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Analysis of 2009 Draft; Thoughts on the Correlation of Stars

By NOLA Blue — January 22nd, 2010 at 3:57 PM — 19 comments
Filed under:
  • baseline talent
  • correlation with success
  • facilities
  • NFL draft
  • predictors
  • quality of coaching
  • stars
  • talent development
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After reading through, and enjoying, many comments on yesterday’s diary post I was driven to give more contemplation to the subject of “stars.”  The first premise derived from yesterday’s data is that a very, very small sliver of high school talent is of the caliber to even be recruited (currently, 0.23% of the talent-pool receives a scholarship to a Div 1-FBS school.)  Moreover, the top 0.1% of the talent pool would now include somewhere between 780 and 1002 high school seniors each year, depending on whether you are of the ilk that 70% or 90% of the top high school football players are seniors (or anywhere in between.)  Either way, this large number of players from within a very tiny sliver of a talent-percentile casts some serious doubt (in my mind) on the ability of scouts to truly differentiate among anyone outside of a football “prodigy.”  See yesterday’s post for a more comprehensive analysis of the “diminishing sliver.”

Among the comments were some great links posted by “Oregon_Alum,” credited to “mejunglechop and others” who had “brought this to the fore.”  The links (below; a couple of which had died before I had the chance to click on them) detail the success of “stars” in correlating to measurable outcomes.  I found the first article, from athlonsports.com, to be very convincing and well-stated.

http://www.athlonsports.com/college-football/16635/recruiting-the-nfl-draft
http://www.sundaymorningqb.com/2008/3/17/71811/4082
http://rivals.yahoo.com/ncaa/football/blog/dr_saturday/post/Hug-your-fri...
http://www.athlonsports.com/college-football/13422/nfl-stars-how-recruit...
http://www.sundaymorningqb.com/2008/1/21/1614/43228

The athlonsports.com article uses an analysis of the 2008 and 2009 NFL drafts to point out that the “stars” a player was previously given by talent scouts directly correlated with the likelihood of being drafted.  According to their data analysis of the 2008 draft, a player given that 5th star coming out of high school has a 40-48% chance of being drafted in the top 3 rounds; 4-star 9-11%, 3-star 3.6% and 2-star less than 1%.  And, giving more credibility to the college scouts’ “eye,” I found that the NFL scouts had a pretty good eye as well… 7 draftees from 2008 were subsequently selected for the Pro-bowl (I know I don’t need to say it, but that includes our very own Jake Long) with draft-order actually seeming to represent the spread of talent: 4 future Pro-bowlers in the 1st round, 2 in the second, and 1… well he went undrafted (apparently, even the NFL scouts miss one now and again.)  As a side note, these 7 elite players came from (in draft-order): UofM, Boise St., Tennessee St., East Carolina, Cal, Rutgers and Fresno St… I found that interesting.  Also: 4-star, 2-star, 4-star, 2-star, 5-star, 3-star, and 3-star… maybe the “chip on the shoulder” has a bit of a lasting effect.   I digress…

I cannot argue against “stars” correlating well with an eventual NFL selection, the numbers seem clear.  But, given that I am still leery of scouts’ ability to differentiate between non-prodigal high school players (3-17 players each year might be football prodigies, OK maybe 22… ) from within the top 0.23%, I am left questioning where such a correlation might stem from.  My initial theory is coaching and facilities (aka “player development”) as well as media exposure.

At this point my thought goes something like this…

I am currently studying tuberculosis in Moldova.  It is estimated that 1/3 of patients with an active case of TB will spontaneously resolve without treatment.  In contrast, somewhere between 60-65% of patients who undergo pharmaceutical treatment will be healed (note: that is a very low success rate for treatment, not applicable to those seen in the US… hence why I am here studying the system.)  But, let’s say that the infrastructure is overwhelmed and some people’s diagnoses are missed.  Those people will not be admitted to the facilities which (in this case) would have doubled their odds of survival.

