News: BTB: Finding the superior athlete: Impact edge rushers in the 2018 NFL Draft

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We look at the athleticism and the production of this year’s edge rushing class to try to figure out which player might have the biggest impact at the NFL level.

Back in 2015, we introduced Cowboys Nation to the concept of SPARQ on these pages, and SPARQ turned out to be a concept that resonated powerfully with many fans. A metric that was previously virtually unknown outside of the most hardcore advanced-stat-aficionados (and a bunch of Seahawks fans) now has Cowboys social media all a-buzz and a-twitter.

Over the next days and weeks, we’ll look at all the defensive position groups in this year’s draft class via SPARQ, so today I’ll provide an extended (re-)introduction to SPARQ before we move on to this year’s edge rusher class.

SPARQ

Many elite athletes in the various college programs find that once they enter the NFL, their previously elite skill set is - at best - par for the course on an NFL team. As a matter of principle, NFL players are bigger, faster, stronger, and more talented than college players.

Which is why NFL teams are obsessed with athleticism over almost anything else, and which is why we as fans pore of 40-yard dash times and other Combine measurables so much. You can teach most players to recognize when a defense is in man or zone, but you cannot teach a player to outrun a faster opponent.

Not all good athletes are good players
Very few poor athletes are good players
Most great players are great athletes

— Zach Whitman (@zjwhitman) March 6, 2017​

A little over a decade ago, Nike developed a metric called SPARQ. The idea behind SPARQ was to have a composite metric that would allow you to quickly assess the athleticism of a player with a single number. Think of it as an SAT score for Football Players. This “SAT” score, or SPARQ rating, does not trump the evaluation of game tape, a person’s football character and competitiveness, interviews with coaches, and medicals. It is just another tool for coaches to use, but it does encapsulate one simple truth about the NFL:

Given the same level of talent, the bigger/faster/stronger players almost always win.

And that’s where SPARQ comes in. The SPARQ metric is calculated using eight inputs. There is no height or arm length component involved, but SPARQ blends an athlete’s weight, explosive power, speed and agility into one metric.

(1) Player Weight: this “normalizes” the score, giving credit to a heavier player who displays similar movement skills as a smaller, quicker player.

(2) Explosive power bench press, broad jump, vertical jump.

(3) Speed and agility: 40-yard dash, ten-yard split, short shuttle and 3-cone drill.

Unfortunately, Nike never published the exact formula for the SPARQ metric. But an enterprising blogger, Zach Whitman, reverse-engineered an approximation of the formula, and while he doesn’t divulge the formula either, at least he publishes the results of his calculations at 3sigmaathlete.com.

Here’s Whitman explaining how SPARQ can be used.

What’s the use of SPARQ?

What we see often in pre-draft analysis is an over-emphasis on the forty-yard dash, for which there are two main reasons: (1) speed is important, and (2) we’re familiar with the common forty benchmarks. A 4.4s 40 is fast and sounds good, and there’s an inherent understanding of what it means.

The problem is that the forty-yard time isn’t fully indicative of a player’s overall athleticism. Most people don’t know off-hand what a good broad jump is for a wide receiver, and even fewer are aware of what they should expect from a defensive end. SPARQ is a way to standardize these different parameters and gain a more circumspect view of a player’s natural ability. [...]

SPARQ isn’t perfect. Player test results have error and, even if they were perfect, don’t fully represent the ability of an athlete. The goal here isn’t to build an airplane. SPARQ is just a method by which we can better understand players, and it’s important to not let perfect be the enemy of good.
​

So what, if any, correlation does the SPARQ metric have with actual NFL production? Here’s a chart courtesy of Zach Whitman at 3sigmaathlete.com explaining that exact correlation.

The chart uses Approximate Value (read up on that metric here) as a measure of NFL production and the SPARQ score as a measure of athleticism. SPARQ here is expressed as a player’s ranking relative to his peers at his position (a 0 z-score is average, a 2.0 is two standard deviations above the peer average). Whitman explains the rest:

What we see is that there’s a clear trend toward more athletic players producing a higher AV3. If there was no relationship between athleticism and production, this line would be flat, parallel to the x-axis (i.e., zero slope). This relationship is statistically significant with a p-value of approximately zero.
​

Today we're going to look at both the athleticism and production of the 2018 edge rusher class and then combine both to try to figure out which players might have the biggest impact at the NFL level.

