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re: A statistics nerd on Reddit plugged all 128 teams into a computer model
Posted on 8/25/15 at 3:41 pm to anc
Posted on 8/25/15 at 3:41 pm to anc
quote:
For example, for Mississippi State, the model shows that they are most like 2011 Oklahoma State (12-1), 2012 Arkansas (3-8), or 2013 Michigan (7-6).
So you're saying your statistician says y'all could be great, average, or shitty?
Wow, some bold prediction.
1
Posted on 8/25/15 at 3:43 pm to rbWarEagle
Also, the offensive/defensive production for last year is a less than adequate predictor.
Posted on 8/25/15 at 3:44 pm to anc
quote:
-A lot of people are calling for Mississippi State to drop off, but my model doesn't see it. Sure, they lose STARTERS, but the problem is they don't lose as much PRODUCTION. This was a deep team last year, so the guys who didn't start last year who are replacing the starters produced, they just didn't start. #9 might be a bit too high, but a 9-3 record is perfectly reasonable.
Finally someone did some actual analysis.
Posted on 8/25/15 at 3:44 pm to rbWarEagle
Yea, based on his disclaimer for Auburn, I think the correct prediction should have been: Cannot calculate. 
Posted on 8/25/15 at 3:45 pm to CoonassBulldog
And if they go 9-3 (big if), you're permanently gone via the ban bet we made earlier this year.
frick you.
frick you.
Posted on 8/25/15 at 3:46 pm to GoCrazyAuburn
I mean, it's a neat idea and this guy did a good job, but it's hardly a good predictor for this year. It would be a much better predictor if he used the first 3-5 games of the season as a basis for the model, in my opinion.
Posted on 8/25/15 at 3:46 pm to Tornado Alley
quote:
And if they go 9-3 (big if),
no way we go less than 10-2 unless Dakota gets hurt
Posted on 8/25/15 at 3:49 pm to Gradual_Stroke
quote:
Reddit sucks dick
so you 4chan?
what a phaggot
Posted on 8/25/15 at 3:51 pm to anc
quote:
The model is interesting.
That is quite frankly an opinion.
Posted on 8/25/15 at 3:52 pm to Tornado Alley
This is me and my work. I post the sheets on the MSB in the betting thread.
I understand its not a perfect system but its not really meant to predict an entire season. These are just my sheets I use for gambling purposes. I might use the whole season predictions for win totals and futures but thats it. Creating preseason ratings that make sense is so difficult that you can't please everyone, and its a crap shoot anyway. The MAIN REASON I made preseason ratings was so my system could have something to work with the ifrst 7-8 weeks of the year while I wait for the sample size of games played to build up. In the past I had to wait until Week 9 to use my system as the sample size was too low and therefore my system's output was unstable.
Hell I created the sheets in the Reddit post on Saturday, and I have already made a few tweaks and changes to my system so those sheets don't reflect where my system is at right now. For example my numbers now have Alabama losing to Georgia last time I checked.
The only thing I really care about is Week 1. My sheets go into much more detail on a week by week basis. Here you go South Carolina fans, here is what my model does on a per-game basis.
I understand its not a perfect system but its not really meant to predict an entire season. These are just my sheets I use for gambling purposes. I might use the whole season predictions for win totals and futures but thats it. Creating preseason ratings that make sense is so difficult that you can't please everyone, and its a crap shoot anyway. The MAIN REASON I made preseason ratings was so my system could have something to work with the ifrst 7-8 weeks of the year while I wait for the sample size of games played to build up. In the past I had to wait until Week 9 to use my system as the sample size was too low and therefore my system's output was unstable.
Hell I created the sheets in the Reddit post on Saturday, and I have already made a few tweaks and changes to my system so those sheets don't reflect where my system is at right now. For example my numbers now have Alabama losing to Georgia last time I checked.
The only thing I really care about is Week 1. My sheets go into much more detail on a week by week basis. Here you go South Carolina fans, here is what my model does on a per-game basis.
Posted on 8/25/15 at 3:52 pm to cardboardboxer
quote:
That is quite frankly an opinion.
SECRant is no place for opinions
This post was edited on 8/25/15 at 3:55 pm
Posted on 8/25/15 at 3:53 pm to anc
And this folks is why the BCS no longer exists.
Posted on 8/25/15 at 3:53 pm to CoonassBulldog
And your dumbass included no caveat in the permanent ban bet concerning injuries to notable Mississippi State players.
I figure you'd welch when you lose, anyways.
I figure you'd welch when you lose, anyways.
Posted on 8/25/15 at 3:54 pm to NYCAuburn
quote:
SecRant is no places for opinions
Posted on 8/25/15 at 3:55 pm to rbWarEagle
quote:
I mean, it's a neat idea and this guy did a good job, but it's hardly a good predictor for this year. It would be a much better predictor if he used the first 3-5 games of the season as a basis for the model, in my opinion.
It's difficult to really come up with anything substantial. With football even for a whole season you have a sample size of 11-13 games, which is small. You need a sample size of about 6 games before the data is useful enough.
I am a big Ken Pomeroy fan, so I modeled my football preseason ratings similar to how he does his basketball preseason ratings.
One thing that is hurting Auburn is the baseline portion of my system. They were so bad in 2012 that that figure is still dragging them down. The baseline is the rolling 5 year average, with more weight to recent seasons.
Posted on 8/25/15 at 3:56 pm to accnodefense
How cute, you use last year's data.
News flash, players graduate and new players come in. Sometimes new players can be studs and player replacing the graduated players can be worse or better.
Gotta love computer geeks thinking they have the game of football predictions mastered.
Those computer geeks always miss the biggest things with their calculations - the HUMAN factor.
News flash, players graduate and new players come in. Sometimes new players can be studs and player replacing the graduated players can be worse or better.
Gotta love computer geeks thinking they have the game of football predictions mastered.
Those computer geeks always miss the biggest things with their calculations - the HUMAN factor.
Posted on 8/25/15 at 3:57 pm to nebraskafaninwi
Shut the frick up
Posted on 8/25/15 at 3:57 pm to accnodefense
quote:
It's difficult to really come up with anything substantial.
You are talking a lot of sense.
Posted on 8/25/15 at 3:58 pm to craigbiggio
My man. 
Posted on 8/25/15 at 4:00 pm to nebraskafaninwi
quote:
Gotta love computer geeks thinking they have the game of football predictions mastered.
Never said I did. Again this is for gambling purposes only. It's a starting point. I use this data to help me handicap games. But its not the gospel or the final say.
quote:
News flash, players graduate and new players come in. Sometimes new players can be studs and player replacing the graduated players can be worse or better.
It's not like my system uses last years numbers and assumes nothing changes. It takes a team, what they did last year, and what they have coming back, and identifies past teams who were in similar situations and then aggregates how those teams improved or declined.
I understand that some teams lose players and bring in better ones, but there is no objective way to measure that. You can't objectively measure how a recruit who has never played meaningful snaps will perform. For every Johnny Manziel you have a Jeff Driskell.
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