In our ongoing series on superior athletes in the 2017 draft (on DEs, DTs, and LBs) we looked at a metric called SPARQ, which is a single number designed to summarize a player's athleticism. The number is calculated with a proprietary formula that incorporates player weight, bench press, broad jump, vertical jump, forty-yard dash, ten-yard split, short shuttle and 3-cone drill (details here).
In those four posts, we combined the SPARQ metric with a metric for the college production to see which draft prospects would emerge as the most productive AND most athletic. Today, we're turning our attention to cornerbacks and the metric we'll be using looks at the cornerback stats and weights them with a point system that gives you a single number which shows how many Production Points a player averaged per game (the metric is explained in detail in the post on linebackers).
The NFL is obsessed with athleticism. No matter how fast a defender might recognize or diagnose, no matter how diligently he plays with technique, if a prospective NFL athlete doesn't meet certain athletic thresholds, he has little chance of being drafted and no chance of making an impact. That's why front offices pore over certain measurables; they offer a sense of whether players have the raw athleticism to survive in a league that quickly and brutally exposes all but the most genetically gifted.
The following table summarizes both the SPARQ and the Production Points of the top 26 cornerbacks in the 2017 NFL draft along with their SPARQ scores, courtesy of Zach Whitman of 3sigmaathlete.com (click on the blue column headers to sort):
|Cornerback SPARQ & Production Points, 2017
|5||Marshon Lattimore||Ohio State||6-0||193||1||6.3||135.4||96.0|
|36||Gareon Conley||Ohio State||6-0||195||1-2||6.6||128.5||86.2|
|50||Adoree' Jackson||Southern California||5-10||186||2||7.8||125.8||79.5|
|113||Rasul Douglas||West Virginia||6-2||209||3-4||8.7||112.1||30.9|
|153||Corn Elder||Miami (Fla.)||5-10||183||4-6||9.9||104.4||10.8|
|175||Damontae Kazee||San Diego State||5-10||184||5||12.5||107.7||17.9|
|184||Jeremy Cutrer||Middle Tennessee||6-1||167||5||11.0||98.1||3.2|
|189||Marquez White||Florida State||6-0||194||5-6||4.0||109.8||23.6|
Note that the Production Points are based on the last two college seasons of each prospect. This can put prospects who had a very strong final season in college, or who weren't starters two years ago, at a disadvantage. I'll address this in more detail at the bottom of this post.
For cornerbacks, a Production Score of 8.5 is average, a score above 10.0 suggests very high college productivity, thus possibly foreshadowing future NFL success, and anything above 12.0 is exceptional.
In the table above, "NFL%" refers to the NFL positional averages and not to the draft positional averages. This means that a 50.0 percentile represents a player who rates as a league-average NFL athlete at the position. If you sort the table above by NFL% you'll see that this CB draft class includes some truly exceptional athletes, even compared to their NFL peers.
Kevin King, as measured by SPARQ, is the most athletic prospect in this class, and his 99.3 percentile is exactly the same as Jalen Ramsey's last year, and not far off from Byron Jones, who scored in the 99.9th percentile in 2015. Of the 26 top-rated corners in this draft, 12 players exceed NFL peer average with their athletic markers and 14 are below peer average. What's remarkable about this rookie class is that it's clearly split into two groups: the above average athletes scored in the 79th to 99th percentile, while the below average athletes scored from the 3rd to the 37th percentile. That's a huge gap between the 37th and 79th percentile without a single player.
The following graph provides a visual representation of what happens when we plot Production Points against the SPARQ score for the 26 prospects above.
The players marked in blue were all brought in for official pre-draft visits by the Cowboys.
Going clockwise from the top left of the graph, the C quadrant features players with a strong record of production at the college level, but who have questions regarding their athletic ability. The A quadrant (top right) shows the players most likely to succeed at the NFL level; they have a strong track record of production and combine that with the necessary athleticism to allow them to compete at the NFL level. The B quadrant (bottom right) shows superior athletes whose college production has been sub par, leaving scouts to question why this might be the case. The D quadrant (bottom left) is a nasty place for a prospect to find himself; it's where the guys sit whose college production and athletic markers are both below those of their peers.
Surprised at seeing Chidobe Awuzie as the standout A-quadrant player? Maybe you shouldn't be. Here's Rob Rang of CBS Sports on Awuzie and his fit in Dallas:
By allowing multiple members of their secondary to walk in free agency, it seems like that the Cowboys will address that position early and potentially often in the draft. For whatever reason Awuzie has not generated as much national attention as some of his peers at cornerback but some scouts feel he is the safest of this year's class, standing out on tape due to his quickness, anticipation and toughness, including in run support.
The A-quadrant looks rather empty with just two players (Awuzie, Griffin), but there are a few players in the B-quadrant who are borderline A-quadrant players (King, Jackson, Wilson). Also, for the other players in the B-quadrant, teams will need to understand whether a below-average production in college could be an issue at the NFL level. Marshon Lattimore and Gareon Conley for example, two of the highest ranked corners in this year's draft, played in an Ohio State defense that also featured likely top-10 pick Malik Hooker and projected second-round MLB Raekwon McMillan and allowed the third-fewest points in the nation last year. Maybe there simply wasn't much more production to be had in that system.
We know that the Cowboys prefer their corners to be long - at least 5'11", and preferably 6'0" or taller. So, just to see what happens, I'll limit my search to corners that are six feet tall or taller. If we do that, here's what the new graph looks like:
The graph clears up a little bit by limiting it to players six feet or taller. With this limitation, the A quadrant is comprised exclusively of players who score the scouting trifecta: they have length, production, and athleticism. Quadrants B and C are made up of players who exhibit two of these three desirable traits.
Another factor to consider when talking about the production of a given player in college is how many years of production you take into account. In previous exercises like this, I've always used the last college two years to calculate the production points, as I felt this provided a good measure of production over time. But taking two years may be a disservice to prospects that declared after their junior seasons, or prospects that had a standout season in 2016 but only a so-so season in 2015.
Which is why the next graph uses only the 2016 college production of each prospect for the Production Points:
The biggest winner here is Rasul Douglas, who jumps from 8.7 points to 14. Douglas had 8 INTs, 8 PBUs, and 70 tackles in his one season as a starter in 2016, but only 1 INT, 1 PBU, and 8 tackles as a backup the year before. Teams will have to decide which version of Douglas they'll get, the plus-sized corner who notched an FBS-best eight interceptions and earned First Team All-Big 12 honors in 2016, or the JuCo-transfer who played mostly special teams in 2015.
The same is true for Adoree' Jackson, who is an A-quadrant player based on 2016 only, and all other players who move up in the chart based on 2016 only.
Similarly, there are players like Sidney Jones (-1.8 points), Teez Tabor (-1.1) and others, whose production declined in 2016. Again, teams will want to understand the reasons for that slump in production, and whether it's relevant for their assessment of the player or not.
To ease your mind about the methodology used, here's a chart of some historic corners and how they would have fared in our evaluation. There's not a lot of historic SPARQ data around, but these are the numbers I could get my hands on. Note that I've had to change the scale on this chart compared to the charts above to accommodate some of the extraordinary numbers these players put up: