This is the fourth post in our ongoing series on superior athletes in the 2018 draft (on DEs, DTs, and LBs). And by now you should know the drill:

First, we look at the college production of a specific position group. For the safeties, we’ll be using a metric based on production points (the metric is explained in detail in the post on linebackers), which looks at the key stats for safeties and weights them with a point system that gives you a single number showing how many production points a player averaged per game.

Then we match that with a metric for athleticism, 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).

Once we have those two metrics, we combine them to see which draft prospects emerge as the most productive AND most athletic.

All the caveats and provisos from the previous posts still apply, but there is one change we'll make for safeties and in the next post for cornerbacks: instead of looking at their production over the last two college seasons, we'll only look at each prospect's last and final college season. The reason for this is that almost half of all defensive backs in this draft class declared after their junior season (Derwin James even entered the draft after his official sophomore season), and many only became starters in their junior seasons.

The next table summarizes both the production and Sparq data we have for 24 safeties with a draftable grade according to the NFLDraftScout big board. The players are sorted by their rank on the same board. Players marked with an asterisk (*) don't have an “official” pSPARQ score per 3sigmaathlete.com because they did not complete all the drills required to calculate the score, but we estimated their Sparq score by using the position average to fill in the missing drill results (the formula I use to estimate a player’s Sparq score delivers results very close to Zach Whitman’s but the results are not identical).

The table is sortable, so you can see who ranks where for each category (just click on the blue column headers):

Player Details Production SPARQ POS Rank Player School Proj. Rd Ht Wt Prod. Pts/game pSPARQ z.Score NFL% SS 11 Derwin James Florida State 1 6-3 215 13.4 130.9 1.2 87.6 SS 33 Ronnie Harrison Alabama 1-2 6-3 214 9.3 -- -- -- FS 59 Justin Reid Stanford 2 6-1 204 13.1 134.2 1.7 95.5 SS 67 Marcus Allen Penn State 2-3 6-2 202 8.8 126.7 0.9 82.9 FS 81 Rashaan Gaulden Tennessee 2-3 6-1 197 9.8 99.1 -1.8 3.5 SS 96 Terrell Edmunds Virginia Tech 3 6-2 220 10.2 138.9 1.9 97.2 FS 104 Jessie Bates Wake Forest 3-4 6-2 195 11.0 116.2 -0.1 46.2 SS 113 Dane Cruikshank* Arizona 3-4 6-1 206 10.7 124 -- -- FS 125 Jordan Whitehead Pittsburgh 4 5-11 195 9.0 110.3 -0.7 24.5 SS 131 Kyzir White* West Virginia 4 6-2 216 13.5 117 -- -- FS 140 Godwin Igwebuike Northwestern 4-5 6-0 205 10.4 135 1.8 96.2 SS 149 DeShon Elliott Texas 4-5 6-2 205 15.3 115.9 -0.3 39.6 FS 166 Quin Blanding Virginia 5 6-2 215 14.5 111.4 -0.6 28.2 SS 173 Troy Apke Penn State 5 6-2 198 7.2 147.0 2.7 99.6 SS 200 Trayvon Henderson Hawaii 5 6-0 208 8.5 132 1.3 89.6 SS 218 Siran Neal Jacksonville State 6 6-0 199 7.4 123.3 0.4 67.1 SS 238 Tre Flowers Oklahoma State 7 6-3 200 9.9 116.5 -0.2 42.1 FS 239 Armani Watts Texas A&M 7 5-11 205 13.2 -- -- -- FS 249 Natrell Jamerson Wisconsin 7 6-0 198 8.3 123.3 0.6 72.9 SS 261 Damon Webb Ohio State 7-FA 5-11 195 8.5 -- -- -- FS 279 Joshua Kalu Nebraska 7-FA 6-1 195 9.9 134.2 1.7 95.6 FS 299 Sean Chandler Temple 7-FA 6-0 190 9.8 94.5 -2.3 1.2 SS 322 Tracy Walker Louisiana-Lafayette 7-FA 6-2 200 11.8 112.5 -0.6 28.2 FS -- Tarvarius Moore* Southern Miss 3 6-2 190 12.0 130 -- --

PRODUCTION

For safeties, 11 or more production points indicate a strong track record of college production, and anything above 14.0 is exceptional.

Having said that, we can’t look at production points in isolation, but need to add some context to these numbers. We need to factor in the type of role each player had in college. Some players played both corner and safety during their college careers. Others played more of a hybrid linebacker/safety role, others yet again spent more time in deep center field than in the box - all these things affect a player’s college production, but you can't see all of that by only looking at numbers. Which is why production points and Sparq are two tools out of many more that can help in the final evaluation of a prospect.

