2 and 3 Star Athletes: Drafted at Same Rate When Placed in Same Environment
I’ll post the results first, since I understand some people have jobs and spouses… reasons, methodology, discussion are all below.
In short, I analyzed 4 recruiting classes (2002-5) and the corresponding 5 NFL drafts (2005-9).
Likelihood of being drafted from Boise St, TCU and
Utah:
3-stars 8.00%; 2-stars 9.28%
Likelihood of being drafted from Cal, Iowa, Oregon, Va
Tech:
3-stars 12.99%; 2-stars 12.20%
The rationale for the use of these schools and their separate grouping is given below; grouping involves facilities and initial selection involves coaching stability. Also, the BCS schools (Cal, Iowa, etc.) will be used again in the soon to be posted analysis of 4-stars vs. 3-stars and the effect of 5-stars on their fellow teammates.
As you can see, there is no difference between a 2-star and 3-star athlete, as far as talent and potential can be measured by draft status. When placed in the hands of a capable coaching staff (all of the above universities) and a similar environment (BCS with high level of facilities, or BCS crasher with decent facilities) there is no appreciable difference in draft status. I now beg you all to stop bagging on our 2-star recruits, it not only shows a lack of respect but from this point forward will have to be considered a lack of basic comprehension. An analysis of 521 athletes ranked with 2- or 3-stars, and the subsequent 57 draftees to come from this pool, has proven the system flawed for 2- and 3-star athletes. Please feel free to refer anyone who remains ignorant to this fact here, so that they may either argue with the methodology or inform their thought process.
Now, to begin…
A few weeks back, I wrote two diaries (here and here) regarding the feasibility of recruiting services being able to dependably differentiate between athletes from the top 0.23% of high-school football players. (If you don’t need a refresher of the findings, please skip to the next paragraph.) The first post looked at the fact that the talent pool (number of total high-school football players) has grown each year consecutively since at least 1988, while the total number of active scholarships for football at NCAA Division 1-FBS schools grew at one-third the rate (fluctuating between 9,095 and 10,115 scholarships.) Scholarships available basically grew by 11%, while the pool of high-school football players grew by 31.6% over the same period. Thus, we see a shrinking percentile from which schools are drawing their talent (parity, anyone?) The second post was an analysis of the 2009 NFL draft, looking at the impact of “Rivals’ Top 100” athletes from the 2005 recruiting class on total draftee production. The results of the 2009 draft showed that teams could be broken down into 4 categories: those which produced at least 4 draftees, those with 2-3 draftees, and those with less than 2. Thus, when considering that a random spread of draftees across all Div 1 college teams would result in 2.15 draftees per team, it is easy to see that there are “over-performers,” “average-performers” and “under-performers” as far as draftee-production is considered. The other factor considered was teams’ acquisition of “Top 100” (Rivals) recruits in 2005: twenty-three of the nation’s college teams accounted for the signing of 86% of these athletes. Thus, there was a clear delineation between recruiting rankings: again “over-performers” and “under-performers.” The result of comparing these groups: there was no correlation between being a highly successful recruiter of “Top 100” talent in 2005 and producing NFL draftees in 2009. This was admittedly a very narrow slice to analyze… and yes, I had admitted that upfront.
So, after reading these diary posts there were many great comments and ideas put forth by the MGoBlog community. One idea in particular caught my attention: both “brax” and “4roses” suggested analyzing the correlation between stars and draft-status from among players placed in the same environment. This would be the only way to extract a correlation that accounted for, and negated, the recruiting services’ currently common practice of bumping up athletes’ star ratings after they commit to big-time BCS schools. The goal would be to isolate the effect of differences in coaching and training facilities to get a true bearing on recruits’ talent and potential, and whether or not “stars” actually peg innate talent/potential differences.
Right now the central argument of “star” supporters is “hey, look at the rate of drafting for 5 stars, 4 stars, 3 stars and so on…” True, there is a clear regression at work there. But, it does not necessarily speak to the star system predicting talent and performance; rather it is very likely that the stars are predicting which schools recruits go to. There is an obvious difference in facilities among schools, and there is clearly a shuffle of coaches that generally flows in one direction (towards U of M, Florida, Texas, etc.) This creates a potential gap in player development, and should heavily affect draft-status. If the administration of “stars” were to be biased toward awarding extra stars to recruits heading to big-time schools, then it would lose its validity as a measure of actual player talent and potential.
So, the analysis…
Idea: Cross reference players’ star-rating at time of signing day with their ultimate rate of selection to the NFL. Compare the rates for each star-level within a small sample of schools deemed to be similar.
Time Period: I retrospectively evaluated the star-ratings of players from four consecutive recruiting classes (2002-5.) Their draft-status was referenced to five consecutive NFL drafts (2005-9.)
Parameters: To be included in the 2-star vs. 3-star evaluation, a school has to have had a high-number of both 2 and 3 star recruits through the four recruiting classes; as well as a significant number of draftees over the five year period (in this case, Boise set the low bar with only 7 draftees over that period.) Also, in considering the pool of 2- and 3-stars, “kickers” were not included in the count.
Sample selection:
The first group is a group of three schools which consistently compete at a high level, without the benefit of BCS caliber facilities, and consistently place players into the NFL. They also have had stable coaching situations. For this pool of players, I examined Boise St, TCU, and Utah. I acknowledge Utah had the least stable coaching situation, considering Urban Meyer’s departure.