So, in the football context:  a certain percentage of the high-school players (and I am not yet talking about the “prodigies,”) who continue on to play NCAA football, will someday develop into the mold of a potential professional player (likened to the cases of TB which spontaneously resolve.)  This is irrespective of their star-ranking, as well as exposure to coaching and facilities (likened to TB-treatment.)  In other words, there is a specific number of recruits from across the star-spectrum who are “destined” for a slot in future NFL draft; based on future physical and mental development, as well as intelligence, self-motivation and character.  This explains the numerous 2-stars we see drafted from the FBS subdivision each year, as well as the 22 players drafted from outside of the FBS subdivision in 2009.  Obviously, the baseline of “destined-success” is nowhere near 33% of all new college players.  My posit is that a longitudinal study would reveal a baseline of inherent draftability among players, measured by the success of Div 1-FCS players in achieving such outcome.  Granted, there are some great coaches and nice facilities in Div 1-FCS; but, the facilities’ levels could certainly be considered “basic” in comparison with those of Michigan, LSU, USC etc., while successful coaches are continually “poached” through the ranks to end up at… Michigan, LSU, USC etc.  Remember, FCS division players still come from the top 0.5% of high school football talent, and apparently this talent pool is still of high enough quality (in comparison with that of the FBS subdivision) to have accounted for 8.6% of the 2009 NFL draft.

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List of schools from outside of FBS represented in 2009 NFL Draft:

Abilene Christian**


Sam Houston St.

Cal Poly SLO


St. Paul’s College

Furman



Stephen F. Austin

Liberty



Stillman

McNeese St.


Tennessee St.

Monmout


Weber St.

Nebraska-Omaha


West Texas A&M

Nichols St.


W. Illinois

Norfolk St.


Western Ontario

North Dakota St.


William and Mary

Richmond







**Indicates 2 draftees


Perhaps this means that upwards of 20% of the NFL draft is filled with players that develop regardless of coaching and facilities.  8.6% of draftees came from approximately 11,500 FCS athletes, correlating to an expectation of an additional 10.5% to have come from the approximately 14,000 participants in the FBS subdivision.  How is the other 80% filled?

Well, my theory is that the other 80% is first filled by the correctly identified prodigies, with the remainder arriving in a disproportionate manner based on attending schools with the best facilities, the best coaches, and the most media exposure.  So, back to the star-system.  What is it truly correlated with?  Well, first, the talent scouts seem to correctly identify most of the prodigies; the 5-star ranking is sort of a highly sensitive measure with a poor selectivity (identifying 90% of the prodigies with a rate of false-positives hovering around 50%.)  This is why we see that 5-star ratings correlate so well with future success (in this case measured by draft-status.)  Secondly, the star-system is correlated to the student-athlete’s college destination.  As “Noahdb” pointed out (among yesterday’s comments,) most schools are using recruiting services as the preliminary filter.  I wouldn’t doubt that the 4 and 5 star kids, at positions of need, are given the first-looks by the big time schools (enter first source of data bias…)   It is also pretty obvious that the recruiting services freely modify recruits’ star-levels after seeing where the recruit is likely to commit (enter second source of data bias…)  These biases add up to meaning that the major, automatically qualifying BCS schools have classes filled with a disproportionate number of 4 and 5 star athletes (regardless of the actual talent of the athletes.)

If the star system was actually a predictor of success, then we should see that 4 and 5 star athletes are drafted from “big-time” schools at the same rate.  But, when analyzing the 2009 draft by universities the draftees are selected from, we see 4 university categories emerge:  Over performers, Average performers, Underperformers, and the dreaded Underperforming Outliers.

The Over-performers:  split into two categories, those who successfully recruited at least one player from the Rivals’ 2005 Top 100 and those who did not.

School


‘09 Draftees

      % of Total   

        Draftees

           2005

        Top 100

              Rate

         Proportion

Alabama


4

1.5625

2

1.28

Clemson


4

1.5625

1

0.64

Georgia


6

2.3438

4

1.706667

Iowa


4

1.5625

5

3.2

LSU


6

2.3438

3

1.28

Maryland


5

1.9531

1

0.512

Ohio St


7

2.7344

3

1.097143

Oklahoma

5

1.9531

8

4.096

Ole Miss


4

1.5625

2

1.28

Oregon


5

1.9531

1

0.512

Penn St


5

1.9531

2

1.024

S. Carolina

7

2.7344

3

1.097143

Texas


4

1.5625

3

1.92

USC


11

4.2969

9

2.094545

Virginia


4

1.5625

1

0.64

Wisconsin

4

1.5625

1

0.64

 

