a career-high 67%, finally being utilized as a primary starter.
So, we know that Ossai was used as a starter last year. But did he play like one?
Check different analytics sites, and you will get different answers.
If you ask Pro Football Focus, Ossai was below-average in terms of pass-rush efficiency. According to PFF, Ossai’s pressure rate (percentage of pass-rush snaps in which he pressured the quarterback) was 11.5%, placing 51st among the 91 edge rushers with at least 200 pass-rush snaps. This ranking does not match up with the 37th-ranked salary New York gave him.
But if you ask NFL Pro, Ossai performed almost precisely to the level that New York paid him. In NFL Pro’s system, Ossai’s pressure rate was 13.2%, which placed 38th out of 91 qualifiers. That’s an above-average mark and nearly identical to his No. 37 ranking in salary.
The difference is jarring. One site says the Jets are overpaying Ossai by a significant margin. The other says he is getting paid precisely as much as he should be.
What gives? How could two sites spit out a 13-spot difference in Ossai’s pressure-rate ranking?
Well, it comes down to the fact that PFF and NFL Pro are tracking pressures differently.
This is where subjectivity comes in. We’re not talking about singles and stolen bases here. Two major analytics sites are using completely different processes to evaluate the same metric.
At PFF, pressures are charted manually by film analysts. The site employs hundreds of analysts who review and grade game film each week. So, it’s up to human interpretation whether a given rep should be constituted as a “pressure” generated by the defender.
At NFL Pro, pressures are charted using a GPS tracking system. Essentially, a computer tracks spatial coordinates, speed, and blocking matchups in real time to estimate whether a defender beat their blocker to create pressure on the quarterback.
Both styles have their benefits and flaws.
The benefit of PFF’s approach is that humans can identify subtle pieces of context that a tracking system might miss.
Maybe a defensive tackle collapsed the pocket and forced the QB to step up, even if they did not actually get past their blocker and reach the QB.
Maybe an edge rusher was chipped and faced a long-developing, seven-step drop, which meant the rusher took about 3 seconds to get home instead of the, let’s say 2.5 seconds that the tracking system might prefer for the play to constitute a “pressure”, but given context, it was still a very good play if you actually watched it.
There could be plenty of examples like this, where a human does or does not give credit for a pressure because of visual context that would be missed by just looking at dots on a screen.
The downside of PFF’s approach is that relying solely on humans only further increases the stat’s subjective nature. While PFF likely has a universal set of rules that analysts are supposed to follow to define what constitutes a pressure, you could still get two different opinions from two analysts on the same play. The sport is far too complex for the gray area to ever be truly eliminated.
The benefit of NFL Pro’s approach is that the set of rules is more clearly defined. The system likely has an explicit definition of what a pressure is: something like “defender gets past his blocker and within X yards of the QB in under Y seconds.” This eliminates a lot of the subjectivity and offers a consistent definition of what is being tracked.
The problem with that is we lose out on the discernment that human analysis could provide. Some pressures being credited by NFL Pro might not actually deserve to be credited as pressures, while NFL Pro might miss out on crediting pressures that deserve to be credited as such because of the way they affected the QB, even if they technically did not get within X yards in Y seconds.
So, which system is better?
That answer, just like much of what happens on a football field, is subjective. Some people don’t trust PFF and would rather go with a consistent, computer-tracked system. Some people would prefer to side with eye-test-based tracking instead of GPS-based tracking.
Personally, I lean toward PFF for pressures. From comparing my film takeaways with both PFF’s and NFL Pro’s (previously Next Gen Stats) pressure numbers, I have found PFF to be more accurate.
The main flaw with NFL Pro is that it credits too many extra pressures that don’t really deserve to be credited as such. League-wide, NFL Pro tallies more pressures than PFF, which means they are tacking on pressures in situations where PFF’s human analysts don’t see it the same way.
I tend to agree. I think the rules of the GPS tracking system cause it to give out some pressures on plays where the player didn’t actually affect the QB very much, even if they met certain rigid criteria. Human analysis allows us to contextualize in ways that would be missed if we simply defined pressures by the distance between dots on a screen.
NFL Pro credited Ossai with 47 pressures in 2025, while PFF gave him 43. Those four pressures might not seem like much, but it’s enough to explain the 1.7% difference in his pressure rate, which made up a 13-spot difference in his ranking.
My opinion is that PFF’s pressure numbers tend to be more accurate, so I would lean toward Ossai’s 51/91 ranking in PFF’s pressure rate being more reliable than his 38/91 ranking at NFL Pro. Some folks, though, may have read this article and came away thinking that NFL Pro’s methodology is clearly better. That’s completely reasonable, and it perfectly encapsulates why NFL analytics remain such a subjective topic.
Perhaps it would be fair to settle for a middle ground between the two sites. That would put Ossai’s median pressure rate ranking at about 45th of 91, which is smack-dab in the middle.
Considering that Ossai’s run defense is viewed as above-average (he ranked 24th out of 91 qualifiers with a 70.6 run defense grade at PFF), his league-average pressure rate isn’t too shabby. Above-average run defense and league-average pass rushing would be enough to justify Ossai’s 37th-ranked $11.5 million salary. That’s baseline play for a starting edge rusher, which is what the Jets are paying for.
If Ossai truly is a 38th-ranked pressure producer, though, he would be a slight bargain on his salary when coupled with his top-25 run defense. Meanwhile, if he is actually a 51st-ranked pressure producer, his salary might start looking just a tad expensive for what he brings to the table.
Therein lies the complexity posed by the dichotomy within the NFL’s analytics space. Extracting definitive conclusions on a player’s worth is extremely difficult in a sport that is subjective enough to the point that two different analytics sites can yield a 13-spot discrepancy in their quantification of how good a starting edge rusher is at pass rushing.
Maybe the best way to choose which site to believe is by answering whether you believe the glass is half-full or half-empty. Glass-half-full Jets fans will cite Ossai’s NFL Pro ranking in pressure rate. Glass-half-empty Jets fans will cite his PFF ranking in pressure rate.
That’s all well and good… until I tell you that PFF thought Will McDonald ranked much better as a pass rusher in 2025 than NFL Pro did.
No matter—if the glass is half full, NFL Pro is correct for Ossai, while PFF is correct for McDonald; we can toss aside the negative metrics for each player.
NFL analytics will never cease to be hilarious.
