Recruiting Forum Football Talk [RIP 9.3.2019]

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Ok, here's what I got...

Using Phil Steele's total experience points, the previous year's total offensive yards per game, and the previous year's Sagarin rating, I was able to create a model to predict last year's results with a r2 of 0.78, or a model that accounts for 78% of the variation for all FBS teams.

When you pull out the SEC and compare what the model predicted versus Sagarin's final ratings, you get this...

Screen Shot 2019-07-14 at 4.27.49 PM.png

This is how it would have shook out as far as predicted wins and losses versus what actually happened last year.

Screen Shot 2019-07-14 at 4.36.39 PM.png
The model predicted that we should have lost every SEC game we played last year, but we ended up pulling out two wins.

When you roll the model forward to next year, you can use it to get a sense of who might be rising rising or falling when you compare it to last year's final ratings. I was a little surprised that the model revises everyone down next year EXCEPT Tennessee.

Screen Shot 2019-07-14 at 4.58.04 PM.png

Finally, when you compare us to the SEC teams on our schedule, what we have is this:
Screen Shot 2019-07-14 at 4.51.16 PM.png
We're still behind a lot of folks, but the gap is closing, especially if you thinking about the differential between us and Auburn last year (about 14 pts on Sagarin's scale). So, the model says that we should expect to beat Vandy, we should be in for close games against Kentucky, Missouri, and South Carolina, and Georgia and Florida are within the distance that was between us and Auburn last year. Bama is Bama.

Looking at this, I put us losing to Florida, Georgia, and Alabama, winning close ones to South Carolina and Kentucky (even though the model has us slightly behind them), and beating Vandy soundly. I don't know what to do with Missouri. They might have a deeper team, but our coaching staff is so much better. There's there's Mississippi State.

I think Mississippi State shows some of the flukiness that comes along with Sagarin's model, which tries to incorporate strength of schedule. In his final rankings, despite going 8-5, his model ranked them as #8 in the country. So, when you project the model forward and use last years final rankings in the prediction for next year, it pushes the prediction for Mississippi State so high despite losing their starting QB and three first round draft picks on defense. As a faculty member, I've gotten cheap season tickets for MSU games, but I didn't renew this year. I just don't see how they lose as much as they did, and do better than the 8-5 season that they posted the year before. If we have another Auburn-grade upset next season, this is the game I'm going with.
 

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Smoke is billowing up again in Gainesville involving very serious and ugly misconduct by another player. Fans are being warned to brace for another bad week.

Offseason In Shambles!
LOL one poster said he blames the liberals that want to storm Area 51.
 
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Ok, here's what I got...

Using Phil Steele's total experience points, the previous year's total offensive yards per game, and the previous year's Sagarin rating (the , I was able to create a model to predict last year's results with a r2 of 0.78, or a model that accounts for 78% of the variation for all FBS teams.

When you pull out the SEC and compare what the model predicted versus Sagarin's final ratings, you get this...

View attachment 212552

This is how it would have shook out as far as predicted wins and losses versus what actually happened last year.

View attachment 212553
The model predicted that we should have lost every SEC game we played year, but we ended up pulling out two wins.

When you roll the model forward to next year, you can use it to get a sense of who might be rising rising or falling when you compare it to last year's final ratings. I was a little surprised that the model revises everyone down next year EXCEPT Tennessee.

View attachment 212563

Finally, when you compare us to the SEC teams on our schedule, what we have is this:
View attachment 212562
We're still behind a lot of folks, but the gap is closing, especially if you thinking about the differential between us and Auburn last year (about 14 pts on Sagarin's scale). So, the model says that we should expect to beat Vandy, we should be in for close games against Kentucky, Missouri, and South Carolina, and Georgia and Florida are within the distance that was between us and Auburn last year. Bama is Bama.

Looking at this, I put us losing to Florida, Georgia, and Alabama, winning close ones to South Carolina and Kentucky (even though the model has us slightly behind them), and beating Vandy soundly. I don't know what to do with Missouri. They might have a deeper team, but our coaching staff is so much better. There's there's Mississippi State.

I think Mississippi State shows some of the flukiness that comes along with Sagarin's model, which tries to incorporate strength of schedule. In his final rankings, despite going 8-5, his model ranked them as #8 in the country. So, when you project the model forward and use last years final rankings in the prediction for next year, that's why it's pushing Mississippi State so high despite losing their starting QB and three first round draft picks on defense. As a faculty member, I've gotten cheap season tickets for MSU games, but I didn't renew this year. I just don't see how they lose as much as they did, and do better than the 8-5 season that you posted the year before. If we have another Auburn-grade upset next season, this is the game I'm going with.
Good work
 
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Holy ****. That's like asking, Cindy Crawford or $5 Hooker?

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🐐

Somebody's old. And it ain't just Cindy Crawford.
 
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I used to do heroin and meth together...I just thought I was a drug addict till I started that..sometimes we would snort a line of cocaine on top of it just to get a lil extra kick...Back then we called it speedballin...mixing uppers and downers.

In a side note, we used to get special K from time to time, but I never liked the high no matter what I did it with.
Well, if you were expecting to get “high” off K.... there’s your problem....
 
Wins_Rating_UT prediction.jpg

Based on the post from earlier, I took the 2018-2019 win totals and plotted them against the final Sagarin Ratings. I then plotted the projected Sagarin number on top of it.

It looks like we're pretty close to the median for 8 win teams from least year. That's my best guess for setting an over-under for next season.
 
I used to do heroin and meth together...I just thought I was a drug addict till I started that..sometimes we would snort a line of cocaine on top of it just to get a lil extra kick...Back then we called it speedballin...mixing uppers and downers.

In a side note, we used to get special K from time to time, but I never liked the high no matter what I did it with.
What did you do after last Thursday though? 😏
 
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Man, I tried to quantify coaching and just gave up. I'm curious to hear how you did it.

Just ran a straightforward multiple linear regression and found the best predictors so far for predicting Sagarin's ratings (which factors in strength of schedule) are Phil Steele's "returning experience points", the previous season's returning yard's per game rank (if ol' Doc Schmidhammer saw that I used a rank in a linear regression he'd probably blow a gasket), and and the previous season's final Sagarin rating. That get's a R-Square of .78.

FPI can get on DN.
I've done it with basketball and am fairly satisfied with the results comparing talent rankings (via 247 composite) and experience (via KenPom) with the KenPom offense/defense metrics.

Looking at doing the same thing using Connelly's experience metrics, the 247 talent composite (much better for football), and some combination of ESPN's FPI, Sagarin, and the S&P+ to quantify the performance, but it's still very much a work in progress for football.

SIAP

OMK7LRBedcnhm.gif
 
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