Understanding NFL Next Gen Stats in 2026

If you’ve watched any football over the past few years, you’ve likely noticed the growing presence of Next Gen Stats in NFL broadcasts. Whether through TNF’s Prime Vision, the popular “Catch Probability” highlights, or mysterious stats like “pressure rate” and “air yards,” the NFL’s unique player-tracking engine has created a whole pocket of data for fantasy nerds to mine.

But what are the relevant Next Gen stats, and when and how can we use them to further our fantasy acumen? This article should give you a solid starting point for both questions. And if you have any others, reach out on X (formerly known as Twitter).

Note: If you're interested, you can access and comb through a ton of NGS data yourself on the team's free site or on the NFL Pro data suite!

Next Gen Passing Stats

Air Yards

At the core of much of what Next Gen Stats does with the passing game is “Air Yards,” defined as “the vertical yards on a pass attempt at the moment the ball arrives at its target, in relation to the line of scrimmage.” You may have heard the label “depth of target,” and in layman's terms, air yards are essentially how far “downfield” a pass travels. By any name, it's a metric to separate deep shots from dump-offs, and to delineate everything in between.

To a degree, “intended air yards” (air yards on pass attempts, IAY) and more importantly “completed air yards” (air yards on completions, CAY) correlate well with NFL success and with fantasy points. Quarterbacks who are successfully driving the ball downfield typically score more fantasy points on average than those who lean on the dink-and-dunk. To paint the picture, let's look at the top and bottom of the air yards per attempt standings last year. The leader, in a pure aberration, was J.J. McCarthy, who insisted on throwing the ball deep downfield very ineffectually. Writing him off as an outlier, the next four names in order are Lamar Jackson, Matthew Stafford, Drake Maye, and Trevor Lawrence. Very good company. At the bottom of the AY/A list? Aaron Rodgers, Geno Smith, Tua Tagovailoa, Jared Goff, Kirk Cousins, and Bryce Young. The only QB in that group that cracked the top 20 in fantasy points per game was Jared Goff (QB12).

As Goff demonstrated, quarterbacks with lower air yards benchmarks can still be viable for fantasy (especially if they throw a lot of touchdowns). Brock Purdy and Bo Nix were both decent last year despite below-average AY/A. But as a rule, pushing the ball downfield typically correlates well with more efficient fantasy production, and provides us with upside plays like Stafford and Maye last year.

Completion Percentage Above Expectation

One of the more popular examples of Next Gen Stats I mentioned earlier in the introduction was “Completion Probability” — something you may have seen flashed on NFL Network highlights of particularly wild touchdown passes. One of the most memorable from last year was this one from Dak Prescott to Jalen Tolbert last season, which NGS tagged with a 7.2% completion probability, second-most improbable in their recorded data.

Dak Prescott's 34-yard pass to Jalen Tolbert had a completion probability of 7.2%, the second-most improbable completion in the NGS era.

Tolbert was 0.2 yards from the sideline when the pass arrived.#GBvsDAL | #DallasCowboyspic.twitter.com/d9zMS7P8XR

— Next Gen Stats (@NextGenStats) September 29, 2025

From the data NGS has collected on these factors, they produce an “Expected Completion Percentage” statistic (xCOMP), which can then be used to calculate a QB’s “Completion Percentage Above Expectation.” A passer’s xCOMP is a good indicator of how often they’re making “tough throws” rather than easy ones, and a passer’s completion percentage above expectation is often a good indicator of their accuracy and efficiency on all throws.

As a rule, the best in the “above expectation” business are known for succeeding on the chances they take, while taking fewer of those chances. The worst "below expectation" offenders are mostly guys willing to sling it without the greatest results (looking at you, McCarthy), or in some cases to dink-and-dunkers with such a high xCOMP that their actual completion percentage ends up being lower by necessity.

