2019 Texas Football Season - "#8 Go Fuck Yourself Bitch"

[Magus Ossis 2784]

14 minutes ago, closetojumping said:

 Let’s not write a JUCO off in his first semester at Texas because there are rumors that he didn’t kill it in the training room while recovering from injury, his first week on campus. Some of this shit takes on a life of its own as though it’s an immutable fact or something. 

I dunno. If we don't jump to conclusions, run down our players, pull bad ideas out of thin air, carry criticism too far, and press on in our ignorance, some of us won't get any meaningful exercise.

[Bodacious Bevo 3576]

As long as he isn't pulling a Manning with the trainers I won't get too worked up about it 

He seemed pretty self-aware and focused during his recruitment 

[LTtxfan 49008]

4 hours ago, closetojumping said:

 Let’s not write a JUCO off in his first semester at Texas because there are rumors that he didn’t kill it in the training room while recovering from injury, his first week on campus. Some of this shit takes on a life of its own as though it’s an immutable fact or something. 

 

                          

 

[BigHorn'13 3356]

6 hours ago, closetojumping said:

 Let’s not write a JUCO off in his first semester at Texas because there are rumors that he didn’t kill it in the training room while recovering from injury, his first week on campus. Some of this shit takes on a life of its own as though it’s an immutable fact or something. 

My bad, thought that came from you...fuckinwitcha

[KYHorn 16865]

Figured this is the best place for this question... I just found out I'll be in Austin for the LA Tech game (season opener). Let me preface by saying I haven't been to a home game in probably 5 years. Looking online,  tickets in sections 3-6 range from $169- $270 and in sections 27-30, range from $120- $220 (between seatgeak and vividseats). Do you think these prices will fall once single game tickets become available? I don't really know what prices to expect for a season opener vs a team like LA Tech. In your opinion, what range should I look to buy in for these sections?

[NBMisha 224]

Pre game on the street will beat that.

[Bodacious Bevo 3576]

You'll easily find tickets for La Tech for way less right before the game starts

I'd start monitoring seatgeek a week or two before. If you're just looking for cheapest ticket available I'd bet you could get in for like 40 bucks 

[texifornia 56561]

Lol S&P+ haaaaaates us:

https://www.sbnation.com/college-football/2019/2/11/18219163/2019-college-football-rankings-projections

Relevant teams:

Rank/Team/Conference/Recruiting impact/Returning Production/Weighted 5-year/Projected S&P+

4

LSU

SEC

3

4

6

25.8

5

Oklahoma

Big 12

4

6

5

25.0

13

Texas A&M

SEC

8

13

24

34	TCU	Big 12	30	41	16	9.2
35	Texas	Big 12	9	51	37	8.9

38

West Virginia

Big 12

45

34

40

8.6

40

Baylor

Big 12

36

42

31

8.1

43

Iowa State

Big 12

49

40

69

7.2

55

Texas Tech

Big 12

64

50

53

4.8

64

Kansas State

Big 12

65

62

34

3.0

86

Louisiana Tech

C-USA

81

84

75

-2.4

107

Kansas

Big 12

67

109

121

-12.1

 

Oops forgot these two and the formatting is super wonky if I try to put them in the correct spots:

22

Oklahoma State

Big 12

37

23

22

12.8

126

Rice

C-USA

119

123

126

-20.0

And for those wondering, this is why our Recruiting Impact is #9:

• For recruiting, I create a rating based on these weighted four-year recruiting rankings. The weighting (67 percent this year’s class, 15 percent last year’s, 15 percent the year before that, three percent the year before that) is based on what makes the ratings most predictive.

Edited February 11, 2019 by texifornia

[Valmy77 13122]

Oklahoma State is #22 and Rice is #126. So S&P+ expects us to go 8-4.

I don't get what "recruiting impact" means. And "returning production"? I mean what is "production" here? Number of blocks, tackles, kicks, throws, and catches coming back? I mean I get we lost a few guys but do we really have among the lowest in "returning production" in all of P5?

Edited February 11, 2019 by Valmy77

[sushihorn 3233]

7 minutes ago, Valmy77 said:

Oklahoma State is #22 and Rice is #126. So S&P+ expects us to go 8-4.

I don't get what "recruiting impact" means. And "returning production"? I mean what is "production" here? Number of blocks, tackles, kicks, throws, and catches coming back? I mean I get we lost a few guys but do we really have among the lowest in "returning production" in all of P5?

It's basically a data mining project which values DB tackles as the highest measure of defensive production.  Considering that the miner has already admitted his model is terrible at assessing Tom Herman teams, I just ignore what he says about Texas.

[texifornia 56561]

10 minutes ago, Valmy77 said:

Oklahoma State is #22 and Rice is #126. So S&P+ expects us to go 8-4.

I don't get what "recruiting impact" means. And "returning production"? I mean what is "production" here? Number of blocks, tackles, kicks, throws, and catches coming back? I mean I get we lost a few guys but do we really have among the lowest in "returning production" in all of P5?

Here you go - we're losing a LOT of guys (almost all of our starting DBs, LBs, and linemen). We should be replacing them with studs, but still:

• For returning production, I take each team’s returning offensive and defensive production(which are on different scales) and apply projected changes to last year’s ratings. The ranking you see below is not where they rank in returning production but where they would rank after the projected changes are applied to last year’s S&P+ averages. This piece makes up a vast majority of the overall S&P+ projections.

Edited February 11, 2019 by texifornia

[Valmy77 13122]

Just now, sushihorn said:

It's basically a data mining project which values DB tackles as the highest measure of defensive production.  Considering that the miner has already admitted his model is terrible at assessing Tom Herman teams, I just ignore what he says about Texas.

He did not admit that at all. In fact he doubles down in that article.

Quote

In 2018, another Herman team defied both expectation and statistics. In his second year at Texas, his Longhorns ranked 32nd in S&P+ and, per second-order wins, had the look of an eight-win team. For every strong performance (namely, wins over Oklahoma and Georgia), there was a dud or near-disaster — a loss to Maryland, near-losses to Tulsa, Baylor, Texas Tech, Kansas, etc. Against anyone but the top teams, they did the bare minimum; it bit them once and nearly did so many other times.

Calling Georgia and Oklahoma strong performances and Tech and Kansas duds is idiotic. Those four games were almost completely identical. Big leads with 4th quarter meltdowns. It is just what we did last year.

Quote

S&P+ is going to project them to win about seven games. A Herman team has defied stats a couple of times now, but they haven’t yet done it back-to-back.

So seven wins then, not eight. My bad.

[Mitch Cumsteen 18524]

Quote

• For recent history, I’ve found that getting a little weird predicts pretty well. This number isn’t a strict five-year average — last year’s ratings already carry heavy weight from the returning production piece. Instead, what you see below is a projection based solely off of seasons two to five years ago. Recent history doesn’t carry much weight in the projections, but it serves as a reflection of overall program health. We overreact to one year’s performance sometimes.

Because what happened in the Charlie Strong era should be an excellent predictor of what happens at Texas next year. 

[Valmy77 13122]

15 minutes ago, texifornia said:

Here you go - we're losing a LOT of guys (almost all of our starting DBs, LBs, and linemen). We should be replacing them with studs, but still:

Ok but among the worst in all of P5? Does nobody in the country use upper classmen or have anybody leave early for the draft besides Texas?

I mean OU is losing Kyler Murray but one would think they are losing nobody of any significance at all based on their returning production ranking.

Edited February 11, 2019 by Valmy77

[Valmy77 13122]

7 minutes ago, Mitch Cumsteen said:

Because what happened in the Charlie Strong era should be an excellent predictor of what happens at Texas next year. 

I mean a few of his players are still here.

[Huckleberry 32710]

Seems like Connelly might be falling into a fairly common trap. He keeps piling more and more data on and can't stop because the more he piles on the better the correlation numbers look.

But that's a false positive. When running a regression analysis, even throwing bullshit unrelated data in will cause your R-squared value to inflate. I wouldn't be surprised to learn that when he says that he includes things that make the ratings "most predictive" he's talking about increasing R-squared values or something similar. Which wouldn't mean they're predictive at all. Let's just take a quick sanity check on his recruiting input, for example.

That input is 67% first year players, 15% second year, 15% third year, and 3% fourth year players. It makes sense that it's weighted toward younger players because he's trying not to duplicate his returning production input. Okay, makes some sense even if he's already in trouble from mixing and matching different measures. The question is this - does anyone think that two-thirds of snaps vacated by departing seniors and early draft entries are taken by true freshmen? Does that sound right, or even close, to anyone?

[sushihorn 3233]

18 minutes ago, Valmy77 said:

Ok but among the worst in all of P5? Does nobody in the country use upper classmen or have anybody leave early for the draft besides Texas?

I mean OU is losing Kyler Murray and 80% of their OL but one would think they are losing nobody of any significance at all based on their returning production ranking.

 

[Katfid54 8593]

16 minutes ago, Huckleberry said:

Seems like Connelly might be falling into a fairly common trap. He keeps piling more and more data on and can't stop because the more he piles on the better the correlation numbers look.

But that's a false positive. When running a regression analysis, even throwing bullshit unrelated data in will cause your R-squared value to inflate. I wouldn't be surprised to learn that when he says that he includes things that make the ratings "most predictive" he's talking about increasing R-squared values or something similar. Which wouldn't mean they're predictive at all. Let's just take a quick sanity check on his recruiting input, for example.

That input is 67% first year players, 15% second year, 15% third year, and 3% fourth year players. It makes sense that it's weighted toward younger players because he's trying not to duplicate his returning production input. Okay, makes some sense even if he's already in trouble from mixing and matching different measures. The question is this - does anyone think that two-thirds of snaps vacated by departing seniors and early draft entries are taken by true freshmen? Does that sound right, or even close, to anyone?

HAHAHA Exactly!  You really showed him!

Or maybe you didn't.

Who knows?  Your post is indecipherable to me.

 

[Huckleberry 32710]

Ha. It's not so much trying to bust somebody on the internet as it is just discussing the importance of sanity checking your statistical results. I did a study on statistics and how they correlated from season-to-season in the past. Sometimes there would be some weird things that popped up. Off the top of my head I think from 2008 to 2009 there was a negative correlation from one season to the next in forced fumbles per carry. So would I actually expect a team that was good at forcing fumbles in 2008 to be bad at it in 2009? Of course not, that fails the sanity check.

So when it comes to that recruiting input, we should be asking the question if 67% makes sense for first year players.

[Tex Long 4352]

How long has Connelly been prognosticating? How well have his predictions played out? 

[fellside 1079]

As much as it annoys me that S&P punishes teams for playing conservative and winning close games, it would be nice if Texas would start blowing teams out again.

If you can beat Oklahoma and Georgia, you should blow out Tulsa and Kansas.  S&P is pretty much right about that.  So Texas should start doing that because that sounds fun...

[NBMisha 224]

The point was there are inherent reasons why there will always be teams whose results defy, positively and negatively, these types of models.  And that can't be changed.

The point about the close calls is not  bad, imho.  All the gray hair earned last season testifies to the possibility that we overachieved a bit.

[Fozzz 152]

45 minutes ago, sushihorn said:

It's basically a data mining project which values DB tackles as the highest measure of defensive production.  Considering that the miner has already admitted his model is terrible at assessing Tom Herman teams, I just ignore what he says about Texas.

I don't think Connelly ever said that, and S&P+ nailed Herman's 2016 and 2017 teams.  Even though we are fans, we don't have to totally discount unfavorable projections because we don't like them.  It's okay.  

[Valmy77 13122]

Just now, Fozzz said:

I don't think Connelly ever said that, and S&P+ nailed Herman's 2016 and 2017 teams.  Even though we are fans, we don't have to totally discount unfavorable projections because we don't like them.  It's okay.  

Oh he may be right. I just do not understand his stats that claim the team TCU and Oklahoma State are returning is better than ours. I mean we do have a few guys coming back. I also do not get why our recruiting ranking is so low. Then you throw in the fact that the Strong era is being factored in and you see why we are ranked so low. But why? How do those numbers work? They seem very weird and arbitrary. 

