The Race for the Number One Recruiting Class

Thanks for putting this together.  Since you already did all this work, I hope you don't have to go into hibernation again to come up with an update next week after National Signing Day.

Great work, Mathlete.  I like the reasoning behind each approach you provide, helps out a lot.  I'm curious if I'm missing something about Texas A&M...33 commits?  Wow, didn't take them long to assimilate to the SEC.  Are they really losing that much to graduation and/or declaring early?  The current roster shows less than 20 seniors.

And finally:  Re: Sparty...."the peak is significantly lower and the decline is even faster"

From your fingers to God's ears, my friend.

Really love the recruit ratings vs Nth best recruit plots...was wondering how someone could come up with a quick visual to show something like this, and this perfectly shows it off. Nice work!

Always good to get a few different cuts of the data with different analytical approaches. Insightful as always.

I really like those graphs you used to compare class depth and quality. Very cool.

Jaylon Smith is going to be nasty. At least we'll only see true freshman/sophomore versions.

This was amazing, nice work & thanks for putting it together.  I loved the Nth-rank way of looking at things.

The nth best approach reiterates the concept of this class being a deep collection of very good players.  Every player from spots 3-26 is top 5, so lots of depth.

Clearly reinforces the quality of OL with 4 of top 8 and the concerns with our WR talent given all 3 in the bottom 7 of position players.

Kudos to Hoke for a top 5 class.  Well done.

I love that Mike Valenti just said the other day that Ohio State's recruiting is "on a different level" than Michigan's.

Oh shit, I love this. I've tried some similar rankings in the past, so I know how difficult and time-consuming it is, and I absolutely love some of the decisions you made here (logging, comparing Nth best recruits, etc.). These are better than anything I did and better than anything I've seen others do.

It's interesting to me that according to Scout, Michigan's class is far and away #1, while the others have M between 5 and 7. Scout heavily weights recruits according to their position ranking, and Michigan has a ton of top 5 players at their position. I'm not sure it's a good way to do it, but Michigan looks nice at #1.

I wonder if finding the area under the curves on those graphs wouldn't be a good way to rank teams. It presumably would be a lot less work to calculate it on an ongoing basis. You could automate it and release it every week. I'd do it, but my calculus is beyond rusty.

Negligible differences between our class and Ohio's aside, this is another fantastic effort by Hoke & Co. I cannot wait until our overall roster values reach elite levels.

...that is both informative and impressive. You my friend are ranked #1 in recruiting class analysis! Thanks for info.

Hoke has really built this team from the inside out which is by far the best way to do it. If you go back thru the years the O and D line are your money makers.When other teams D players are on their backs and the QB is under the gun, thats where you win.Would not trade this class for anyone elses.

Just another idea for how to rank these teams.  In Cross Country (CC) you get points for your place, and the LOW score wins.  Your top 5 runners place counts toward your score and your next 2 runners can push runners from other teams back.  For example in a dual meet, a shut out occurs when you place your top 7 runners before the other team's #1 runner.  Your placements are 1,2,3,4,5,6,7 and your score is 1+2+3+4+5 = 15.  The other team's placements are 8,9,10,11,12,13,14 and their score is 8+9+10+11+12 = 50.  If you have more than 7 athletes on your team, they don't count in the scoring.

An advantage of this system is that it would take advantage of the depth of a class, as well as the top.  Highly rated players get few points, but a lower ranked player can really scuttle the ranking.  (Imagine if your CC team went 1,2,3,4,150.  That would be a score of 160.  Despite having the 4 best runners there, you --almost certainly-- wouldn't win.  I've seen a score as high as ~130 win the state meet, but that was a very close meet...#2 had only a point or 2 more.)

Adapting this to recruiting rankings is (relatively) simple.  We'd first need to determine what teams you care about and rank ONLY THOSE players.  Now there are two parameters that you'd have to set.  First, how many players contribute to a team's score.  (I'd probably start with 20.)  Next you'd have to determine how many players you want to cap the total class size at.  (25 seems reasonable to me).  Once you set this second threshhold, you can eliminate any players above that threshhold from your "scoresheet".

Lastly, you'll have to complete the teams who have less than 20 recruits.  Suppose there are 240 players on your scoresheet.  Because USC only has 14 players, they need 6 more to get to 20.  So you'd have to add in player # 241, 242, 243,...246 to their tally.  You'd also repeat this for any other team with less than 20 recruits (starting at #241 again).  From there it would be as simple as adding up places.

Are you using R to analyze this data?  The graphs look like R outputs.  Just curious because I'm taking an R Data Analysis class on Coursera right now.

However, I think the real measure of a class is how it stacks against the needs of the team. For example, if Bama already has 6 five star running back recruits, and they pass on one this year for a four star lineman where they need depth, is that not a better recruiting class for Bama.

The question is how to measure this: perhaps by extending the third method back three or four classes, and then getting a relative need ranking by position. This of course is further compicated by adding in base defensive and offensive scheme and associated desired depth levels by position.

So, for now I'll be happy just knowing we have a top 10 class, and we're really strong in the areas we have seen we need depth in (OL, RB, and QB).

Thanks for the hard work, Mathlete. I wonder - how hard would it be to input past class rankings into these formulas? I'd like to see how classes from four years ago and beyond would score in these formats. We could score schools on running four year segments and see of one of these would be a better predictor of a football programs success. I know there are other variables (coach's x's & o's ability, injuries, transfers, etc.), but I'm curious.

Thanks again.

Thanks for doing this, it is great!  Please update after NSD, if you find the time.

This is the best, most thoughtful, approach to team recruiting rankings I've seen on the web.  It addresses most of the points I've made in my various gripes about recruiting rankings in the past.  Great Work!

My thoughts:

The add-em-up approach is clearly inferior, despite it's popularity.  This approach lets the right side (tail) of the plot guide the rankings instead of the left side (top-end recruits), even though the left side is far more impactful.  It is weak not only in looking forward (opportunity cost), but backward - stable programs that don't need a full class are penalized. It's only virtue is simplicity.

The average-em-up approach is better and underrated in this conversations.  Teams have small classes not because they are "holding" scholarships but because they've already used them. (OR, in USC's case, scholarship penalties, but those are outliers).  I think small classes generally reflect stability, not conservativism.  The average method avoids the "stability penalty".  If you have no attrition and red-shirt everyone, you should have about 20 people per year -- few programs can attain that, but it wouldn't mean you're recruiting poorly compared to a 30 person class.

The player rank approach is great.  It does something I've been arguing for - which is to apply little or no benefit to the lower rated 'ends' of the recruiting class.  These recruits are just filling spots depending on team roster needs, not moving the needle between rated programs.

Finally, I disagree with the conclusion.  Michigan isn't 'certainly' a top 5 class - in your rankings it is 5th (player rank) or 7th (average rank).  With more elite recruits likely to commit to teams currently in the top 10 -- but not Michigan -- it is likely that Michigan moves down a bit.  It is a top 10 class, but probably not top 5, barring something unexpected.

I'm sure the Tigers or Wings would pay you good $$$ for a stat guy....