Most of the time, the best fantasy passers are those with a positive differential above an average or slightly above average xCOMP. This is because quarterbacks with extremely high xCOMPs — like Tua Tagovailoa or recent Aaron Rodgers — often end up being consistent but low-upside “game managers” for fantasy, while QBs with extremely low xCOMPs — like Ward — are usually volatile as passers, with high highs and low lows.

There’s a lot of room for fantasy production through different iterations of these statistics, but it’s helpful to know what they mean for a player’s consistency, upside, and all-around fantasy production.

Time to Throw

Time to Throw is quite simply how many seconds a quarterback takes from snap to throw on each dropback. It can often be as much an indicator of offensive scheme and protection as it is of a QB’s processing speed or willingness to scramble, but it typically involves some combination of all three. Guys like Caleb Williams, Lamar Jackson, and Sam Darnold are consistently "slow," while Tua Tagaviloa, Aaron Rodgers, and Joe Burrow are consistently "quick."

Time to throw doesn’t have the strongest correlation to fantasy points, largely because of how much scrambling QBs tip the scales, but it can offer some insights when combined with additional context. If a passer has a low time to throw and high intended air yards, they’re like a volatile pocket-passer with big upside and a few extra interceptions (Trevor Lawrence). If they have a high time to throw and low intended air yards, they’re probably mobile, struggling to process, and at risk of inflated sack rates (Williams). Typically, lower times to throw are better for QB production if you’re not racking up points on the ground (guys like Burrow win this way). But every once in a while, there’s an exception that combines high time to throw with high intended air yards and finds impressive week-to-week production through big play efficiency — Darnold has been a top example the last couple years between his Minnesota breakout and Seattle Super Bowl run.

Next Gen Rushing Stats

Efficiency

Next Gen Stats’ rushing efficiency metric (EFF) is calculated by measuring the total distance a player travels (in any direction) per rushing yard gained (downfield). At its core, it is a measurement of how “North/South” a runner tends to be. While the number doesn’t correlate that strongly with fantasy points, it does have a strong inverse correlation with yards per carry averages — that is, as the efficiency number gets lower (for more North/South runners), the yards per carry tends to go up.

This correlation is swayed by more volatile “big-play” runners, as you will commonly see more breakaway runs from the "lower EFF" guys. Guys like Derrick Henry and James Cook typically put up very low EFF numbers, and are known for getting downfield in a hurry and being efficient as a result. Players like Kenneth Walker III and Christian McCaffrey post higher EFF numbers and are known for dancing behind the line and (sometimes) making a lot out of a little.

As with time to throw, fantasy backs can win in different ways with different EFF markers. Pass-catching studs like McCaffrey often produce for fantasy with high EFFs, but more “pure rushers” like Henry and Jonathan Taylor have had extremely efficient fantasy stretches with extremely low EFFs.

Rush Yards Over Expected

Similar to “Completion Percentage Over Expected,” Next Gen Stats also has a metric to measure expected rushing yards on a given play and then calculate the rush yards over expected (RYOE). Unsurprisingly, this number also correlates very closely with yards per carry, but can provide a little more insight to that number, with a little less dilution from broken plays.

Guys like Cook and Henry are always high on the RYOE list (especially last year), but we can also see the rise of names like De'Von Achane (+1.03) and even J.K. Dobbins (+1.08 average RYOE in 2025), who have flashed the skills to make more out of a rush than the average player. We can also identify RBs who may never be a team's bell-cow back, such as Bucky Irving (-0.74) and Isiah Pacheco (-0.41). Players aspiring to efficient fantasy seasons despite low RYOEs will likely need to find value in the passing game (see McCaffrey, again) and/or the touchdown department (as R.J. Harvey as a rookie).

Next Gen Receiving Stats

Average Targeted Air Yards

After several years of growing popularity, Next Gen’s most recognizable impact in the fantasy community likely belongs to targeted air yards — i.e. air yards for receivers. Since we’ve covered the definition of air yards in the passing section above, we can focus here on how it translates to pass-catchers.

