Illinois Football Recruiting Thread

[Illinicpa14]

Honestly I would have even went lower than top 50 year in and year out but this forum might have turned on me.lol We are in agreement and it is about consistency. As long as we don't have random 100th ranked classes twice in a five year period things will be fine. BB specializes in certain positions where the recruits are rated lower and he can develop them. Between his system and the transfer portal it is just all for the fans to have fun with year round more than anything. BB had richer recruiting avenues to work from with Wisconsin and Arkansas. If he can somehow bring in that talent every year than we are talking special things.....(already love where we are but growth is constantly raising the standard for this program)

This chain has been super helpful as someone who the past decade has really only followed Basketball closely.

I realize we are making great strides but just for context, when BB was rolling at Wisconsin competing for titles every year, were his classes significantly better?

 

[aaeismacgychel]

yeah the more commits a team has, the fewer points 247 "awards" a team for adding another recruit at the same position.
Example. DL1 is a .90 and worth 10 points. DL2 is a .88 and worth 8 points. DL3 is a .87 and worth 7 points, and DL4 is a .86 and worth 5 points.
Say DL1 and DL2 both commit to Illinois. 247 adds 10 points for DL1 and then 8-ish points for DL2. There's a cutoff point; I haven't gone in depth or ran the numbers, but at some point if DL3 commits to Illinois 247 will only add a fraction of the recruits base points.
So DL1 + DL2 might give Illinos about 18 points, but if DL3 and and DL4 also commit to us, the total points for those 4 players might only be 23. There's diminishing returns.
Also if a player is "unranked" they don't add any points.;

I took some time playing around deriving the formula 247 composite sports uses and I'm about 99.9% sure it's simply the following that each player contributes:

=100*(x-0.7)*e^{-0.5*[(n-1)/9]^2}

Where x is the individual player's rating and n is the nth best recruit they are that you have recruited. As an example, Zafir Stewart has a composite rating of 0.8578 and is considered our 9th best recruit. If we put those in the formula I posted for x and n respectively, you get:

Stewart Contribution=100*(0.8585-0.7)*e^{-0.5*[(8-1)/9]^2) = 11.71, which is indeed his contribution to our overall composite score.

This can be replicated for each of our 11 recruits thus far and it comes out exact, so unless there's something additional going on where that 9 value changes, I'm fairly certain this is the formula and as such it doesn't take into account position as you assert. Our total score is simply the sum of these contributions.

 

[Mr. Tibbs]

This chain has been super helpful as someone who the past decade has really only followed Basketball closely.

I realize we are making great strides but just for context, when BB was rolling at Wisconsin competing for titles every year, were his classes significantly better?

his teams were usually ranked around 32-46

typically 2-3 four star players and the rest 3*.
he found the type of guys he wanted then, pretty much as he is now . we really can’t expect things to be much different now.

can we be marginally better ? perhaps . we will never really be able to be in the top 4-5 in recruiting in the conference , esp after this year

 

[illinidarrin]

https://twitter.com/i/web/status/1673126461610287105

 

[mhuml32]

View attachment 26795

what is Pat Ryan telling this recruit about IU? give me you best quote:

They're going to need a new head coach this winter

 

[mhuml32]

I was surprised too. Which tells me a lot about how the staff views him.

Or views the TE room.

 

[mhuml32]

I think Bret likes grabbing what he thinks are athletic / versatile high school tight ends and with some , then seeing if they can either turn them into tackles or some other position of value

Is this true? I can't think of a single tackle brought in under Bielema that fits the mold of being an athletic but big TE so we'll try him on the offensive line. Thought that was more Lovie/Rod's approach (for reasons that fit their offensive scheme).

 

[mhuml32]

Werner is setting the over/under commitment threshold as Green, Reynolds, Hollinger, and Capka-Jones (23). Getting 1-2 more beyond that would be preferred, as the remaining names are the contentious battles with in-conference peers or national recruits.