[texifornia 56561]

1 minute ago, Valmy77 said:

Oh he may be right. I just do not understand his stats that claim the team TCU and Oklahoma State are returning is better than ours. I mean we do have a few guys coming back. I also do not get why our recruiting ranking is so low. Then you throw in the fact that the Strong era is being factored in and you see why we are ranked so low. But why? How do those numbers work? They seem very weird and arbitrary.  

I mean our recruiting ranking is still top 10. It's getting dragged down by the #25 ranked 2017 class.

Edited February 11, 2019 by texifornia

[KYHorn 16865]

32 minutes ago, Huckleberry said:

Seems like Connelly might be falling into a fairly common trap. He keeps piling more and more data on and can't stop because the more he piles on the better the correlation numbers look.

But that's a false positive. When running a regression analysis, even throwing bullshit unrelated data in will cause your R-squared value to inflate. I wouldn't be surprised to learn that when he says that he includes things that make the ratings "most predictive" he's talking about increasing R-squared values or something similar. Which wouldn't mean they're predictive at all. Let's just take a quick sanity check on his recruiting input, for example.

He just needs to click "adjusted r sqaured" on his spss dropdown. Problem solved.

[Valmy77 13122]

2 minutes ago, texifornia said:

I mean our recruiting ranking is still top 10. It's getting dragged down by the #25 ranked 2017 class.

Oh. Wait so that ranking is not just taking into account the new players coming in? Wouldn't the "Returning production" take into care of what is returning? 

This thing is opaque as hell.

Edited February 11, 2019 by Valmy77

[Huckleberry 32710]

12 minutes ago, Fozzz said:

I don't think Connelly ever said that, and S&P+ nailed Herman's 2016 and 2017 teams.  Even though we are fans, we don't have to totally discount unfavorable projections because we don't like them.  It's okay.  

He predicted 2017 Texas as #16 in the nation. They finished unranked in the polls and #30 in his S&P+.

He predicted 2016 Houston as #53. They finished #39 in his S&P+.

A lot of that is normal variability and certainly shouldn't be viewed as a bad result. But if your range for nailing a prediction is +/- 14 spots then it's not that great of a predictive tool. That would be like saying that his prediction for 2019 Texas is that we will be somewhere between the 21st and 49th best team in the country. Okay.

Edited February 11, 2019 by Huckleberry

[texifornia 56561]

2 minutes ago, Valmy77 said:

Oh. Wait so that ranking is not just taking into account the new players coming in? Wouldn't the "Returning production" take into care of what is returning? 

This thing is opaque as hell. 

It's 67 percent this year’s class, 15 percent last year’s, 15 percent the year before that, three percent the year before that.

[Valmy77 13122]

1 minute ago, texifornia said:

It's 67 percent this year’s class, 15 percent last year’s, 15 percent the year before that, three percent the year before that.

Fair enough. Is he re-adjusting the class ranks based on how they actually turned out though? The 2017 class has done pretty well despite its ranking in the fake offseason championship race.

Edited February 11, 2019 by Valmy77

[sushihorn 3233]

38 minutes ago, Huckleberry said:

Seems like Connelly might be falling into a fairly common trap. He keeps piling more and more data on and can't stop because the more he piles on the better the correlation numbers look.

But that's a false positive. When running a regression analysis, even throwing bullshit unrelated data in will cause your R-squared value to inflate. I wouldn't be surprised to learn that when he says that he includes things that make the ratings "most predictive" he's talking about increasing R-squared values or something similar. Which wouldn't mean they're predictive at all. Let's just take a quick sanity check on his recruiting input, for example.

That input is 67% first year players, 15% second year, 15% third year, and 3% fourth year players. It makes sense that it's weighted toward younger players because he's trying not to duplicate his returning production input. Okay, makes some sense even if he's already in trouble from mixing and matching different measures. The question is this - does anyone think that two-thirds of snaps vacated by departing seniors and early draft entries are taken by true freshmen? Does that sound right, or even close, to anyone?

Warning: Nerd Rant

Connelly seems to forget that real world data is a t-distribution, not a z-distribution (perfect bell curve).  And he's using so many data sets that his model has consumed a lot of degrees of freedom.

