When we introduced Cowboys Nation to the concept of SPARQ back in 2015, it resonated powerfully with many fans. A metric that was previously virtually unknown outside of the most hardcore advanced-stat-aficionados has now become a staple of our draft preparation - despite the Cowboys not having a first-round pick this year.
Over the next days and weeks, we’ll look at all the defensive position groups in this year’s draft class via SPARQ. Which is why I’ll provide an extended (re-)introduction to SPARQ today. Skip the next few paragraphs if you’re familiar with SPARQ, read them if not. After the introduction, we’ll we move on to this year’s edge rusher class.
INTRODUCTION TO SPARQ |
Many elite college athletes find that once they enter the NFL, their previously elite skill set is merely an average skill set 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 obsess over 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. A good athlete is not automatically a good player, and very few poor athletes are good players. But most great players (outside of perhaps QBs and specialists) are great athletes.
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 0.0 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 2019 edge rusher class and then combine both to try to figure out which players might have the biggest impact at the NFL level.
ATHLETICISCM: SPARQ 2019 |
Whitman publishes all the pSPARQ numbers on his website, and the following table summarizes his SPARQ data for this year’s top 29 edge rushers ranked among the top 256 draft prospects by The Draft Network. For your convenience, the table is sortable (just click on the blue column headers).
Edge Rusher SPARQ 2019 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|
POS | Rank | Player | School | Ht | Wt | pSPARQ | z-score | NFL Perc |
||
DE | 1 | Nick Bosa | Ohio State | 6'3¾" | 265 lbs | 128.5 | 0.7 | 74.8 | ||
OLB | 4 | Brian Burns | Florida State | 6'5" | 231 lbs | 142 | 1.7 | 95.4 | ||
OLB | 6 | Josh Allen | Kentucky | 6'4'' | 230 lbs | 129.9 | 0.8 | 78 | ||
DE | 20 | Clelin Ferrell | Clemson | 6'5'' | 260 lbs | - - | - - | - - | ||
DE/OLB | 30 | Montez Sweat | Mississippi State | 6'5'' | 241 lbs | 144.8 | 1.9 | 97.1 | ||
DE | 32 | Rashan Gary | Michigan | 6'4" | 281 lbs | 141.7 | 1.7 | 95.1 | ||
OLB | 42 | Jachai Polite | Florida | 6'2'' | 260 lbs | 105.1 | -1.1 | 13.8 | ||
DE/OLB | 43 | Chase Winovich | Michigan | 6'3" | 253 lbs | 127.3 | 0.6 | 71.7 | ||
OLB | 47 | Christian Miller | Alabama | 6'3" | 240 lbs | - - | - - | - - | ||
OLB | 77 | D'Andre Walker | Georgia | 6'2" | 240 lbs | - - | - - | - - | ||
DE | 94 | L.J. Collier | TCU | 6'4" | 276 lbs | 101.9 | -1.3 | 9.3 | ||
DE | 97 | Wyatt Ray | Boston College | 6'3" | 250 lbs | 117 | -0.2 | 42.1 | ||
DE | 98 | Zach Allen | Boston College | 6'4⅛" | 280 lbs | 112.6 | 0.1 | 54.2 | ||
DE | 120 | Joe Jackson | Miami | 6'5" | 258 lbs | - - | - - | - - | ||
OLB | 121 | Justin Hollins | Oregon | 6'4" | 238 lbs | 129.4 | 0.6 | 74.2 | ||
DE | 123 | Jaylon Ferguson | LA Tech | 6'5" | 269 lbs | - - | - - | - - | ||
DE/OLB | 130 | Oshane Ximines | Old Dominion | 6'3'' | 247 lbs | 111.9 | -0.6 | 28.1 | ||
DE | 140 | Anthony Nelson | Iowa | 6'7" | 271 lbs | 130.2 | 0.8 | 78.6 | ||
DE | 165 | Malik Carney | North Carolina | 6'3'' | 235 lbs | 108.6 | -0.8 | 20.5 | ||
OLB | 167 | Sutton Smith | Northern Illinois | 6'0'' | 225 lbs | 115.8 | -0.3 | 38.7 | ||
DE | 178 | Ben Banogu | TCU | 6'4" | 249 lbs | 144.9 | 1.9 | 97.1 | ||
DE | 198 | Maxx Crosby | Eastern Michigan | 6'5" | 265 lbs | 135.8 | 1.2 | 88.7 | ||
DE/OLB | 208 | Jalen Jelks | Oregon | 6'5" | 245 lbs | 101.7 | -1.3 | 9 | ||
DE | 231 | Byron Cowart | Maryland | 6'4" | 270 lbs | 97.2 | -1.7 | 4.7 | ||
DE | 234 | Shareef Miller | Penn State | 6'5" | 256 lbs | 102.1 | -1.3 | 9.4 | ||
DE | 240 | Jonathan Ledbetter | Georgia | 6'3" | 277 lbs | 84.3 | -2.6 | 0.4 | ||
DE | 244 | Cece Jefferson | Florida | 6'1'' | 242 lbs | 92.1 | -2.1 | 2 | ||
DE | 252 | Austin Bryant | Clemson | 6'3⅞" | 270 lbs | - - | - - | - - | ||
DE | 256 | Carl Granderson | Wyoming | 6'4" | 255 lbs | 115.4 | -0.3 | 37.6 |
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 0.0 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 11 edge rushers with above average athleticism in this draft class, among them some of the top prospects in this year’s draft class, like Nick Bosa (128.5), Josh Allen (129.9), or Brian Burns (142.0).