Of note: a randomized distribution of draftees would mean an average of 2.15 draftees taken from each FBS school (assuming none come from FCS, Div II, Canada, etc.)  Therefore, I have considered all teams which supplied 4 or more draftees to be over-performers.  The number of draftees from each is accompanied by the percentage of total draftees represented by that team.  For example, USC supplied 11 draftees, which was 4.3% of the total taken across all 7 rounds of the ’09 draft.  The numbers in the next column indicate the number of Rivals Top 100 recruits signed by each school in 2005; 2005 is the class with the biggest impact on the 2009 draft (although I concede the early attrition of juniors would be expected to affect the stability of this figure.)  The final column is a simple comparison of the % of Top 100 talent acquired in 2005 vs. the % of draftees produced in 2009.  If the top 100 recruits are truly more likely to be drafted, then the teams which acquire the highest % of them should produce a comparably disproportionate number of draftees.  A score above 1 indicates a team which is taking a high level of talent, but not matching that rate with NFL talent.  A score below 1 means the team is producing NFL talent at a greater rate than it is taking in top 100 talent; “0” would be the best possible score, meaning a team is producing NFL talent without the aid of any Top 100 recruits.

Speaking of ratio scores of “0,” the next set of draft Over-performers did so without taking a single top 100 recruit in 2005.

School


‘09 Draftees

          % Total  

         Draftees

           2005

        Top 100

                Rate

          Proportion

Cinci


6

0.023438

0

0

Georgia Tech

4

0.015625

0

0

Mizzou


6

0.023438

0

0

N. Carolina

5

0.019531

0

0

Oregon State

8

0.03125

0

0

Pitt


4

0.015625

0

0

Rutgers


5

0.019531

0

0

TCU


5

0.019531

0

0

Texas Tech

4

0.015625

0

0

U Conn


4

0.015625

0

0

Utah


4

0.015625

0

0

Wake


4

0.015625

0

0

 

Analyses of these two groups: 

There were 28 teams in total.  26 are from the automatically qualifying BCS conferences.  The other two are… TCU and Utah.

The first group of 16 teams produced a total of 85 draftees.  That is a rate of 5.3 draftees per team, for a total of 33.2% of all 2009 draftees.  In order to accomplish this feat, these 16 teams (13.4% of Div 1-FBS teams) signed 49% of the top 100 recruits in 2005, according to Rivals.

The second group of 12 teams produced a total of 59 draftees.  That is a rate of 4.9 draftees per team, for a total of 23% of all 2009 draftees.   These 12 teams (10.1% of Div 1-FBS) signed zero top 100 recruits in 2005, according to Rivals.

In other words, the first 16 teams signed an average of 3.1 recruits, each, from the top 100, and produced only 0.4 more draftees, each.  Remember there’s basically a 50% chance of a 5-star being a “prodigy”… the first 16 teams signed 14 of these athletes.  This means that 7 of their draft slots were due to the odds of a 5-star being a prodigy… therefore, their expected non-prodigal rate is 4.9 draftees per team (the same as the other 12 teams in the Over-performers category.)

In order of gross output:  the top performers are USC, Oregon St., Ohio St. tied with S. Carolina, followed by a four-way tie for 5th between Cinci, Georgia, LSU and Mizzou.  Ordered in terms of their “Rate Proportions:”  Oregon St., Cinci tied with Mizzou, Ohio St. tied with S. Carolina, LSU, Georgia and USC.  Based on this data, if I were looking for a coach I would look at Oregon St. (USC tried and failed,) Cinci (Notre Dame tried and succeeded) and Mizzou.

The Average-performers:  since we would expect 2.15 draftees per team after a random distribution, I considered those teams sending 2-3 draftees to the NFL as average.  I excluded teams which finished with 2-3 draftees but had at least 3 top 100 recruits in 2005 (they fall into the Underperforming Outliers.)

School


                        ‘09 Draftees

          2005

       Top 100

Abilene Christian

2


0

Arizona


2


0

Arizona St

2


0

Auburn


3


1

Ball St


2


0

Boston College

2


0

BYU


2


0

Cal


2


2

Florida


3


1

Fresno State

2


0

Hawaii


3


0

Illinois


3


1

Louisville


2


0

New Mexico

2


0

NC State


2


2

Purdue


2


1

Rice


2


0

San Jose St

3


0

Southern Miss

2


0

Syracuse


2


0

W Michigan

2


0

West Virginia

3


1

 

Analysis:  There were 22 schools which finished in the “Average” category, 12 are auto-qualifying BCS schools.  There were also 9 Rivals Top 100 athletes among these twelve schools, with 3 five-stars.