ATHLETICISM


Whitman publishes all the pSPARQ numbers on his website, and the following table summarizes his SPARQ data for this year’s top 23 edge rushers with a Sparq score and a draftable grade by NFLDraftScout. For your convenience, the table is sortable (just click on the blue column headers).

Edge Rusher SPARQ 2018

POS​

CBS
Rank​

Player​

School​

Proj.
Round​

Ht​

Wt​

pSPARQ​

z-score​

NFL
Perc
DE​

4​

Bradley Chubb​

N.C. State​

1​

6-4​

269​

132.1​

0.9​

82.4
DE​

15​

Marcus Davenport​

Texas-San Antonio​

1​

6-6​

264​

130.9​

0.8​

80.1
DE​

19​

Harold Landry​

Boston College​

1​

6-3​

252​

134.7​

1.1​

87.1
DE​

34​

Sam Hubbard​

Ohio State​

1-2​

6-5​

270​

124.7​

0.4​

64.7
OLB​

40​

Lorenzo Carter​

Georgia​

1-2​

6-6​

250​

143.1​

1.8​

96.1
OLB​

51​

Rasheem Green​

Southern Cal​

2​

6-5​

275​

123.9​

0.3​

62.6
DE​

54​

Uchenna Nwosu​

Southern Cal​

2​

6-3​

251​

122.3​

0.2​

57.9
DE​

65​

Ogbonnia Okoronkwo​

Oklahoma​

2-3​

6-1​

253​

133.8​

1.1​

85.5
DE​

105​

Jalyn Holmes​

Ohio State​

3-4​

6-5​

283​

109.2​

-0.8​

21.8
DE​

116​

Tyquan Lewis​

Ohio State​

4​

6-3​

265​

140.8​

1.6​

94.4
OLB​

124​

Kylie Fitts​

Utah​

4​

6-5​

253​

131.9​

0.9​

82.1
DE​

133​

Chad Thomas​

Miami​

4​

6-6​

281​

106.8​

-1.0​

16.9
DE​

135​

Josh Sweat​

Florida State​

4​

6-3​

296​

142.4​

1.7​

95.6
OLB​

148​

Jeff Holland​

Auburn​

4-5​

6-2​

249​

103.9​

-1.2​

12.0
OLB​

152​

Ade Aruna​

Tulane​

4-5​

6-6​

262​

133.8​

1.1​

85.6
DE​

171​

Ola Adeniyi​

Toledo​

5​

6-2​

248​

108.4​

-0.8​

20.0
OLB​

177​

Marquis Haynes​

Mississippi​

5-6​

6-3​

235​

115.9​

-0.3​

38.9
DE​

189​

Hercules Mata'afa​

Washington State​

5-6​

6-1​

254​

108.3​

-0.8​

19.9
OLB​

190​

Dorance Armstrong​

Kansas​

5-6​

6-4​

257​

112.0​

-0.6​

28.4
OLB​

203​

Leon Jacobs​

Wisconsin​

6​

6-3​

246​

130.1​

0.8​

78.4
DE​

227​

John Franklin​

Stephen F. Austin​

6-7​

6-4​

283​

120.1​

0.0​

51.4
OLB​

242​

Garret Dooley​

Wisconsin​

7​

6-3​

248​

119.1​

0.0​

48.5
OLB​

250​

Peter Kalambayi​

Stanford​

7​

6-3​

252​

127.6​

0.6​

72.5​

​

A few notes on the data:

• pSPARQ is the single metric designed to summarize a player’s athleticism.
• z-score calculates a player’s ranking relative to his peers at his position. A z-score of 0 means a player has average athleticism, a 2.0 means he’s two standard deviations above the peer average, a negative value means he's below the peer average
• NFL perc. is the z-score translated into percentiles. A 50.0 percentile would represent a player who rates as a league-average NFL athlete at the position. The higher the number the better.

Going by the pSPARQ score, there are 15 edge rushers with above average athleticism in this draft class, among them some of the top prospects in this year's draft class, like Bradley Chubb (132.1), Marcus Davenport (130.9), Harold Landry (134.7), Sam Hubbard (124.7), Lorenzo Carter (143.1), or Ogbonnia Okoronkwo (133.8).