The second group comes from the larger pool of BCS schools with high draft-success. Thus, for teams taken from the BCS level, I had the luxury of being able to use a limiting-requirement of coaching stability; only schools with no head-coaching change between 2002 and 2009 were used. This reduced the available pool: Cal, Florida St, Georgia, Iowa, Ohio St, Oklahoma, Oregon, Penn St, Texas, USC, and Va Tech. For today’s comparison between 2- and 3-star athletes, the list is further pared down to the schools with a high number of 2- and 3-star athletes: Cal, Iowa, Oregon and Va Tech. This group is important because they have a high number of 4-star recruits as well; meaning they will be a bridge between the analyses of 2- vs 3- star recruits and 3- vs. 4-star recruits.
Data:
Boise |
Tot 4 |
Tot 3 |
Tot 2 |
1 |
9 |
76 |
|
4 Draft |
0 |
||
3 Draft |
1 |
||
2 Draft |
5 |
||
% |
0% |
11% |
7% |
TCU |
Tot 4 |
Tot 3 |
Tot 2 |
5 |
21 |
53 |
|
4 Draft |
1 |
||
3 Draft |
2 |
||
2 Draft |
7 |
||
% |
20% |
10% |
13% |
Utah |
Tot 4 |
Tot 3 |
Tot 2 |
2 |
20 |
65 |
|
4 Draft |
1 |
||
3 Draft |
1 |
||
2 Draft |
6 |
||
% |
50% |
5% |
9% |
Cal |
Tot 4 |
Tot 3 |
Tot 2 |
21 |
36 |
27 |
|
4-Draft |
5 |
||
3-Draft |
4 |
||
2-Draft |
3 |
||
% |
24% |
11% |
11% |
Iowa |
Tot 4 |
Tot 3 |
Tot 2 |
13 |
37 |
34 |
|
4-Draft |
0 |
||
3-Draft |
3 |
||
2-Draft |
7 |
||
% |
0% |
8% |
21% |
Oregon |
Tot 4 |
Tot 3 |
Tot 2 |
16 |
42 |
34 |
|
4-Draft |
1 |
||
3-Draft |
4 |
||
2-Draft |
4 |
||
% |
6% |
10% |
12% |
Va Tech |
Tot 4 |
Tot 3 |
Tot 2 |
17 |
39 |
28 |
|
4-Draft |
3 |
||
3-Draft |
9 |
||
2-Draft |
1 |
||
% |
18% |
23% |
4% |
Results:
BCS Crashers…
Tot 4 |
Tot 3 |
Tot 2 |
|
8 |
50 |
194 |
|
Draft 4 |
2 |
||
Draft 3 |
4 |
||
Draft 2 |
18 |
||
Tot % |
25.00% |
8.00% |
9.28% |
4-, 3- and 2-star Analysis of Cal, Iowa, Oregon and Va Tech…
Tot 4 |
Tot 3 |
Tot 2 |
|
67 |
154 |
123 |
|
4 Draft |
9 |
||
3 Draft |
20 |
||
2 Draft |
15 |
||
Tot % |
13.43% |
12.99% |
12.20% |
Discussion…
First, resist the temptation of looking at the drafting of 4-stars from the BCS crashers as legitimizing the star-system. Eight athletes from a four-year recruiting cycle does not bring nearly enough statistical power to make any claims. Therefore, do as I have done: ignore them. In the comparison of 3- and 4-star athletes we will look at a much larger sample size from schools which have enough 4-star recruits and NFL draftees to power a comparison. So, save those comments for that analysis.
Second, for those of you still reading this, I have included the 4-star data for the BCS teams; so you get an advanced view of the 3- and 4-star analysis. Pretty crappy reward for your reading efforts? Yes… but I appreciate those efforts nonetheless. :^)
Third, a bit of repetition… but with more definition. As you can see, there is no difference between a 2-star and 3-star athlete, as far as talent and potential can be measured by draft status. When placed in the hands of a capable coaching staff and a similar environment, there is no appreciable difference in draft status. We can see that while each school has a fairly large sample of 2- and 3-star recruits to analyze (among the schools considered, 81 per BCS-crasher and 69 per BCS) the number of draftees from an individual school would not allow enough power. Hence, the need to group the schools. I left the schools in two separate groupings because of two factors: one, it allowed a consideration of the effect of different facility levels on player development; secondly, the BCS group will be used as a bridge to the 3- vs. 4-star analysis.
We can see that the rate of drafting from the middle-echelons of the BCS for 2- and 3-star athletes is approximately 50% higher than the rate of drafting from the top echelon of non-BCS schools (12%-ish vs. 8%-ish.) I generally relate the BCS crashers’ success to the high-quality of coaching staffs they have assembled and been able to keep. It would be interesting to see if there is a large difference in facilities at these schools when compared to Cal, Iowa, Oregon and Va Tech. If the gap is minimal, then the difference in drafting above could be considered to have more to do with media exposure and proven play against higher-performing competition. It is an interesting question, and probably pretty difficult to investigate.
So, an analysis of 521 athletes ranked with 2- or 3-stars, and the subsequent 57 draftees to come from this pool, has proven the system flawed for 2- and 3-star athletes. I already made my feelings known at the start of the post, but I will say it again… please stop dismissing our 2-stars. It is obvious that they are just as likely to be contributors as our 3-stars, and as Michigan Men they deserve our support regardless of contribution.
Go Blue!
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