The Dreaded Under-performing Outliers:  The schools in this category have the distinction of having excelled in recruiting while performing average or below in producing 2009 draft prospects.

School


  ‘09 Draftees

         % Total   

         Draftees

           2005

        Top 100

                Rate

          Proportion

Florida St


1

0.003906

9

23.04

Miami


1

0.003906

5

12.8

Michigan


2

0.007813

7

8.96

Nebraska


3

0.011719

4

3.413333

Tennessee

1

0.003906

7

17.92

Texas A&M

2

0.007813

3

3.84

Va. Tech


1

0.003906

2

5.12

 

Analysis:  Seven schools, all from among the auto-qualifying BCS conferences.  I named this category as being outliers not because their proportional representation is sufficiently small to be a complete anomaly (5.9% of total Div. 1-FBS schools is a pretty large segment of the total.)  It is because each had its own set of circumstances leading up to the 2009 draft.  Michigan and Tennessee finished with uncharacteristically bad records (for different reasons,) same goes for Texas A&M, and who knows what happened with Florida St…. you would think that 9 recruits from the top 100 who helped piece together a 9-4 season would have been a sure-sell for a few more draft slots than 1.  Maybe Bowden really had lost his knack for coaching.

At any rate, these seven schools accounted for a whopping 37% of the Top 100 Rivals recruits in 2005; 10 of which were five-stars!  Four years later they combined for a horrendous showing at the draft:  11 draftees (4.3% of the total.)  Assuming the “50% of five-stars turn out to be prodigies” theory, 5 of the 11 drafts slots were a given, irrespective of coaches and facilities.  That means these seven programs could take credit for developing only 6 NFL caliber players.  Finally, according to the “rate proportions” Florida St. was the most colossal failure, followed by Tennessee and Miami.  I’ll stop there.

Conclusions:  After viewing three categories, we are left with the knowledge that in the 2009 draft, the 66 auto-qualifying BCS schools (67 with Notre Dame) split into 26 Over-performers, 12 Average, 22 Underperformers, and 7 Underperforming Outliers.  Among the Over-performers, there was no difference in draftee output (after 5-star talent was accounted for) between the group of 16 teams with a large representation (49%) of 2005’s top 100 recruits and the group of 12 teams with none of 2005’s top 100 recruits among them.  The impact of recruiting-stars took another hit when teams accounting for 37% of 2005’s top 100 talent combined for a miserable 4.3% of draftees in 2009.  Finally, 8.6% of the draftees in 2009 came from the Div 1-FCS subdivision.  This gives an initial estimate of 19.1% of draft-slots being accounted for by a baseline of players who will develop into NFL talent irrespective of differences in coaching, facilities and media exposure (and stars allotted to them.)

This has been an analysis of a single draft.  The data from the 2009 draft supports that while “stars” may correlate with draft success, it is likely a correlation due to “stars” predicting the collegiate destination of athletes as opposed to describing a differentiable talent level.  The two sources of bias aforementioned would suggest this possibility, as well as the fact that after accounting for 5-star athletes, the presence of “top 100” talent did not impact the NFL-production of universities with comparable levels of coaching and facilities.  In fact, a large concentration (37%) of “top 100” talent within 7 traditionally successful schools’ 2005 recruiting classes had no positive impact on the 2009 draft results.   I acknowledge the value of 5-star athletes; 50% of them are probably the much searched for football “prodigies” while the rest are just mis-rated and subject to the need for successful development.  I am not convinced that there is a discernible and/or long-term difference between 2-, 3- or 4- star athletes; rather, the appropriate coaching and facilities can turn any of these athletes into future NFL studs.

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January 22nd, 2010 at 4:43 PM | Iowa and Okl (Score:1)
Ziff72
Joined: 07/07/2008
MGoPoints: 5147

Didn't Iowa and Okl underperform in that they had more top 100 guys than actually drafted??