 

[Illini92and96]

I took some time playing around deriving the formula 247 composite sports uses and I'm about 99.9% sure it's simply the following that each player contributes:

=100*(x-0.7)*e^{-0.5*[(n-1)/9]^2}

Where x is the individual player's rating and n is the nth best recruit they are that you have recruited. As an example, Zafir Stewart has a composite rating of 0.8578 and is considered our 9th best recruit. If we put those in the formula I posted for x and n respectively, you get:

Stewart Contribution=100*(0.8585-0.7)*e^{-0.5*[(8-1)/9]^2) = 11.71, which is indeed his contribution to our overall composite score.

This can be replicated for each of our 11 recruits thus far and it comes out exact, so unless there's something additional going on where that 9 value changes, I'm fairly certain this is the formula and as such it doesn't take into account position as you assert. Our total score is simply the sum of these contributions.

Dude, I’m decent at math but how the heck did you reverse engineer that??

 

[illini0440]

I'm surprised they went for another WR. Someone has to be on their way out right?

One of the positions were thinnest at sooo not surprising

 

[Simeon Rice]

Werner is setting the over/under commitment threshold as Green, Reynolds, Hollinger, and Capka-Jones (23). Getting 1-2 more beyond that would be preferred, as the remaining names are the contentious battles with in-conference peers or national recruits.

Unfortunately, that list is mostly the ones that we're really not competing against top competition. Hopefully, we can land some of the more sought-after targets

 

[aaeismacgychel]

Dude, I’m decent at math but how the heck did you reverse engineer that??

It won't be as impressive after I explain it, lol, but the major things I had to go on is that 24/7 claimed they used a gaussian distribution formula and that they ordered the recruits such that a school's top recruit was weighted 100% with each ensuing next top recruit getting weighted less. And it also greatly helped that I knew the answer to what the contribution of each athlete needed to be thanks to 24/7's class calculator.

A Gaussian function has the following form:
f(x)=A*e^{-.5*[(x-B)/c]^2}

Based on the fact that we know the top recruit for a given school is weighted 100%, that means the decay part of the function goes to e^0. So A is fairly easy to figure out since you know the contribution and rating of your top recruit. And when looking at a few schools to figure out how they got A from the recruit's rating, it became very apparent that A was just that recruit's rating minus 0.7 and multiplied by 100.

Similarly, knowing that there is an e^0 term for the first recruit, you know x-B equals 0 when x is 1, so B is equal to 1. That means A and B are solved for and all that's left is solving for C.

Since you have 11 recruits and know what their contributions are, you just have a system of equations and it's straightforward to finding c is about equal to 3.0. And after looking at an additional team with more recruits, this held true.

So as I said, not so impressive if you know what a Gaussian function looks like based on the info they provided. I personally did expect it to be more complicated as was being suggested, but the basic equation just worked, so no additional investigation was necessary.

 

[illiniguy]

It won't be as impressive after I explain it, lol, but the major things I had to go on is that 24/7 claimed they used a gaussian distribution formula and that they ordered the recruits such that a school's top recruit was weighted 100% with each ensuing next top recruit getting weighted less. And it also greatly helped that I knew the answer to what the contribution of each athlete needed to be thanks to 24/7's class calculator.

A Gaussian function has the following form:
f(x)=A*e^{-.5*[(x-B)/c]^2}

Based on the fact that we know the top recruit for a given school is weighted 100%, that means the decay part of the function goes to e^0. So A is fairly easy to figure out since you know the contribution and rating of your top recruit. And when looking at a few schools to figure out how they got A from the recruit's rating, it became very apparent that A was just that recruit's rating minus 0.7 and multiplied by 100.

Similarly, knowing that there is an e^0 term for the first recruit, you know x-B equals 0 when x is 1, so B is equal to 1. That means A and B are solved for and all that's left is solving for C.

