Last time I ran through offensive metrics (link here) that matter and now I will hit the defense. Defense is a lot harder to simplify as there are fewer true individual metrics and a player’s impact on defense often doesn’t show up in a stat. Correlations to player value (Approximate Value or AV) will be lower and players will be outliers to a bigger degree. As a reminder, here I am seeking as best as possible metrics that you can see when watching a game and avoiding player “grades” which don’t mean anything themselves (grades from PFF, as an example, are really good but there isn’t much value in just relaying them here).
| Defensive Line | Linebacker | Cornerback | Safety |
| Pass rush win rate + Run stops | Run stops + Completion % allowed + Pressures | Completion % allowed + Yards per reception + TDs-interceptions + Missed tackle rate | Forced incompletions + Run stops + Pressures + Turnovers |
Defensive Line
Pass Rush Win Rate + Run Stops
The best defensive line metrics are, naturally, the opposite of the offensive line’s metrics:
- Pass rush win rate (PRWR) – The ability to beat a block in less than 2.5 seconds
- Run stops* – The ability to force a runner to adjust a running lane or make a tackle within 3 yards of the line of scrimmage
*Run stops are defined as the lineman preventing an offensive player from gaining 40% of yards to go on 1st down, 50% of yards to go on 2nd down, and preventing a first down or touchdown on 3rd and 4th downs. Basically, limiting the offense to less than half the yards they need.
Pass Rush Win Rate (PRWR) is not a perfect metric because the pass rush is only one piece of a defense’s success against the pass with the secondary being a huge component. To illustrate, below shows PRWR vs. the passer rating allowed with coverage grades shown with the circle size (smaller circle is a worse coverage grade).
With this you will see Philadelphia with a relatively good pass rush but a poor passer rating allowed but this was because of its secondary. Conversely, the teams in the bottom right are the teams with the best PRWRs and lowest passer ratings allowed – these all also have good coverage grades. In the bottom left, there are some teams (SFO, DEN, and GNB) with below average PRWRs but still good passer ratings allowed due to very good coverage grades.
Switching to run defense, below shows run stop rate (run stops as a percentage of rush attempts) vs. rush yards per attempt. Using run stops works better than the related Run Stop Win Rate (RSWR) which has some oddities (Houston scores in the top 10 in RSWR but has the lowest rated run defense in the league). The circle size below is the RSWR to visualize it, with a bigger circle being a higher rated RSWR. You can see HOU as an outlier, allowing 5.2 yards per attempt but having a good RSWR score, but when you use run stop percentage, HOU drops to one of the lower in the league.
Neither of these will get really high R2 values because defensive line can only control the pass and rush so much on its own (run stops have a bit better correlation than pass rush). Both metrics intuitively make sense. A run stop (limiting to fewer than half of the yards to go) shortens drives and reduces chances to score. And defensive linemen beating their blocks in under 2.5 seconds either gets to the quarterback for a pressure (offensive DVOA reduces by over 100 points under pressure) or forces a quicker throw which will limit depth of target and explosive plays.
Linebacker
Run Stops + Completion % allowed + Pressures
Linebacker is becoming one of the more interesting positions in the NFL (along with safety) as they are the primary position often tasked with dealing with the growing offensive mismatches being used. It’s becoming hard to even list who is a linebacker – “base” defense is only 25% of snaps so at least one linebacker is off the field most of the time. But more and more, hybrid players (converted safeties or undersized but athletic ends) are being used in this role.
To simplify linebacker as much as possible and cover their responsibilities in both run and pass defense, the three key metrics to look at are run stops, forced incompletions, and pressures. These three get an R2 of 0.63, meaning 63% of a linebackers value (defined by AV) is explained by them:
- Run stops* – Average of 6.6 per season across all LBs, 14.6 among starters
- Forced Incompletions – Average of 1.3 per season across all LBs, 2.9 for starters
- Pressures – Average of 5.4 across all LBs, 11.9 for starters
The key outliers in the top right on the below chart are the elite linebackers and seasons (Fred Warner, Darius Leonard, Bobby Wagner, Dont’a Hightower in 2019). One thing to note is almost all are part of defenses that have top-end DVOA scores which may be elevating all defensive player value scores given how AV works (a large part of the AV score includes the starting total value of the defense which is split up by positional allocation). But the combination of stops, incompletions, and pressures has a good correlation to linebacker value.
When you look at the top linebackers from 2020 (those that generated 10 or more AV for the season), you see that while they are all good at both run and pass defense, they have wide ranges across these metrics, which is what makes it impossible to use a single metric.
As I explained in the offensive metrics post, the closer these metrics are to true value – which is scoring points on the offense and preventing points scored on the defense – the better they will be. For linebackers, limiting run gains, forcing an incompletion, and disrupting the quarterback are the most important things they can do, especially in the NFL today when they are asked to cover receivers, tight ends, running backs, and increasingly contain mobile quarterbacks.
Cornerback
Completion % allowed + Yards allowed per reception + TDs allowed – Interceptions + Missed tackle rate
Cornerback is another position that is tough to measure easily. The best corners often aren’t targeted and result in a lack of traditional metrics (interceptions, forced incompletions) or skew other metrics (catch rate, yards per reception).
Many will look at yards allowed per coverage snap which is a very good stat but there is too much overlap between good and bad cornerbacks as shown below. The top CBs (with AV of 10 or above) are in blue with the rest of the league in red – while the top CBs on average give up fewer yards per coverage snap (1.0 yard vs. 1.3 yards), there is so much overlap.