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January 22nd, 2010 at 5:00 PM | A question of Gross-performance vs. Efficacy (Score:1)
NOLA Blue
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Joined: 12/15/2009
MGoPoints: 389

Over-performers were selected on one criteria, with no provision for demoting them. If a team had at least 4 draftees I considered them an over-performer of creating draftable talent (sort of a gross measure... doubling the average makes them an over-performer.) Granted, among them there were those who required more top 100 talent to achieve this production; and the poor "rate proportion" definitely identifies them as having ineffectively utilized their 2005 talent. In a listing of "rate proportion" performances, they would definitely both rank near the bottom.

Fanatic since 1978.  Internet tough guy since 2012.

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January 27th, 2010 at 3:21 PM | coaching effect? (Score:1)
PartyonSybil
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Joined: 11/17/2009
MGoPoints: 2

I recently heard of a professor in Notre Dame's Business School that was using similar numbers (pre-college scouting rank, post-college draft rank) to determine the effectiveness of coaching staffs'. Interesting to think that over a number of years (say 5), some schools bring in a lot more high quality than come out of their program. Obviously there are probably a few other factors to consider, but on an aggregate basis these numbers probably say a lot about the effectiveness of the coaches that are in place and whether are not they are able to develop the talent which they recruit.

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January 22nd, 2010 at 4:47 PM | This looks awesome, but for (Score:1)
ameed
Joined: 07/01/2008
MGoPoints: 188

This looks awesome, but for now too long, head asplode - I will definitely read this when free time permits!

Thanks!

Excellence is Good

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January 22nd, 2010 at 5:16 PM | Love Your Work! (Score:1)
4roses
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Joined: 06/30/2008
MGoPoints: 14

Though it is a long read and makes the head spin a tad bit, it is very interesting.

One suggestion on trying to further test your theory. Compare the "success" (i.e. matriculation to the pros) of players within specific programs. Essentially, are the 5 & 4 star players at U of M (or OSU, USC, Fla, etc.) getting drafted at a higher rate that the 2 & 3 star players at the same institution? If your general theory is correct, then you would expect to see no major difference. Anecdotal evidence at U of M tends to suggest this is True: L. Hall, B Braylon, D. Harris, J. Long were not 5 stars (IIRC).

~ Geek/Band Fag/Michigan Man '92

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January 22nd, 2010 at 5:34 PM | But... (Score:1)
Rasmus
Joined: 07/02/2009
MGoPoints: 1006

Some of the 2005 class won't be in the draft until this year. The list includes Mesko, Moosman, and Ortmann, all of whom seem likely to sign with NFL teams, but I gather Mesko is the only one with a realistic shot at being drafted.

Manningham was also in the 2005 class but was drafted in 2008. Although in your data he's balanced out by Morgan Trent from the 2004 class who was drafted in 2009.

Since recruiting classes vary from year to year, I don't think you can say this averages out. If Michigan had had a strong group of redshirts in the 2004 class, that might have skewed the numbers one way. Instead, a weak group skewed them the other way. Anyhow, FWIW, Michigan's 2005 class will likely have three players drafted, not two: Manningham, Taylor, and Mesko.

Also note that the only 5-star in that class was Kevin Grady. So it would seem the biggest factor in having a highly-rated recruiting class underperform is having a 5-star fail to make the NFL draft. They are supposed to be the most likely to make it, so when one fails, it hurts the most.

[My apologies in advance if you discussed any of this and I missed it -- I may have read your post a little too quickly.]

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January 22nd, 2010 at 6:03 PM | True (Score:1)
NOLA Blue
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Joined: 12/15/2009
MGoPoints: 389

This is the "stability" issue I was referring to in regards to juniors leaving for the draft early (as well as 5th years leaving late.) Individual teams will definitely experience varying degrees and directions of wobble. I may at some point analyze the 2006 and 2007 drafts in the same way (which would average out the wobble on individual bases.) But, I still believe that the 2005 recruiting class, as a whole, has the largest impact on the 2009 draft.

Unfortunately for U of M, our 2005 class' pinnacle year was heavily impacted by a coaching transition which led to a series of transfers, and a 3-9 year... the outlying performance in the draft is just one more vestige of the transition.

Fanatic since 1978.  Internet tough guy since 2012.

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January 22nd, 2010 at 5:26 PM | "I am not convinced that (Score:1)
brax
Joined: 02/04/2009
MGoPoints: 62

"I am not convinced that there is a discernible and/or long-term difference between 2-, 3- or 4- star athletes; rather, the appropriate coaching and facilities can turn any of these athletes into future NFL studs."