Since you have 11 recruits and know what their contributions are, you just have a system of equations and it's straightforward to finding c is about equal to 3.0. And after looking at an additional team with more recruits, this held true.

So as I said, not so impressive if you know what a Gaussian function looks like based on the info they provided. I personally did expect it to be more complicated as was being suggested, but the basic equation just worked, so no additional investigation was necessary.

 

[band camp]

It won't be as impressive after I explain it, lol, but the major things I had to go on is that 24/7 claimed they used a gaussian distribution formula and that they ordered the recruits such that a school's top recruit was weighted 100% with each ensuing next top recruit getting weighted less. And it also greatly helped that I knew the answer to what the contribution of each athlete needed to be thanks to 24/7's class calculator.

A Gaussian function has the following form:
f(x)=A*e^{-.5*[(x-B)/c]^2}

Based on the fact that we know the top recruit for a given school is weighted 100%, that means the decay part of the function goes to e^0. So A is fairly easy to figure out since you know the contribution and rating of your top recruit. And when looking at a few schools to figure out how they got A from the recruit's rating, it became very apparent that A was just that recruit's rating minus 0.7 and multiplied by 100.

Similarly, knowing that there is an e^0 term for the first recruit, you know x-B equals 0 when x is 1, so B is equal to 1. That means A and B are solved for and all that's left is solving for C.

Since you have 11 recruits and know what their contributions are, you just have a system of equations and it's straightforward to finding c is about equal to 3.0. And after looking at an additional team with more recruits, this held true.

So as I said, not so impressive if you know what a Gaussian function looks like based on the info they provided. I personally did expect it to be more complicated as was being suggested, but the basic equation just worked, so no additional investigation was necessary.

It's impressive AF. For real.

 

[spillini]

It won't be as impressive after I explain it, lol, but the major things I had to go on is that 24/7 claimed they used a gaussian distribution formula and that they ordered the recruits such that a school's top recruit was weighted 100% with each ensuing next top recruit getting weighted less. And it also greatly helped that I knew the answer to what the contribution of each athlete needed to be thanks to 24/7's class calculator.

A Gaussian function has the following form:
f(x)=A*e^{-.5*[(x-B)/c]^2}

Based on the fact that we know the top recruit for a given school is weighted 100%, that means the decay part of the function goes to e^0. So A is fairly easy to figure out since you know the contribution and rating of your top recruit. And when looking at a few schools to figure out how they got A from the recruit's rating, it became very apparent that A was just that recruit's rating minus 0.7 and multiplied by 100.

Similarly, knowing that there is an e^0 term for the first recruit, you know x-B equals 0 when x is 1, so B is equal to 1. That means A and B are solved for and all that's left is solving for C.

Since you have 11 recruits and know what their contributions are, you just have a system of equations and it's straightforward to finding c is about equal to 3.0. And after looking at an additional team with more recruits, this held true.

So as I said, not so impressive if you know what a Gaussian function looks like based on the info they provided. I personally did expect it to be more complicated as was being suggested, but the basic equation just worked, so no additional investigation was necessary.

 

[STLflyinIllini]

I took some time playing around deriving the formula 247 composite sports uses and I'm about 99.9% sure it's simply the following that each player contributes:

=100*(x-0.7)*e^{-0.5*[(n-1)/9]^2}

Where x is the individual player's rating and n is the nth best recruit they are that you have recruited. As an example, Zafir Stewart has a composite rating of 0.8578 and is considered our 9th best recruit. If we put those in the formula I posted for x and n respectively, you get:

Stewart Contribution=100*(0.8585-0.7)*e^{-0.5*[(8-1)/9]^2) = 11.71, which is indeed his contribution to our overall composite score.

This can be replicated for each of our 11 recruits thus far and it comes out exact, so unless there's something additional going on where that 9 value changes, I'm fairly certain this is the formula and as such it doesn't take into account position as you assert. Our total score is simply the sum of these contributions.

