Draft Twitter Pre-Combine Top 100 Talent Gap Analysis

The Top 100 Project

The Draft Twitter Top 100 project is ever evolving.  Initiated to compile opinions of as many NFL prospect talent evaluators as possible to create an aggregate list, the Draft Twitter Top 100 project hopes to take another step forward with the upcoming Combine ballot.  The aggregate Top 100 NFL prospects compiled from the lists of the contributors will serve as the trigger point for Integrated Scouting where the composite knowledge base and discovery of a panel of scouts will try to normalize some of the conscious and unconscious biases that may skew one talent evaluator’s rankings.   Through aggregation of scouts of different backgrounds, philosophies and analytical methods, the DraftTwitter Top 100 hopes to establish a back-tested track record of sensible player rankings. 

The Value of the Talent Gap

In creating the DraftTwitter Top 100, it became clear there composition of the list would give rise to analysis of talent gaps, that is, which player positions are so stocked with talented prospects the value of each is somewhat diminished and which player positions may have only a couple of prospects that stand out above the others in their group, making them more valuable?

The ranking tell us which players are considered the best, but if the graded distance between a #1 player at any position is large, he is far more valuable than if 3 other players at his position were chosen over the next 10 spots.  

Once we assess how large this talent gap is for each position, it will give us an idea of how valuable a player really is once we consider other players who may be somewhat close to his talent level.

Looking at the Pre-Combine Top 100 (click through HERE to view), there are a few conclusions we can draw based on the aggregate rankings of 27 talent evaluators.

			Rankings
Position	# in Group	Average Score	Average Score Rank	Avg Score St Dev	PPPD	PPPD St Dev	FINAL SCORE	FINAL RANK
SS	5	44.35	7	1	3	1	3.00	1
FS	4	44.94	6	3	2	5	4.00	2
RB	8	47.93	5	4	8	3	5.00	3
ILB	3	55.69	1	8	1	12	5.50	4
OLB	6	54.55	3	10	7	2	5.50	5
QB	5	54.99	2	12	5	4	5.75	6
DE	11	49.74	4	2	10	9	6.25	7
TE	6	37.91	12	9	6	6	8.25	8
OT	7	38.62	11	7	9	7	8.50	9
DT	12	34.57	14	5	11	8	9.50	10
WR	11	39.94	10	6	12	11	9.75	11
OG	4	37.48	13	13	4	10	10.00	12
CB	16	43.56	8	11	13	13	11.25	13
C	2	40.91	9	14	14	14	12.75	14

Average Score

The evaluators were asked to list their Top 100 NFL draft prospects.  From those results, each player received points based on the following scale:  the #1 player received 100 points, the #2, 99 points and so on until the 100^th player received just 1 point.  An average score was then calculated.

Inside Linebackers received the highest aggregate rankings.   Although only 3, the group of Reuben Foster (#9), Jarrad Davis (#36) and Raekwon McMillan (#60) had an average ranking score of 55.69.

Defensive Tackles were the lowest aggregate ranked position.  Of the 12 members of the group, 8 fell below the 34.57 point average for the position.  Four members scraped the bottom of the rankings at #95, #96, #99 and #100.

Group size was not a factor in the above as the Defensive End group of 11 was in the top 4 in terms of position average while the Guard group of 4 was second to last.

Average Score Standard Deviation

Taking a look at the standard deviations of the average scores across each position group, we see the group with the widest distribution of average scores was the five man Strong Safety group.  They were smack dab in the middle of the Average Score rankings at #7 of 14, however, their scores varied the most with a Standard Deviation of 31.9.  With a group that currently includes Jamal Adams, Jabrill Peppers, Justin Evans, Obi Melifonwu and Eddie Jackson, it’s hard to imagine one or more of them will not move up the rankings after the upcoming Post Combine Ballot (please see the Shameless Self Promotion, below, for details)  and impact the Strong Safety group’s overall distribution.

Excluding the two man Center group, the 4  man Offensive Guard group’s St Dev at 16.9 points, is the lowest in the Pre-Combine Draft Twitter Ballot. 

Preceding Position Player Differential (PPPD)

The next part of the analysis looks at the difference between the scores of a player and the player taken before him.  If WR2 has a score of 82 and WR1 had a score of 90, the differential would be 8.  The analysis then averaged out the differentials and found the StDev of the same. 