The reason yards per coverage snap fails is because the best corners often have a higher average depth of target as they cover the best receivers as shown below. The top CBs in the league have an average depth of target of 11.4 yards, a full yard higher than the bottom quartile and 0.7 yards above the average. As an example, in the above chart one of the blue dots further to the right is Jalen Ramsey’s 2018 season where he allowed an above average 1.3 yards per coverage snap but he dealt with one of the highest average depths of target (13.5 vs. a league average of 10.7) as he was in single-coverage vs. WR1s. Justifying his value ranking, he gave up an elite catch rate (87th percentile) and lower than average QB rating allowed (73.8).
The cornerback metrics are more complicated than I was seeking and ultimately you would want to compare corners against rated wide receivers, but the below four metrics do a good job of explaining corner value (and, again, these are metrics you can easily see watching a game):
- Completion % allowed – How often the CB allowed a receiver to make a catch. Slot receivers or CBs covering short routes can be penalized on completion % alone which is why yards allowed and average depth of target (aDOT) needs to be considered next.
- Yards allowed per reception – Average yards per reception is a good metric but skews slot corners that defend shorter routes and penalizes corners that have to defend deep threats. I tried different adjustments (without needing to pull # of slot vs. outside snaps) and settled on using yards allowed per reception * 10.7/aDOT. The average depth of target across all CBs is 10.7 so this will give a slight adjustment based on the depth that CBs are defending.
- Touchdowns allowed minus interceptions – As we are looking at metrics that stay as close to true value (the ability to score or prevent a score), TDs and interceptions are absolutely critical. Interceptions are valued at 0.588 of a touchdown based on prior research explained here). This is the metric that shows the least stability year-to-year and while it reflects CB ball skills, there is an opportunistic or situational component to it as well.
- Missed tackle rate – This is one of the more stable metrics year-to-year for corners and covers both their value in the run game and in limiting gains in passing.
No metric will ever be perfect and result in an un-debatable ordering of players – AV doesn’t do this, PFF is great but has its flaws, and so on. But below shows the top CBs in 2020 by catches, yards, TD-Ints, and missed tackles. The center grey columns show each player’s percentile performance in each and these percentiles are then combined into a composite score, one weighted per 500 coverage snaps (to give more weight to players that played more and weed out low volume players) and a second percentile that is unweighted. I included each player’s AV (column 4) and the PFF rank for the top 10 corners (last column).
There are, of course, differences between this and AV and PFF rankings. The relative weightings of catches vs. yards vs. TD-Ints could be adjusted to value the aspects of a corner’s role more or less, but there were several interesting things when I looked at this:
- There is pretty good agreement with AV but a little more difference with PFF ranks. One reason is PFF scores regardless of snap count – Bryce Callahan is the key example here, rated 3rd by PFF with elite coverage grades and 2 interceptions and no TDs allowed but he only played 386 coverage snaps. I prefer weighing snap count because the more a player plays, the greater their value, but it depends what you are trying to accomplish.
- As mentioned above, interceptions aren’t a very stable metric year-to-year but they are valuable and need to be included (besides a touchdown, turnovers are the highest value play at 4 expected points). But interceptions will skew CBs – the examples of CBs with high interceptions here are Malcolm Butler (5) and Xavien Howard (10). Both are 4-5 spots higher than they would have been if they had interception totals at their career average. But again, interceptions are valuable and both Butler and Howard are known for their ball skills.
Safety
Forced incompletions + Run stops + Pressures + Turnovers generated
Safety turned out to be one of the most difficult positions to simplify because similar to linebacker, what a safety is today is increasingly varied. They have responsibilities in coverage, against the run, as a pass rusher, and often take responsibility covering the tight end and running back.
Because of this, how the top safeties generate value varies widely. The average usage for safeties is 65% in coverage, 32% in the box, and 3% as a pass rusher but the actual usage varies greatly. Below shows safeties plotted by percentage of time in coverage or the box and their AV value and PFF rankings denoted with the circle colors. Players above the dashed line are used in the box more than average and below the dashed line are used in coverage more often.
Given this, safeties can provide value in greatly different ways and you cannot just look at coverage stats, even though coverage is still two-thirds of their time. The simplest way I believe to look at this is to “count the impacts” of safeties – impacts defined as the discrete plays that you can see including forced incompletions, run stops, quarterback pressures, and turnovers (forced fumbles and interceptions). Other metrics like completion percentage allowed or missed tackle rate slightly improve the tie to value but overcomplicate an already complicated view.
The below shows safeties grouped into sets of 10 players by their 2020 AV compared with the number of forced incompletions, run stops, pressures, and turnovers. The top ten safeties by value generate 28.5 “impacts” vs. 23.5 for the next group of ten with a continual decline shown.
There is one outlier group, the 81-90 grouping where Miami’s rookie Brandon Jones skewed the numbers as he generated 15 run stops and 6 pressures in only 385 snaps as an almost exclusive box defender. In 2020, Jones only accumulated 2 AV but projecting him out to a full season, his AV would be 6-7 and would have put him in the top 30 safeties. Players with low snap / game counts and little history that stick out in the data are interesting to watch moving forward as their playing time increases.
As with the other metrics, I was seeking relatively simple metrics you can see when watching games that are highly correlated to player value. With safeties, these all make sense – their ability to stop completions and stop runs, to pressure the QB, and to generate turnovers all have great value to a defense.
Note: The source data files will be added here and to Github once they are cleaned up and any non-sharable data is removed.