I have no idea what that means, ha, but yes messing around with the calculator it seems you are correct. Had just noticed when I entered certain players into the class calculator, other players' points went down. Guess I just assumed it was related to position instead of overall diminishing returns bc in my mind that would make sense. Maybe Werner over at Illini Inquirer could hire you to make a complex algorithm that includes positional redundancy, bc although I don't understand it, your explanation looks impressive.

 

[Joel Goodson]

It won't be as impressive after I explain it, lol, but the major things I had to go on is that 24/7 claimed they used a gaussian distribution formula and that they ordered the recruits such that a school's top recruit was weighted 100% with each ensuing next top recruit getting weighted less. And it also greatly helped that I knew the answer to what the contribution of each athlete needed to be thanks to 24/7's class calculator.

A Gaussian function has the following form:
f(x)=A*e^{-.5*[(x-B)/c]^2}

Based on the fact that we know the top recruit for a given school is weighted 100%, that means the decay part of the function goes to e^0. So A is fairly easy to figure out since you know the contribution and rating of your top recruit. And when looking at a few schools to figure out how they got A from the recruit's rating, it became very apparent that A was just that recruit's rating minus 0.7 and multiplied by 100.

Similarly, knowing that there is an e^0 term for the first recruit, you know x-B equals 0 when x is 1, so B is equal to 1. That means A and B are solved for and all that's left is solving for C.

Since you have 11 recruits and know what their contributions are, you just have a system of equations and it's straightforward to finding c is about equal to 3.0. And after looking at an additional team with more recruits, this held true.

So as I said, not so impressive if you know what a Gaussian function looks like based on the info they provided. I personally did expect it to be more complicated as was being suggested, but the basic equation just worked, so no additional investigation was necessary.

what's it like being a wizard?

 

[Illini92and96]

It won't be as impressive after I explain it, lol, but the major things I had to go on is that 24/7 claimed they used a gaussian distribution formula and that they ordered the recruits such that a school's top recruit was weighted 100% with each ensuing next top recruit getting weighted less. And it also greatly helped that I knew the answer to what the contribution of each athlete needed to be thanks to 24/7's class calculator.

A Gaussian function has the following form:
f(x)=A*e^{-.5*[(x-B)/c]^2}

Based on the fact that we know the top recruit for a given school is weighted 100%, that means the decay part of the function goes to e^0. So A is fairly easy to figure out since you know the contribution and rating of your top recruit. And when looking at a few schools to figure out how they got A from the recruit's rating, it became very apparent that A was just that recruit's rating minus 0.7 and multiplied by 100.

Similarly, knowing that there is an e^0 term for the first recruit, you know x-B equals 0 when x is 1, so B is equal to 1. That means A and B are solved for and all that's left is solving for C.

Since you have 11 recruits and know what their contributions are, you just have a system of equations and it's straightforward to finding c is about equal to 3.0. And after looking at an additional team with more recruits, this held true.

So as I said, not so impressive if you know what a Gaussian function looks like based on the info they provided. I personally did expect it to be more complicated as was being suggested, but the basic equation just worked, so no additional investigation was necessary.

Ah. I was trying a Seinfeldian equation. No wonder it seemed so complicated

 

[Lee]

I took some time playing around deriving the formula 247 composite sports uses and I'm about 99.9% sure it's simply the following that each player contributes:

=100*(x-0.7)*e^{-0.5*[(n-1)/9]^2}

Where x is the individual player's rating and n is the nth best recruit they are that you have recruited. As an example, Zafir Stewart has a composite rating of 0.8578 and is considered our 9th best recruit. If we put those in the formula I posted for x and n respectively, you get:

Stewart Contribution=100*(0.8585-0.7)*e^{-0.5*[(8-1)/9]^2) = 11.71, which is indeed his contribution to our overall composite score.