For comparison, 2015 Cowboys draft picks Randy Gregory and Ryan Russell had pSPARQ scores of 132.8 and 122.3 respectively, 2016 pick Charles Tapper had a score of 133.7, and 2017 pick Taco Charlton had a score of 121.6, all of which should give you an idea of what type of athleticism the Cowboys are looking for in their pass rushers. As a further point of reference, some of the better pass rushers to enter the league in recent years like J.J. Watt, DeMarcus Ware, Jadeveon Clowney, Justin Houston, or Cameron Jordan all scored above 140.

Not all edge rushers have a Sparq score though; highly-rated players like Arden Key or Duke Ejiofor didn't complete enough drills to calculate a score from.

So now we know who the superior athletes in this edge rusher class are. But by itself, that won’t help us all that much. After all, the history of the NFL draft is littered with superior athletes who never made it in the NFL.

Which is why we're now going to look at the college production of the edge rushers in the 2018 draft class.

PRODUCTION


The Production Ratio is a metric initially proposed by Pat Kirwan, and is a very simple metric that adds up sacks and tackles-for-loss and divides the sum by the number of college games played. The resulting number is one tool among many - albeit a pretty good one - that measures the playmaking potential of front four players coming out of college. The Production Ratio is calculated as follows:

PRODUCTION RATIO = (SACKS + TACKLES FOR LOSS) / NUMBER OF GAMES PLAYED ​

​

The resulting number gives you a metric with which to evaluate a player’s playmaking ability, even if it isn’t a one-to-one measure of the frequency of splash plays (sacks or tackles-for-loss) a player recorded per game. That’s because in the official stats, a sack also counts as a tackle for loss, so adding up the two numbers is a bit of double-counting. But in terms of the Production Ratio as originally described by Pat Kirwan, sacks plus the total number of TFLs go into the formula.

The ratio is usually calculated over the entire college career of a prospect, but that method can be inaccurate because not every prospect has a four-year career in college or the prospect might be a late-bloomer. To correct for that, we’ll only look at the last two seasons of a player’s college career. For the two-year measure, a number above 1.5 is often indicative of premier talent for a pass rusher, a value above 2.0 can be indicative of elite talent.

Not every successful NFL pass rusher necessarily had prolific college production. Detroit’s Ezekiel Ansah had 44 sacks over his first five seasons, yet only had a two-year production ratio of 0.70 in college. Chandler Jones entered the league with a modest production ratio of 1.28, yet he leads the 2012 draft class with 64 total sacks over six years. In Ansah’s case, his exceptional athleticism and physical potential trumped his lack of college production, in Jones’ case, a knee injury severely limited him in his final college season, thus his lack of elite-level production in college.

Similarly, not every draft prospect with a high college production ratio will automatically turn into an All Pro pass rusher in the NFL. In 2014, Jackson Jeffcoat had the highest production ratio of his draft class with 2.47, but was out of he NFL after just two years, only starting in one NFL game.

The table below shows the current top-ranked edge rusher prospects in the 2018 draft class. The table is sorted by each player's NFLDraftScout ranking and contains the top 27 edge rusher prospects that were given a draftable grade by NFLDraftScout.