I am not convinced that the analysis supports this conclusion. Without yet looking at the numbers, anybody want to bet me that a two star recruit at University X has a statisticly lower change of being drafted than a four star recruit at that same university? Analyzing players from the same school controls for coaching and facilities and would really test the hyothesis that there is no discernible difference between 2 and 4 star recruits.

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January 22nd, 2010 at 5:51 PM | Michigan has too few 2 stars (Score:1)
brax
Joined: 02/04/2009
MGoPoints: 62

Michigan has too few 2 stars to make a comparison meaningful but if you look at the 2002-2004 recruiting classes at MSU (accourding to ScouT), 2 out of five 4 star recruits were drafted while zero out of twenty-two 2 star recruits were drafted. Is that typical? I'm not positive but if I had to guess I'd say it is.

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January 22nd, 2010 at 7:07 PM | I think you are right... my (Score:1)
NOLA Blue
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Joined: 12/15/2009
MGoPoints: 389

I think you are right... my analysis did not support that statement. In fact, even with yesterday's numbers running through my head, alongside today's, the statement is unfounded. Good job in isolating its ill placement, and thank you for pulling on the reins.

I like the idea put forth by both you and 4roses; an analysis of 2, 3 and 4 star recruits from within the same university. It would definitely neutralize the effect of facilities and coaching. Your start on Michigan St. is good... I'm wondering how many draftees need to come from a University under the same coach to make sure the distribution has a chance to be random; and how many Universities need to be analyzed. I feel like the challenge is finding a university with a good spread of "stars" on the roster year to year, and a decent number of draftees over a coach's tenure. Maybe some of the consistent BCS-crashers? Boise, Utah, TCU?

Fanatic since 1978.  Internet tough guy since 2012.

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January 22nd, 2010 at 5:41 PM | Don't use percentages (Score:1)
MichiganAggie
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Joined: 11/10/2008
MGoPoints: 640

They're a bit misleading when trying to assess under/overperformers. For example, you list Texas A&M due to the disparity between the 2 percentages. It's better to look at difference-scores. So, for A&M it'd be a difference-score of -1 and Cincinnati would have a difference-score of +6.

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January 22nd, 2010 at 6:28 PM | Noted (Score:1)
NOLA Blue
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Joined: 12/15/2009
MGoPoints: 389

To clarfiy, Texas A&M is listed due to: they supplied 2 draftees, which is average. They had 3 top 100 recruits, which is 3x higher than the average.

I do see your point in using a difference score as opposed to a ratio of percentages to indicate efficacy; I wanted to keep away from insinuating that draftees were derived solely from the top 100 recruits. For most teams, the majority of their draftees did not come from 2005 Top 100 recruits... 5/7 OSU were not top 100, 6/11 USC, 4/5 Oklah, 4/6 LSU, 3/4 Wis, 3/4 Clemson, etc. Would assumption of this possibility have been blunted by a system deriving a score by the difference in T100 and Draftees?

Fanatic since 1978.  Internet tough guy since 2012.

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January 22nd, 2010 at 6:18 PM | Really appreciate the work, (Score:1)
Captain
Captain's picture
Joined: 06/12/2009
MGoPoints: 11602

you are fast becoming one of my favorite posters.

That said, I'm concerned some of the analysis is based loosely on an assumption that the 2005 recruiting class would be elevated (if at all) to the NFL in 2009. Unfortunately, I think some of the numbers suffer as a result of the 2009 NFL draft pooling largely from the 2004, 2005, and 2006 recruiting classes.

Colors That Float

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January 22nd, 2010 at 6:49 PM | Agreed (and thanks...) (Score:1)
NOLA Blue
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Joined: 12/15/2009
MGoPoints: 389

The wobble in the impact of 3 recruiting classes on each draft cycle will only be diminished upon analyzing successive drafts. Multiple draft cycles will have to be analyzed regardless, in order to elucidate other patterns (teams consistently over-performing, average impact of non FBS players, etc.)

Given this example: the 2009 draft is impacted by the classes of 2004-5-6 and the 2008 draft is impacted by 2003-4-5 and the 2007 draft is impacted by 2002-3-4. Using three classes to evaluate each one would mean using the 2002 and 2006 classes once, using the 2003 and 2005 classes twice, and using the 2004 class three times. I would have to modify the weight of each one, potentially differently for each draft it is used in; the preciseness of which could only be ensured by looking at the individual draft status of each team's members (how many 5th years, how many early Jrs., how many top 100s remain etc.) Faced with that... I chose to accept the imperfection of simply using the heaviest year. :^)

And lastly, thanks for the compliment!