This can be replicated for each of our 11 recruits thus far and it comes out exact, so unless there's something additional going on where that 9 value changes, I'm fairly certain this is the formula and as such it doesn't take into account position as you assert. Our total score is simply the sum of these contributions.

 

[1m4tr]

It won't be as impressive after I explain it, lol, but the major things I had to go on is that 24/7 claimed they used a gaussian distribution formula and that they ordered the recruits such that a school's top recruit was weighted 100% with each ensuing next top recruit getting weighted less. And it also greatly helped that I knew the answer to what the contribution of each athlete needed to be thanks to 24/7's class calculator.

A Gaussian function has the following form:
f(x)=A*e^{-.5*[(x-B)/c]^2}

Based on the fact that we know the top recruit for a given school is weighted 100%, that means the decay part of the function goes to e^0. So A is fairly easy to figure out since you know the contribution and rating of your top recruit. And when looking at a few schools to figure out how they got A from the recruit's rating, it became very apparent that A was just that recruit's rating minus 0.7 and multiplied by 100.

Similarly, knowing that there is an e^0 term for the first recruit, you know x-B equals 0 when x is 1, so B is equal to 1. That means A and B are solved for and all that's left is solving for C.

Since you have 11 recruits and know what their contributions are, you just have a system of equations and it's straightforward to finding c is about equal to 3.0. And after looking at an additional team with more recruits, this held true.

So as I said, not so impressive if you know what a Gaussian function looks like based on the info they provided. I personally did expect it to be more complicated as was being suggested, but the basic equation just worked, so no additional investigation was necessary.

We have our math insider!!

 

[hooraybeer]

It won't be as impressive after I explain it, lol, but the major things I had to go on is that 24/7 claimed they used a gaussian distribution formula and that they ordered the recruits such that a school's top recruit was weighted 100% with each ensuing next top recruit getting weighted less. And it also greatly helped that I knew the answer to what the contribution of each athlete needed to be thanks to 24/7's class calculator.

A Gaussian function has the following form:
f(x)=A*e^{-.5*[(x-B)/c]^2}

Based on the fact that we know the top recruit for a given school is weighted 100%, that means the decay part of the function goes to e^0. So A is fairly easy to figure out since you know the contribution and rating of your top recruit. And when looking at a few schools to figure out how they got A from the recruit's rating, it became very apparent that A was just that recruit's rating minus 0.7 and multiplied by 100.

Similarly, knowing that there is an e^0 term for the first recruit, you know x-B equals 0 when x is 1, so B is equal to 1. That means A and B are solved for and all that's left is solving for C.

Since you have 11 recruits and know what their contributions are, you just have a system of equations and it's straightforward to finding c is about equal to 3.0. And after looking at an additional team with more recruits, this held true.

So as I said, not so impressive if you know what a Gaussian function looks like based on the info they provided. I personally did expect it to be more complicated as was being suggested, but the basic equation just worked, so no additional investigation was necessary.

 

[Illinois_2_AZ]

Slow morning- how many commits should we expect in the next 3 days??
Also, do any insiders know how the big shot targets enjoyed their visits?

 

[GILL-INOIS]

This chain has been super helpful as someone who the past decade has really only followed Basketball closely.

I realize we are making great strides but just for context, when BB was rolling at Wisconsin competing for titles every year, were his classes significantly better?

BB had classes in the 30s-40s at Wisconsin and 20s at Arkansas. He is a consistent recruiter/developer who has averaged in the 40s at Illinois so far. Overachieved in my eyes with the program that he was given.

Throw in the transfer portal and guys leaving so quickly the rankings are just a number for the fans to talk about in the offseason. Illinois will lose guys after next season, never know if anyone will back out of commit/not sign, etc. Illinois can have staying power if he keeps to past form and keeps landing or eventually develops solid QB play.

 

[cookie86]

So I guess we're not going to see any commits today?

 

[Illiniam1984]

https://twitter.com/i/web/status/1673374178626650113