The Inside Linebacker group had the highest PPPD of 27.79 points between players while the Cornerbacks had the lowest PPPD of 4.04 points (the 2 man Centers group was not included in this analysis).

PPPD Standard Deviation

Looking at the Standard Deviation for PPPD, the Strong Safety group is confirmed as having the largest distribution of 16.5.  In an interesting twist, the ILB group, which had the highest PPPD, was 12 of 14 in terms of their distribution as their  St Dev for PPPD was just 6.17.

The CBs remained 2^nd to last (again, ignoring Centers) with a StDev of 4.03.

Based on the table above, we can see which positions were valued most by the inaugural DraftTwitter Top 100.  Re-ranking the top 14 spots of our survey based on the above would result in the following talent gap weighted ranking:

1.    Jamal Adams (currently #3 in DraftTwitter 100)
2.    Malik Hooker (8)
3.   Leonard Fournette (5)
4. Takkarist McKinley (12)
5. Reuben Foster (9)
6. Deshaun Watson (15)
7. Myles Garrett (1)
8. O.J. Howard (13) 
9. Ryan Ramcyzk (16)
10. Jonathon Allen (2)
11. Mike Williams (7)
12. Dan Feeney (33)
13. Sidney Jones (14)
14. Pat Elflein (48)

Remember, these only consider the top player at each position. 

Shameless Self-Promotion!

The Post Combine Ballot will be available in a few weeks so please feel free to email me at boombearfootballmail to be added to the list of evaluators.

Also, go like the new Boombearjr Football Analysis Facebook Page  https://www.facebook.com/boombearjr/.

Ten Super Efficient Wide Receivers for the 2016-17 NFL Draft No One is Talking About

Return on Investment - A Measuring Tool 

In evaluating Receivers, it is tempting to use raw statistics as a measuring stick,  but how do you compare players stats for a WR in a run based system vs one in a more balanced or pass heavy system?  Is it sensible to just focus on the players with the most receiving yards or TD or both? 

ROI or Return on Investment is a simple way to approach to comparing production efficiency between receivers regardless of statistical volume. 

Quite simply, ROI compares the relationship between the rates of a receiver’s of targets, receptions and yards relative to the rest of the team and analyzes the numbers from an efficiency standpoint.  For more on ROI, please follow this link.

Until reliable FCS passing targets numbers circulate, ROI will be based only on receptions and yards. 

ROI Plus...

Of the 200 FCS receivers in terms of reception yards, we have reduced the list down to 10 draft eligible players who check the box on the following criteria:

Standard Deviation Range

Within 1 standard deviation of the average number of receptions for the Top 200 receivers in the sample (the average number of receptions was 57.9).

Reception to Touchdown Ratio

Had a Reception to Touchdown ratio that was better than the average of 1 TD per every 11.56 receptions.

Minimum Raw ROI

Raw ROI was above the 14.4% average (that is, each player generated greater than 14.4% more reception yards than their share of receptions).

Below Average QB Completion Percentage

Team pass completion % was below the 59.1% of all FCS teams (thus, the WR had to contend with statistically less accurate QBs).

Minimum Adjusted ROI

Finally, the receiver’s QB weighted ROI (which considers QB accuracy) is also above the 13.8% average.

Of the Top 200 receivers in FCS, only ten meet the above criteria.

Player	School	Recs	Yards	TDs	Recs /TD	% Team Recs	% Team Rec Yards	ROI	ROI/Avg	Team Comp %	QB Adj ROI
Deangelo Yancey	Purdue	49	951	10	4.9	15.7%	26.9%	71.1%	4.93	56.0%	73.8%
Josh Reynolds	Texas A&M	61	1039	12	5.1	23.9%	31.3%	30.9%	2.15	54.4%	35.3%
Josh Magee	South Ala.	49	822	5	9.8	21.0%	25.9%	23.3%	1.62	56.0%	26.1%
Tim Patrick	Utah	45	711	5	9.0	21.2%	25.2%	18.9%	1.31	53.1%	24.5%
Tanner Gentry	Wyoming	72	1326	14	5.1	34.3%	41.3%	20.6%	1.43	55.4%	23.9%
Austin Carr	Northwestern	90	1247	12	7.5	31.9%	39.1%	22.6%	1.57	58.4%	23.2%
Marcus Kemp	Hawaii	73	1100	8	9.1	28.4%	34.5%	21.6%	1.50	58.7%	21.9%
Jerome Lane	Akron	62	1018	6	10.3	28.6%	33.2%	16.3%	1.13	54.8%	20.2%
R.J. Shelton	Michigan St.	53	789	5	10.6	25.1%	29.6%	17.7%	1.23	57.0%	19.5%
Kenny Golladay	Northern Ill.	87	1156	8	10.9	37.5%	43.0%	14.7%	1.02	58.0%	15.6%
Top 200 Averages		58			11.6			14.4%		59.1%	13.8%

