2016 NFL Draft: Finding Playmaking Linebackers For The Cowboys

The Cowboys have a lot of question marks at linebacker heading into the 2016 season. They don't know whether Sean Lee will be available for the entire season. Rolando McClain's future with the team is uncertain, and carries the risk of a 10-game ban anyway. They don't know how much recent draft picks Anthony Hitchens and Damien Wilson will be able to contribute in 2016. That's a lot of question marks for the linebacker corps.

The Cowboys will almost certainly shore up the unit during free agency, and there's a good chance they'll look to the draft for linebackers as well. Who they'll end up looking at largely depends on how they view the players already on the roster.

Over the last few years, we've used the Production Ratio to assess which defensive line draft prospects could be potential playmakers in the NFL. Most recently, we looked at the 2016 Defensive Tackles as well as the 2016 Defensive Ends using that metric. But while the Production Ratio looks like a good early indicator for the success of a college DE or DT at the NFL level, the ratio is primarily designed as a measure of disruptiveness for defensive linemen. As such, it is not particularly suited to identify playmaking linebackers in a 4-3 scheme.

So instead of rehashing the Production Ratio, we'll use "Production Points," which is similar to what the Cowboys use to evaluate their defensive players. The metric is actually pretty straightforward, as it looks at the available linebacker stats and weights them with a point system as follows:

Fumble recoveries are not included, as those are about as random a stat as there is. Also not included are defensive scores, as they are largely dependent on field position and have a large degree of randomness as well.

Note also that there is a significant amount of double-counting within these college stats. Officially, a sack for example also counts as a tackle for loss as well as a regular tackle. At the same time, an interception does not count as a pass defensed. In the tables further down, I'll list the full college stats of each player, but I'll eliminate the double counting from the Production Points metric.

Finally, once we've tallied all the points for a given player, we'll divide the total by the number of college games played. To avoid having to adjust for the learning curve most college players go through over their career, we'll only look at the Production Points for the last two college seasons. For the juniors (marked with a '*' below) who declared early, these two seasons will be their junior and sophomore seasons.

To kick things off, and to get a feel for the metric, let's look at the Production Points for the top three off-the-line linebackers (as measured by Approximate Value) from the 2012-2014 draft classes.

As measured by Approximate Value, the nine players above are the top linebackers in their respective draft classes. And going by their Production Points, it seems that a score of 15 or more is a strong indicator of very high college productivity, and potentially future NFL success.

Before we look at this year's draft class, a couple of very general observations about Production Points: This number is just one way of looking at the data we have for each prospect. It is not the be-all and end-all of statistical analysis. In fact, I'd be the first to argue that it isn't even a stat at all, but merely a stat comprehension tool. This metric groups a bunch of numbers that may or may not correlate with each other, and infers causality where there may not even be a correlation.

When you look at the stats you want from an inside linebacker, you want to see a lot of tackles, because that could be an indication that the player diagnoses plays well and has a nose for the ball. You want to see some TFLs and perhaps a few sacks because that could mean he is fast to read and react. You want to see some passes defensed or even a few interceptions because that could mean he plays the pass well.

At the same time, you need to understand the context in which those stats were achieved. A linebacker might have a high tackle number because the defensive scheme he played in funneled ball-carriers his way. He might have high TFL and sack numbers because he moonlighted as a pass rusher on occasion, and those interceptions and passes defensed may have had more to do with luck than with a specific skill.

But we'll use the Production Points system anyway, cognizant of its flaws, because the metric does one thing very well: it provides a different perspective by which to evaluate the draft prospects - and in my book, anything that gets us off the beaten path is a good thing.

The next table features 28 of the top draft prospects who are projected as either inside or outside linebackers in a 4-3 defense. I have omitted all linebackers who project as defensive ends or 3-4 OLBs in the NFL. The 28 prospects are sorted by their rank on the CBSSports big board from Feb. 8, but the table is sortable (click on the blue column headers) so you can sort the data to your heart's content.

Just for reference, Sean Lee had 15.7 Production Points in his last two full college seasons, Rolando McClain had 13.8 and Anthony Hitchens had 13.4.

Two years ago, Ryan Shazier led all off-the-line linebackers with 19.2 Production Points. It's well-documented how Shazier was minutes away from becoming a Dallas Cowboy, so if the Cowboys didn't get who they wanted then, does that mean that they'll try to pick up this year where they left off in 2016?

Scooby Wright stands out in this Production Points analysis, but that doesn't automatically mean that his high college production will translate to the next level, as Rob Rang of CBSSports explains.

His production was inflated by spinning off would-be blockers and tracking down ball carriers in pursuit, as well the action being funneled to him in Arizona's unique 3-3-5 spread defensive alignment. He was often asked to rush the quarterback rather than drop into coverage at Arizona and may lack the fluidity and straight-line speed to handle third down duties in today's pass-happy NFL.

The challenge of adapting to a more traditional defensive alignment and holding up in pass coverage, however, could keep him on the board into Day Two and raises concerns about his ability to duplicate his eye-popping collegiate success in the NFL.

Jatavis Brown, Nick Vigil, and Tyler Matakevitch occupy the next three spots in the Production Points ranking, but how much their points actually means depends a lot on how much weight you give the quality of the opponents these three players faced in college.

Kentrell Brothers and Jaylon Smith are two prospects from big-name schools that also show up well in this ranking. Brothers led the nation in tackles over the last two seasons, and Jaylon Smith is an explosive athlete with great instincts.

When you sort the table above by Production Points, you may notice that Myles Jack is ranked fairly low. This is a bit surprising given his status as a top ten prospect and potential Cowboys target, but it also shows the limitations of an analysis like this that is largely based on volume stats.

One reason Jack's numbers are relatively low is that Jack was a two-way player at UCLA, doubling as a running back on occasion. He also missed all but three games in his final season in 2015, a season that could easily have seen him put up much higher numbers than the year before. Another reason for the low numbers is that in 2014, Jack played mostly weak-side linebacker next to a true middle linebacker in Eric Kendricks (14.7 Production Points) and strong-side linebacker in Anthony Barr (14.6 Production Points) who were both vacuuming up ball carriers. Due to his knee injury in 2015, fans and scouts alike didn't get the chance to evaluate Jack as a middle linebacker, and while he is a terrific player in space, there are some very real concerns about his ability to play MLB, where he'd have to shed blocks regularly and make plays at or behind the line of scrimmage.

From a production point of view, this is a deep but not particularly strong linebacker class, but we saw in the examples above that the metrics we used here may not tell the entire story of a prospect. The Combine will certainly add another level of clarity to this class, but for now this class leaves us with more questions than answers.