Player College Stats Production Ratio

POS​

Rank​

Player​

School​

Proj. Rd​

Ht​

Wt​

Sacks​

TFL​

Games​

Last two seasons
DE​

4​

Bradley Chubb​

North Carolina State​

1​

6-4​

269​

20.0​

46.5​

25​

2.66
DE​

15​

Marcus Davenport​

Texas-San Antonio​

1​

6-6​

264​

15.0​

27.0​

24​

1.75
DE​

19​

Harold Landry​

Boston College​

1​

6-3​

252​

21.5​

30.5​

22​

2.36
DE​

34​

Sam Hubbard​

Ohio State​

1-2​

6-5​

270​

10.5​

21.5​

27​

1.19
OLB​

40​

Lorenzo Carter​

Georgia​

1-2​

6-6​

250​

9.5​

13.5​

28​

0.82
DE​

45​

Arden Key​

LSU​

2​

6-6​

238​

16.0​

20.0​

19​

1.89
OLB​

51​

Rasheem Green​

Southern Cal​

2​

6-5​

275​

16.0​

19.0​

27​

1.30
DE​

54​

Uchenna Nwosu​

Southern Cal​

2​

6-3​

251​

12.5​

19.0​

27​

1.17
DE​

65​

Ogbonnia Okoronkwo​

Oklahoma​

2-3​

6-1​

253​

17.0​

29.5​

26​

1.79
DE​

73​

Duke Ejiofor​

Wake Forest​

2-3​

6-4​

264​

17.0​

33.5​

25​

2.02
DE​

102​

Kemoko Turay​

Rutgers​

3-4​

6-4​

251​

6.0​

9.0​

20​

0.75
DE​

105​

Jalyn Holmes​

Ohio State​

3-4​

6-5​

283​

4.0​

11.5​

27​

0.57
DE​

116​

Tyquan Lewis​

Ohio State​

4​

6-3​

265​

15.0​

20.0​

27​

1.30
OLB​

124​

Kylie Fitts​

Utah​

4​

6-5​

253​

4.5​

6.0​

12​

0.88
DE​

133​

Chad Thomas​

Miami​

4​

6-6​

281​

9.5​

23.5​

25​

1.32
DE​

135​

Josh Sweat​

Florida State​

4​

6-3​

296​

12.5​

24.0​

24​

1.52
OLB​

148​

Jeff Holland​

Auburn​

4-5​

6-2​

249​

12.0​

16.0​

27​

1.04
OLB​

152​

Ade Aruna​

Tulane​

4-5​

6-6​

262​

8.0​

13.0​

24​

0.88
DE​

171​

Ola Adeniyi​

Toledo​

5​

6-2​

248​

12.5​

28.0​

27​

1.50
OLB​

177​

Marquis Haynes​

Mississippi​

5-6​

6-3​

235​

14.5​

22.0​

24​

1.52
DE​

189​

Hercules Mata'afa​

Washington State​

5-6​

6-1​

254​

15.5​

36.0​

26​

1.98
OLB​

190​

Dorance Armstrong Jr.​

Kansas​

5-6​

6-4​

257​

11.5​

29.0​

24​

1.69
OLB​

203​

Leon Jacobs​

Wisconsin​

6​

6-3​

246​

4.5​

10.5​

27​

0.56
DE​

227​

John Franklin​

Stephen F. Austin​

6-7​

6-4​

283​

11.5​

28.0​

22​

1.80
DE​

229​

Davin Bellamy​

Georgia​

6-7​

6-5​

255​

10.0​

16.5​

28​

0.95
OLB​

242​

Garret Dooley​

Wisconsin​

7​

6-3​

248​

11.0​

18.5​

28​

1.05
OLB​

250​

Peter Kalambayi​

Stanford​

7​

6-3​

252​

7.5​

13.0​

27​

0.76​

​

The Production Ratio, like every other stat-based projection tool, is not going to be a perfect predictor of how successful college players are going to be in the NFL. But it does give you something to think about as you evaluate these players and their potential, and it may be one building block in identifying who this year’s playmakers will be - and who won’t.

There are some guys on here whose playing weight may make them more suited to play pass rushing OLBs or 5-techniques in a 3-4 scheme, just as there are players here whose NFL teams may choose to move them inside to 3-technique in a 4-3 defense. But if the Cowboys are looking for pass rushers in the draft, this is the talent pool available.

Bradley Chubb and Harold Landry are the two obvious standouts on this list from a pure Production Ratio point of view. Chubb will likely be out of reach for the Cowboys, but Landry could potentially be available at No. 19.

The knock on Landry has been that his best college season was in 2016 and that he couldn't repeat that performance in 2017, which obviously is something teams will have to consider carefully. But Landry reportedly played hurt in 2017, which would have impacted his production. If we only look at his 2016 stats, his production ratio jumps to 2.92, an astonishingly high value for a Division I player.

We can do the same kind of cherry-picking for the other prospects of course, and only use their 2017 season to calculate their Production Ratio. Here are the top five single-season ratios for the 2018 edge rusher prospects: Harold Landry (2.96), Bradley Chub (2.92), Hercules Mata'afa (2.54), Marcus Davenport (2.32), and Ola Adiniyi (2.04).

Overall, the 2018 draft class looks like a good draft class for pass rushers. If the Cowboys want a pass rusher, they could have their choice in Marcus Davenport or Harold Landry at the top of the draft, but could also find guys with a strong track record of college production, like Duke Ejiofor (2.02), Arden Key (1.89), or Ogbonnia Okoronkwo (1.79) a bit later in the draft.

What the Cowboys need to do is figure out which of the many prospects available can be the most productive in the Cowboys’ scheme, and that may be an entirely different question than whether a guy was highly productive in college or can run a fast 40-yard dash.

ATHLETICISM AND PRODUCTION


If we combine the two metrics, SPARQ and the Production Ratio, we should be able to find the most productive AND the most athletic edge rushers in this draft. The graph below plots the Production Ratio against the SPARQ score for the 23 edge rushers from the tables above.

The two red lines divide the graph into above average and below average performers. Players with a Production Ratio of 1.5 or more (the top two quadrants, “A” and “C”) delivered an above average production in their last two college seasons. Players with a SPARQ score of more than 120 (the two quadrants on the right, “A” and “B”) are above average athletes relative to their NFL peers.

The A quadrant (top right) is where you should find the players most likely to succeed at the NFL level. They have a strong track record of production and have the prerequisite athleticism that should allow them to compete at the NFL level. Six edge rushers from this year’s draft class populate this quadrant, which makes this a solid draft class.

Two edge rushers most frequently associated with the Cowboys (Harold Landry and Marcus Davenport) both find themselves in this quadrant. Both would require a first-round pick (and maybe more) to acquire, but there are also A-quadrant players like Ogbonnia Okoronkwo or Josh Sweat available outside of the first round.

The B quadrant (bottom right) shows superior athletes whose college production has been below average. And while this doesn’t automatically invalidate them as potential prospects, it does raise questions. Teams need to understand why these guys didn’t have the kind of production other players, often with inferior athleticism, had. Was it the scheme they played in, the players they played next to, the opponents they played against, the role they were asked to play, or are they simply not very good football players?

The numbers here won’t answer those questions, but those are questions teams will have to answer satisfactorily via film study, player interviews, coaching interviews, or other means.

The C quadrant (top left) features players with a strong record of production at the college level, but who have questions regarding their athletic ability. Again, being in this quadrant is not necessarily a bad thing - Demarcus Lawrence, for example, was a C Quadrant player (113.8 SPARQ, 2.28 Production ratio). However, if you don’t have the athleticism to compete at the next level, odds are you’re going to struggle mightily - regardless of your college production. It’s just an extra question teams will have to answer.

The D quadrant (bottom left) is a tough one to be in. Below average production and below average athleticism don’t promise a great future in the NFL, but once more, you need to understand each individual case before closing the book on a prospect.

Overall, there is a fairly good chance that either Marcus Davenport or Harold Landry will be available when the Cowboys are on the clock. From a production/athleticism point of view, both would be very good options for the Cowboys - if the Cowboys are looking for a pass rusher. If they have other priorities for their first pick, they still have Day Two options with the likes of Ogbonnia Okoronkwo or Josh Sweat, but it thins out quickly after that.

The mandatory caveat: There are a multitude of factors that determine how well a prospect will do in the NFL. College production and athletic markers are just some of them, but at the very least, they provide some interesting input into the evaluation process.

Given these numbers, and given what you know about these prospects, in which rounds would you be looking for a defensive end, and which one would it be?


As an addendum, here are some historical numbers for edge rushers for comparison.

It’s important to note that while great pass rushers seem to cluster in the A-quadrant, there are great players in the B and C quadrant as well, even if they are not quite as plentiful.

Also, if you're thinking what the heck has all of this got to do with the Cowboys, check out the chart below from last year's draft class. Last year's exercise left us with 17 A-Quadrant prospects on defense, prospects that entered the league with a college history of above average production and a demonstrated above average athleticism.

Nine of the 17 players on this graph visited the Cowboys prior to the draft, and three of them (Taco Charlton, Chidobe Awuzie, and Xavier Woods) ended up being picked by the Cowboys. Both are excellent tallies. The only other NFL team with multiple picks from this 17-player pool is New Orleans (Trey Hendrickson, Marcus Williams) with two. That doesn't mean all these players will automatically succeed in the NFL, but their odds of doing so are better than those of other players with lesser production and athleticism.

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