The Top 10

 DeAngelo Yancey:  He was consistently a top 10 ROI receiver this year.  Played on a team without a lot of success so fell through the cracks. Not only was he #1 in ROI (for WR's within 1 stdev of the Receptions average) but it took him less than 5 receptions to manufacture a touchdown in 2016.  For perspective, the projected WR1 Mike Williams from Clemson scored every 8.9 receptions. Overall receiving yardage leader Trent Taylor of Louisiana Tech scored every 11.3 catches. 

Josh Reynolds: I’ve been talking about him since he got to TAMU from JC – tough, confident and will outlast the DBs.  On a team that recruited so many top high school WRs, Reynolds was clearly the best wide out for the Aggies.  If I had to go into battle with one WR in this draft, this is my guy.

Josh Magee: Have to admit I knew nothing about him until this final run of the analytical model because his reception total must have risen above the minimum required for inclusion in the rankings.  Former MLB player who transferred from Alabama to UAB (to be close to home after his father became ill) to Southern Alabama (after UAB shut down their program), he has a lot of wear on the tires but that experience could come cheap if he’s invited in as an UDFA.

Tim Patrick: He was dominant in ROI for most of the year and then his reception total waned to up him under the minimum required for inclusion but he’s come back at the end of the year. Not flashy, but a big target who can come down with the ball.

Tanner Gentry:  After Josh Reynolds, I’m hitching my wagon to Tanner.  Just a tough guy who has a huge desire to win.  Played hurt most of 2015 before he had to shut it down early, he picked up where he left off last year where he was also a high ROI player.  Watch him in the Mountain West championship game hoist his team on his back to make play after play down the stretch to almost pull the upset.  The guy will grind and grind and grind.

Austin Carr: In 2015, Nebraska WR Jordan Westerkamp was a player I didn’t want to acknowledge as having the goods but he played so well week in and week out, I had to pay homage by making him my Twitter page banner.   In 2016, it was Carr who kept defying my assertion that he would fade away.  He never did fade and was actually one of the 3 Biletnikoff Award finalists.  Typically, ROI erodes as receptions increase beyond 1 standard deviation of the average but in this case, Carr has blown away that myth. Not sure where I would draft him and not sure how I think his career will go but he’s a quality man that will instantly give any team a locker room lift.

Marcus Kemp:  The scout who convinces his team to throw the dice on this man as an UDFA will end up a GM somewhere.  Kemp is the best kept secret out there at his position.  He is a tough, smart, experienced receiver who works to set up the DBs all game to exploit them once they think they know his next more.   He was possibly the only weapon Hawaii  had on offense yet defenses couldn’t stop this 1,100 yard gainer.

Jerome Lane:  Lane’s father Robert was a NFL LB and, although his son plays a different position, he has a similar fire and attitude to win.  Despite playing for an Akron team that struggled, he went over 1000 yards receiving and maintained well above average ROI.

R.J. Shelton: I have to admit, when Conner Cook went to the NFL, I kinda checked out of MSU.  Like Magee, I have not followed Shelton and will need to do some research before giving an opinion.

Kenny Golladay:  In 2015, I expected a receiver named Juwan Brescacin to start his senior year as the #1 option in the NIU receiving game.  His final year was stunningly silent due to the domination of a University of North Dakota transfer named Kenny Golladay who, for lack of a better term, ate Brescacin’s lunch. Kenny has been the go to guy at NIU and should be a nice pick up at the next level.

Shameless Self-Promotion!

I would love ideas on any "non-brand name" receivers from any division you might want reviewed in a future article.  Feel free to email requests to  boombearfootballmail.

Also, go like the new Boombearjr Football Analysis Facebook Page  https://www.facebook.com/boombearjr/.