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Official 2023 Fall Camp Thread

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If models are so worthless/controversial, why do Vegas and pro gamblers use them
so much?
It's not models itself but rather the inputs and assumptions and data controls used in them.

How is Manhattan's model accounting for schematic changes, especially for a new coach? What assumptions are being made there? How about changes in competition? Is it the same playing in the SEC v Pac 12?

MB needs to provide data to support his model being able to actually model CU here.
 
It's not models itself but rather the inputs and assumptions and data controls used in them.

How is Manhattan's model accounting for schematic changes, especially for a new coach? What assumptions are being made there? How about changes in competition? Is it the same playing in the SEC v Pac 12?

MB needs to provide data to support his model being able to actually model CU here.
That's accounted for by the teacup of marbles.
 
It's not models itself but rather the inputs and assumptions and data controls used in them.

How is Manhattan's model accounting for schematic changes, especially for a new coach? What assumptions are being made there? How about changes in competition? Is it the same playing in the SEC v Pac 12?

MB needs to provide data to support his model being able to actually model CU here.
Why the f would MB need to provide that?
 
It's not models itself but rather the inputs and assumptions and data controls used in them.

How is Manhattan's model accounting for schematic changes, especially for a new coach? What assumptions are being made there? How about changes in competition? Is it the same playing in the SEC v Pac 12?

MB needs to provide data to support his model being able to actually model CU here.
1. Schematc changes on their own are not as important to offensive player predictions since my model rates usefulness on a per pay basis. The model does account for plays per game, which is the critical statistic. There’s ample evidence in the model from Kent State and similar offenses to help predict per game play counts.
2. Defensive players are modeled on a usefulness per play basis in all schemes. The key variable we’ve found is the number of offensive plays, not the defensive scheme.
3. Competition is assessed by opponent inputs. My model rates every player. A productive player against other productive players has a higher rating than a productive player against less productive players.
4. My model does not apply only to Colorado. It applies to every team in FBS. We rate FCS players after their season concludes for transfer purposes only.

My inputs and analtytical choices are carefully designed to be as accurate as possible since the predictions generated are attached to actual wagered dollars. My models in American College Football and European Football have beaten sportsbooks every year for over a decade.
 
1. Schematc changes on their own are not as important to offensive player predictions since my model rates usefulness on a per pay basis. The model does account for plays per game, which is the critical statistic. There’s ample evidence in the model from Kent State and similar offenses to help predict per game play counts.
2. Defensive players are modeled on a usefulness per play basis in all schemes. The key variable we’ve found is the number of offensive plays, not the defensive scheme.
3. Competition is assessed by opponent inputs. My model rates every player. A productive player against other productive players has a higher rating than a productive player against less productive players.
4. My model does not apply only to Colorado. It applies to every team in FBS. We rate FCS players after their season concludes for transfer purposes only.

My inputs and analtytical choices are carefully designed to be as accurate as possible since the predictions generated are attached to actual wagered dollars. My models in American College Football and European Football have beaten sportsbooks every year for over a decade.
Are you implying your model beats the battle-tested system of:

>wake up at 9am
>hungover
>take a piss
>”oh damn there’s CFB today”
>pours cereal bowl
>sits on couch in boxers
>eat cereal and open draftkings
>bet on G5 traps you know nothing about

My friends have used it to great success. I think they’re only a few K in the hole
 
Are you implying your model beats the battle-tested system of:

>wake up at 9am
>hungover
>take a piss
>”oh damn there’s CFB today”
>pours cereal bowl
>sits on couch in boxers
>eat cereal and open draftkings
>bet on G5 traps you know nothing about

My friends have used it to great success. I think they’re only a few K in the hole
hell yeah love a good k hole on game day
 
Are you implying your model beats the battle-tested system of:

>wake up at 9am
>hungover
>take a piss
>”oh damn there’s CFB today”
>pours cereal bowl
>sits on couch in boxers
>eat cereal and open draftkings
>bet on G5 traps you know nothing about

My friends have used it to great success. I think they’re only a few K in the hole
I wish that I got to bet against those people. My opponents are corporations who have business relationships with sports media/leagues.
 
I wish that I got to bet against those people. My opponents are corporations who have business relationships with sports media/leagues.
Disgusted No Thank You GIF by Shark Week
 
1. Schematc changes on their own are not as important to offensive player predictions since my model rates usefulness on a per pay basis. The model does account for plays per game, which is the critical statistic. There’s ample evidence in the model from Kent State and similar offenses to help predict per game play counts.
2. Defensive players are modeled on a usefulness per play basis in all schemes. The key variable we’ve found is the number of offensive plays, not the defensive scheme.
3. Competition is assessed by opponent inputs. My model rates every player. A productive player against other productive players has a higher rating than a productive player against less productive players.
4. My model does not apply only to Colorado. It applies to every team in FBS. We rate FCS players after their season concludes for transfer purposes only.

My inputs and analtytical choices are carefully designed to be as accurate as possible since the predictions generated are attached to actual wagered dollars. My models in American College Football and European Football have beaten sportsbooks every year for over a decade.
All of this and no top 25 or pac predictions. Come on @manhattanbuff, i gotta see what you got and if it's the goods.

Let's see who got more of the goods, me or you. I just watch a lot of football, listen to coaches, and know tendencies extremely well. I don't have any cpu algorithms or anything like that. I actually think that makes you a lot better for teams I don't watch but for teams I watch and heavily watch, idk, I think I can compete. I was one of the top Draftkings guys for years and I never create an cpu algorithm once or paid anyone for anything.
 
All of this and no top 25 or pac predictions. Come on @manhattanbuff, i gotta see what you got and if it's the goods.

Let's see who got more of the goods, me or you. I just watch a lot of football, listen to coaches, and know tendencies extremely well. I don't have any cpu algorithms or anything like that. I actually think that makes you a lot better for teams I don't watch but for teams I watch and heavily watch, idk, I think I can compete. I was one of the top Draftkings guys for years and I never create a cpu algorithm once or paid anyone for anything.
You have to call his 1-900 number. $4.99 per minute.
 
Why is the model of someone who could quit his day job and be a professional gambler being questioned when the models he uses, not only for CFB but for European soccer as well, are sought after by extremely wealthy clientele lol
Thats a good question.

I didn't know he was a professional expert but I could tell he was someone that is serious business.

I was just saying, I want to test me v. Him in what I do know. I am knowledgeable and have done well in Vegas and didn't need any tools to do it or hedging to do it as long as it's in my realm of what I know. I've beat many pros before. Been beat by pros as well. I want to test my confidence v. His elite algorithm.
 
I found Manhattan’s take encouraging, am I crazy for that? A ceiling of 9 wins is higher than anyone on the planet has for us - I know that would require unfathomable injury luck, but still. I am a major homer and would have had our ceiling at 7 wins lol. And he said he raised the floor and ceiling due to what he’s seen.

Depth, especially in some spots, was always going to be a major question mark. Manhattan has been pretty optimistic all offseason. We’re gonna ****ing win.
 
All of this and no top 25 or pac predictions. Come on @manhattanbuff, i gotta see what you got and if it's the goods.

Let's see who got more of the goods, me or you. I just watch a lot of football, listen to coaches, and know tendencies extremely well. I don't have any cpu algorithms or anything like that. I actually think that makes you a lot better for teams I don't watch but for teams I watch and heavily watch, idk, I think I can compete. I was one of the top Draftkings guys for years and I never create an cpu algorithm once or paid anyone for anything.
In Barzil, I have a thread that details the answer to your request.
 
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