First, average targeted air yards (TAY), known colloquially to some as average depth of target (aDOT), is exactly what it sounds like — the average number of air yards downfield that a receiver sees on each target. It’s not at all difficult to pinpoint guys like Alec Pierce and Christian Watson for high TAYs. These are your downfield specialists, who will typically be more volatile for fantasy but often responsible for boom weeks throughout a season. On the flip side, you have your Wan'Dale Robinsons, Rashee Rices, and typical tight ends, who tend to see more volume closer to the line of scrimmage and are asked to create after the catch.

As with several of the metrics we’ve discussed, you can get excellent fantasy production from both ends of the spectrum on TAY. Take the Rams, for example: Puka Nacua logged just 8.9 average TAY, while Adams clocked in at 13.2 (well above average). And yet, both finished top-8 at the position in half-PPR points per game.

Once again, context can be key for translating this metric into actionable analysis. Is a receiver a yards-after-catch superstar? His low TAY is probably not an issue. Is a deep-ball specialist with a high yearly TAY switching from a gunslinging QB to a rookie game manager this year? That might be a bad sign for his fantasy outlook.

It’s also worth noting that TAY can be very specifically applied based on your draft or league format. If you’re playing in a PPR league with a tight-end premium (extra points for TE receptions), Tyler Warren and his low TAY (and therefore higher catch rate) gets a pretty significant boost. Are you drafting a best-ball team to win a massive cash prize? Well, those “better-in-best-ball” wideouts are very commonly identified by high TAYs — guys like Pierce and Rome Odunze were inconsistent last year but had several big weeks perfectly suited for best ball.

% Share of Team’s Air Yards

While targeted air yards are valuable, higher numbers don’t necessarily mean “stud” receivers, just specific kinds of receivers. If you’re looking to find the true studs, that’s where share of team’s air yards (TAY%) comes into play. This metric takes a player’s targeted air yards and calculates it as a chunk of their team’s total air yards, creating a measurement of who’s earning the highest volume of their team’s most valuable targets. The top of this metric typically looks like a who’s who of wide receivers and tight ends, with names like Jaxon Smith-Njigba and Brock Bowers ranking highly at their positions last year.

However, this metric is also extremely valuable in identifying breakout candidates, as a player with a high TAY% going from a bad situation to a better one will typically see noteworthy improvement. George Pickens was a TAY% stud in 2024 (39.4%), but was the WR45 in fantasy PPG. Then he moved to Dallas in 2025 and became the WR6 overall, even with CeeDee Lamb on the same roster. One of the biggest standouts in this regard heading into 2026 is Tetairoa McMillan, who dropped a 44.5% air yards share as a rookie, second in the league behind only Jaxon Smith-Njigba. With another year of development, and particularly if Bryce Young can take another step forward, that's the kind of "alpha" usage that could make McMillan a star in fantasy.

Obviously, all TAY% are not created equal, as a 35% share of the Bengals' air yards is going to be worth far more than 35% of the Dolphins' air yards, so that context is important to keep in mind. But if you’re looking to identify “X receivers,” or those rare “top-target tight ends,” this is a good way to do it. Along with McMillan, you might want to keep a close eye on Jaylen Waddle (38.7%) and DeVonta Smith in 2026.

The Bottom Line

• Next Gen Stats are best used to learn and understand the game, evaluate player talent, and explain the trends we see on the field. They’re not often the most predictive in a vacuum but can help us spot useful nuggets of data when properly contextualized.
• In most cases, the NGS metrics are most effective at telling us what kind of player someone is, rather than whether they’re going to be a fantasy stud or not. It’s up to you (or your favorite fantasy analyst) to fit those metrics into a bigger picture and project the relevant consequences.
• Several of the stats we discussed here are most relevant in identifying volatility versus consistency in a player’s production, so use those numbers in conjunction with a good understanding of your fantasy drafts/leagues to find advantages.
• While these and other “rate” metrics are useful, volume is still king in fantasy. Ideally, our QBs would have high average completed air yards and our RBs would have low NGS Efficiency marks, but those numbers aren’t converted into fantasy points without opportunity.