Recruiting Ranking and Results in 3-4 Years

#51
#51
Would it be better if I do a yearly chart like this?

Also, Teams that ended up not ranked were given a value of 50.

2008.jpg
 
Last edited:
#56
#56
After staring at it for a good 5 minutes, I'm going to go with ranking in the top 25 at the end of the year. Likely wrong though

If that's correct, then it looks like a lot of teams crashed and burned three and four years after pulling a highly ranked recruiting class.

Am I reading that right?
 
#57
#57
If that's correct, then it looks like a lot of teams crashed and burned three and four years after pulling a highly ranked recruiting class.

Am I reading that right?

Yes...I gave non ranked teams a value of 50 instead of non ranked
 
#58
#58
IOW's, recruiting svc rankings mean something but not everything... pretty much what I've been saying for awhile.
 
#59
#59
IOW's, recruiting svc rankings mean something but not everything... pretty much what I've been saying for awhile.

Still seems pretty interesting. What year did Rivals lose a lot of their analysts to 24/7 or ESPN or whatever?
 
#60
#60
So......basically you're sayin that the better talent a team has the more likely they are to perform well on the field..... Pretty sure everyone already knew that but thanks for making it official! :eek:k:
 
#61
#61
So......basically you're sayin that the better talent a team has the more likely they are to perform well on the field..... Pretty sure everyone already knew that but thanks for making it official! :eek:k:

I'm not necessarily saying that. I'm saying there's a general tendency, but that there's so much fuzz in the data that it's pretty worthless as far as using it to make an accurate prediction.
 
#62
#62
I'm not necessarily saying that. I'm saying there's a general tendency, but that there's so much fuzz in the data that it's pretty worthless as far as using it to make an accurate prediction.

Yeah I know, just given you a hard time.. :neener2:
 
#64
#64
I plan on making another graph showing more than one year. I just have a lot going on today and not a lot of free time.

(yet I have the free time to get on here and check this thread)
 
#68
#68
Appreciate the stats, and of course we all know numbers can be twisted to prove whatever argument you're making.

In the end, it's more than quantifiable qualities. There's so many other variables that go into success that's it next to impossible to project anything forward from the available data, though that won't stop most from trying.
 
#70
#70
Appreciate the stats, and of course we all know numbers can be twisted to prove whatever argument you're making.

In the end, it's more than quantifiable qualities. There's so many other variables that go into success that's it next to impossible to project anything forward from the available data, though that won't stop most from trying.

But some arguments are going to be better than others. :p
 
#71
#71
Essentially what is being said here is that win % and recruiting rankings, while related, are not everything. There are more variables effecting win % than just the recruits - which is obvious when you say it out loud.

So you analyze the same correlation with multiple variables (SOS, recruiting, etc...).

I would assume that if you took Win % of current coaching staff, SOS, and recruiting rankings and used those variables to predict win %, you would have a very high correlation.

This isn't rocket science, it just looks more complicated than it really is. Thus the saying, lies, damn lies, and statistics.
 
#72
#72
Essentially what is being said here is that win % and recruiting rankings, while related, are not everything. There are more variables effecting win % than just the recruits - which is obvious when you say it out loud.

So you analyze the same correlation with multiple variables (SOS, recruiting, etc...).

I would assume that if you took Win % of current coaching staff, SOS, and recruiting rankings and used those variables to predict win %, you would have a very high correlation.

This isn't rocket science, it just looks more complicated than it really is. Thus the saying, lies, damn lies, and statistics.

To respond, I'll just copy/paste what I posted on another forum...

My goal is to build in some factors that may help increase the resolution of the prediction like...
-a school's historical win percentage
- the head coach's historical win percentage
- some kind of road game/strength of schedule factor.

For example, a road win for Vandy (with a historically low win%) against Alabama (with a historically high win%) coached by Nick Saban (who has a historically high win%) at Alabama is going to be tough to come by.

So, each of these factors alone wouldn't be that valuable, but when you stack them all together in a multiple linear regression, it might have some pretty good predictive value.
 
#74
#74
you dont needs charts or math to see how bad are 2007, 2008 and 2009 classes were... its pretty easy to see why we went 11-14 the last two seasons
 
#75
#75
you dont needs charts or math to see how bad are 2007, 2008 and 2009 classes were... its pretty easy to see why we went 11-14 the last two seasons

Nope. But running the numbers (rather than going off intuition) can more clearly illustrate the depth to which we've been screwed by those busts.
 

VN Store



Back
Top