Fanatic since 1978.  Internet tough guy since 2012.

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January 22nd, 2010 at 8:05 PM | I don't know if you are a data wizard, (Score:1)
Rasmus
Joined: 07/02/2009
MGoPoints: 1006

but if so it seems like it might instead be easier to construct (or find online) data that you could search using player's names to get the real numbers for each class, thereby eliminating the wobble. Basically just compile a data set of the names of players drafted in all possible years for any given class, then use regular expressions to throw all the names for each school in a given class together up against that.

Once you had your system down for doing this, you could analyze multiple recruiting years fairly quickly, I would think.

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January 22nd, 2010 at 6:40 PM | Quantity of star categories (Score:1)
AC1997
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Joined: 09/19/2008
MGoPoints: 878

I think the biggest difficulty in running these types of numbers is the quantity of players in each "star bucket".

If I dump 1000 apples in front of you and tell you to pick the best ten you're going to have a pretty good success rate on those. You are literally picking the best of the best and a very small number. I would argue that if I told you to pick the NEXT best ten you'd still be pretty good. But that's now how the distribution works for star rankings.

After you picked those first ten apples I would then tell you to pick the next best 100 - which starts to get pretty hard. The difference between apple #30 and #100 is pretty hard. Additionally, because the population size increased so much more the ratio of great apples within a larger population equates to a lower success rate. This gets worse and worse across lower star rankings because the population size grows so much.

I guess what I'm wondering is this - would you get a better idea of recruiting accuracy if you looked at positional rankings rather than star ranking?

And I LOVE the idea from "4roses" about tracking NFL success by program - meaning does a particular school put out more NFL players regardless of their ranking than another school.

In the end I think we know this - 5 stars are significantly more likely to succeed given that they're easier to find and there are so few of them. Four stars probably contain just as many players who will dominate, but they're buried in a much larger pool of players with that 4-star label.

AC-1997

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January 22nd, 2010 at 8:05 PM | good analyses (Score:1)
SysMark
SysMark's picture
Joined: 11/15/2008
MGoPoints: 5566

I like these analyses, particularly yesterday's. Sometimes the numbers can get a little overwhelming but I agree with the gist of it. While having 5-star type players is definitely one key to success, and you want them, in my opinion the real key with football is getting as many good players, mostly 3-4 star types, who fit the system you are working under, and are coachable. With football, as opposed to basketball, to be successful you need 25-30 starter caliber players with experience, and a pipeline behind them to sustain success.

Basketball involves far fewer and success depends on 3-4 key players with quality support. A couple of 5-star types can dramatically change a basketball team.

This is why I like what Rodriguez is doing and I hope he sticks with it. He is bringing in as many as he can with a high level of talent and ability that he believes fit his system and he can coach up. At some point the roster will fill up with his players, the experience level will match the talent, and the team could turn the corner very quickly.

A very good example of a team that does all of the above, but with mostly 2-star and lower rated players, is UConn, our next opponent (I live in Connecticut and see them a lot). Generally they have less talent than most teams they play but stay competitive because the players are there 4-5 years, know the system, and are well coached. Michigan, with Rodriguez, should be able to do all of the same things, with 3-4 star athletes, and reach an elite level. For that reason I think the UConn is going to be a very important barometer - Michigan should have the overall superior talent on the field and should win if they have progressed as a team. UConn won't just give the game away.

Call me an optimist.

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January 22nd, 2010 at 10:28 PM | Dude (Score:1)
Geaux_Blue
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Joined: 01/26/2009
MGoPoints: 20378

are you in the New Orleans Alumni group on Facebook? because we know each other guaranteed if you are.

which means you either like me, hate me... or think i'm just okay.

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January 25th, 2010 at 6:52 PM | Someone should look into (Score:1)
DoubleMs
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Joined: 10/13/2008
MGoPoints: 597

Someone should look into D-IAA students that are drafted, and why they are. Sometimes talent flies so far under the radar that nobody in D-1A sees it, and then it emerges in D-1AA (or even smaller) and dominates.

MGoGTI

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