Overall, the standouts in terms of production points here are DeShon Elliott (15.3) and Quin Blanding (14.0).

Elliott exploded onto the scene in 2017, his first year as a starter for the Longhorns, excelling against the pass (6 INTs, 9 PBUs, 1.5 sacks) and against the run (63 Tkls, 8.5 TFLs). He was used interchangeably as a deep coverage safety as well as a blitzing box safety.

Blanding never recorded less than 115 tackles in any of his four college seasons, and capped his college career with a strong 2017 season (137 Tkls, 4 INTs, 2 PBUs, 3.5 TFLs). Blanding is projected as a day three pick due to questions about his athleticism.

Behind Elliott and Blanding, we have a group of seven prospects with above average production, including the top safety in the draft, Derwin James.

Of particular note: four of the eight safeties with above average production either had a top 30 visit with the Cowboys, had a private workout with the Cowboys, or attended Dallas Day.

Here's an overview of the safeties the Cowboys have shown a particular interest in. All six are marked in green in the tables above and below.

Player School Ht Wt Proj. Rd Cowboys interest Terrell Edmunds Virginia Tech 6-2 220 3 Top 30 visit Tarvarius Moore Southern Miss 6-2 190 3 Top 30 visit Kyzir White West Virginia 6-2 216 4 Top 30 visit DeShon Elliott Texas 6-2 205 4-5 Dallas Day Tracy Walker Louisiana-Lafayette 6-2 200 7-FA Top 30 visit Joshua Kalu Nebraska 6-1 195 7-FA Priv. workout

These six players all rank among the top 14 in terms of production points. You might think that's is a simple coincidence, and it well might be, but we know that the production points method is similar to what the Cowboys use to evaluate their defensive players, so perhaps it's not such a coincidence after all.

ATHLETICISM

Moving on to SPARQ, our list of safeties is reduced from 24 to 21 players, as there is no Sparq data available for three of the 24 players.

The graph provides a visual representation of what happens when we plot production points against the SPARQ score for 2018 safety class.

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 with questions regarding their athletic ability. The A quadrant (top right) contains 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.

Overall, this looks like a strong draft class for safeties, especially considering that safeties tend to get picked relatively late in the draft, as they are undervalued relative to some of the more premier positions. While only three players show up in the A-quadrant, quite a few more are borderline A-quadrant players, narrowly failing to surpass one of the red lines in the graph. Keep in mind that these lines are somewhat arbitrarily drawn - while they represent the averages at the position, there is no hard data confirming that the threshold for NFL success is at exactly that point.

Derwin James headlines the trio of prospects in the A-quadrant (as he should, considering he's being projected as a top 10 pick). Justin Reid, widely seen as a second-round prospect, ranks similarly to James. The surprise here is Tarvarius Moore, a player many didn't have on their radar until very recently. Moore wasn't quite as productive as James or Reid, but the graph likely undersells his athleticism. Here's how Moore and James compare in their athletic markers.

40 yard dash 10-yard split Bench press Vert. jump Broad Jump Short Shuttle Three cone Sparq Derwin James 4.47 1.55 21 40.0 11'0" 4.34 7.34 130.9 Tarvarius Moore 4.32 1.60 14 39.5 11'1" 4.20 6.89 130

Try as a might, I can't find the 10-yard split or the bench press reps for Moore, which is why he doesn't have an official Sparq number. To arrive at an “estimated Sparq” for Moore, I plugged in the position averages (1.60 seconds, 14 reps) for the two missing drills into a version of the Sparq formula that I have, which gave me a Sparq of 130. If I were use James' 1.55 seconds and 21 reps for Moore, I'd end up with a 134 Sparq, which is probably the high end of Moore's athleticism. Very impressive.

The Cowboys are definitely interested in safety this year, but given their priorities at other positions, safety will likely be a mid- to late-round pick. The question then becomes, will they be able to get a talent that is better than what they already have on the roster? If they look at some of the A-quadrant or borderline A-quadrant players, the odds of that happening will likely increase.

The Cowboys may even want to invest two picks at safety to take advantage of this strong safety class. A little competition never hurt anybody, and investing an extra late-round pick in a safety is going to be a lot cheaper than signing an ageing veteran.

Again, there’s not a lot of historic SPARQ data around, but these are the numbers I could get my hands on for safeties.

For most other defensive positions, we’ve seen a stronger correlation between production and athleticism when looking at successful NFL veterans. This may be due to the unique situation of the position as outlined above, may be the result of the limited number of historic players available, or it may indicate that the model simply does not work as well for safeties.