The Cowboys may not be looking for a pass rusher this year, but for comparison, here are the pSPARQ scores of some recent Cowboys draft picks:
2015 - Randy Gregory: 132.8
2015 - Ryan Russell: 122.3
2016 - Charles Tapper: 133.7
2017 - Taco Charlton: 121.6
2018 - Dorance Armstrong: 112.0
This 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.
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 2019 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.
The ratio we used is calculated over 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. For more on the methodology, and a detailed look at this year’s draft class, follow this link.
The table below shows the same 29 prospects as in the table above, but this time shows their production ratio.
Players | College Stats | Production Ratio | |||||
---|---|---|---|---|---|---|---|
POS | Rank | Player | School | Sacks | TFL | Games | Last two seasons |
DE | 1 | Nick Bosa | Ohio State | 12.5 | 22.0 | 17 | 2.03 |
OLB | 4 | Brian Burns | Florida State | 14.5 | 29.0 | 25 | 1.74 |
OLB | 6 | Josh Allen | Kentucky | 24.0 | 32.0 | 26 | 2.15 |
DE | 20 | Clelin Ferrell | Clemson | 21.0 | 37.5 | 29 | 2.02 |
DE/OLB | 30 | Montez Sweat | Mississippi State | 22.0 | 29.5 | 26 | 1.98 |
DE | 32 | Rashan Gary | Michigan | 9.0 | 19.5 | 22 | 1.30 |
OLB | 42 | Jachai Polite | Florida | 13.0 | 23.0 | 20 | 1.80 |
DE/OLB | 43 | Chase Winovich | Michigan | 13.0 | 35.5 | 26 | 1.87 |
OLB | 47 | Christian Miller | Alabama | 9.5 | 13.5 | 18 | 1.28 |
OLB | 77 | D'Andre Walker | Georgia | 13.0 | 24.5 | 28 | 1.34 |
DE | 94 | L.J. Collier | TCU | 10.0 | 16.0 | 25 | 1.04 |
DE | 97 | Wyatt Ray | Boston College | 11.5 | 15.5 | 25 | 1.08 |
DE | 98 | Zach Allen | Boston College | 12.5 | 30.5 | 25 | 1.72 |
DE | 120 | Joe Jackson | Miami | 15.5 | 26.0 | 26 | 1.60 |
OLB | 121 | Justin Hollins | Oregon | 10.0 | 26.0 | 26 | 1.38 |
DE | 123 | Jaylon Ferguson | LA Tech | 24.5 | 35.5 | 25 | 2.40 |
DE/OLB | 130 | Oshane Ximines | Old Dominion | 20.5 | 32.5 | 24 | 2.21 |
DE | 140 | Anthony Nelson | Iowa | 17.0 | 23.0 | 26 | 1.54 |
DE | 165 | Malik Carney | North Carolina | 12.0 | 24.5 | 20 | 1.83 |
OLB | 167 | Sutton Smith | Northern Illinois | 29.0 | 46.0 | 27 | 2.78 |
DE | 178 | Ben Banogu | TCU | 17.0 | 34.5 | 27 | 1.91 |
DE | 198 | Maxx Crosby | Eastern Michigan | 18.5 | 35.5 | 24 | 2.25 |
DE/OLB | 208 | Jalen Jelks | Oregon | 10.0 | 22.5 | 25 | 1.30 |
DE | 231 | Byron Cowart | Maryland | 3.0 | 5.5 | 15 | 0.57 |
DE | 234 | Shareef Miller | Penn State | 12.5 | 26.0 | 26 | 1.48 |
DE | 240 | Jonathan Ledbetter | Georgia | 3.5 | 12.0 | 29 | 0.53 |
DE | 244 | Cece Jefferson | Florida | 5.5 | 19.5 | 22 | 1.14 |
DE | 252 | Austin Bryant | Clemson | 16.5 | 29.0 | 29 | 1.57 |
DE | 256 | Carl Granderson | Wyoming | 11.5 | 23.5 | 24 | 1.46 |
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.
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.
ATHLETICISCM 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 with a SPARQ score.
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. Eight edge rushers from this year’s draft class populate this quadrant, which suggests this may be a strong edge rusher class. However, only four of those prospects (Nick Bosa, Montez Sweat, Anthony Nelson, Ben Banogu) have the size to reasonably be seen as a fit for the Cowboys at DE, and Bosa and Sweat are out of reach for the Cowboys in this draft.
That leaves the Cowboys with just two A-quadrant options in this draft; good thing they got Robert Quinn.
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, this is probably not the draft for the Cowboys to go looking for a pass rusher. Perhaps they’ll have more luck at DT, which we’ll look at in the next post.
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.
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.