[texifornia 56561]

1 minute ago, Valmy77 said:

Fair enough. Is he re-adjusting the class ranks based on how they actually turned out though? The 2017 class has done pretty well despite its ranking in the fake offseason championship race.

Nope. It's supposed to just reflect a baseline talent level - not whether they're getting coached up (that gets reflected in the Returning Production score according to his logic).

[sushihorn 3233]

12 minutes ago, Fozzz said:

I don't think Connelly ever said that, and S&P+ nailed Herman's 2016 and 2017 teams.  Even though we are fans, we don't have to totally discount unfavorable projections because we don't like them.  It's okay.  

Actually Connelly has been too low in his projection for every Tom Herman coached team.  Don't let the fact that he was close 2 times and badly wrong 2 times blind you to that pattern.

[Valmy77 13122]

3 minutes ago, Huckleberry said:

He predicted 2017 Texas as #16 in the nation.

What the?

So coming off three straight losing seasons the S&P+ predicts we finish #16. Then after back to back winning ones it decides we are #35? 

And we finished #34 in 2016 after going 5-7...a slot higher than we are starting 2019. Hmmmm. I mean you cannot blame Tom Herman on that one.

[sushihorn 3233]

9 minutes ago, Huckleberry said:

He predicted 2017 Texas as #16 in the nation. They finished unranked in the polls and #30 in his S&P+.

He predicted 2016 Houston as #53. They finished #39 in his S&P+.

A lot of that is normal variability and certainly shouldn't be viewed as a bad result. But if your range for nailing a prediction is +/- 14 spots then it's not that great of a predictive tool. That would be like saying that his prediction for 2019 Texas is that we will be somewhere between the 13th and 41st best team in the country. Okay.

And those were his "accurate" years WRT Tom Herman.

[Valmy77 13122]

Quote

Still, they won 10 games, finishing with a win over a depleted but talented UGA in the Sugar Bowl. 

I mean...FFS S&P+. We had Sterns out and plenty of other injuries (even if guys like Ehlinger and CJ played through them). Now UGA losing is being blamed on them being depleted? How many excuses are going to be manufactured here? 

Edited February 11, 2019 by Valmy77

[sunset87 240]

Like Huck said, the 67% weighting for the Freshman class makes absolutely no sense for predicting next years team.  Also, on offense, I would think returning QBs and Olinemen would be a heavily weighted factor. Not sure if it is...

[Fozzz 152]

12 minutes ago, Huckleberry said:

He predicted 2017 Texas as #16 in the nation. They finished unranked in the polls and #30 in his S&P+.

He predicted 2016 Houston as #53. They finished #39 in his S&P+.

A lot of that is normal variability and certainly shouldn't be viewed as a bad result. But if your range for nailing a prediction is +/- 14 spots then it's not that great of a predictive tool. That would be like saying that his prediction for 2019 Texas is that we will be somewhere between the 21st and 49th best team in the country. Okay.

Sushi was referring to a comment that Connelly had previously made about Herman having overpeformed his S&P "2nd order wins" record (not the pre-season prediction) in 2015, but Connelly never said his model (S&P) was terrible at assessing Herman's teams.  In 2016 Herman's 2nd order wins was 8.1 and in 2017 it was 7.5, indicating that Herman does not have some hidden ability to consistently outperform his S&P 2nd order wins.  

His pre-season projections have tended to overrate Texas, but given where we finished in S&P last year and what we lost from last year's team, I don't see any problem with his projection for next season.  

[Valmy77 13122]

5 minutes ago, Fozzz said:

His pre-season projections have tended to overrate Texas, but given where we finished in S&P last year and what we lost from last year's team, I don't see any problem with his projection for next season.  

Yeah it seems we are returning total dogshit compared to the rest of the Big 12, we have lost every single good player. I guess we should just be happy the S&P+ is saying we are finishing in 4th place instead of 8th place where we belong according to his "returning production" numbers. Only our recruiting is saving us from a 3-9 type season.

Edited February 11, 2019 by Valmy77

[Huckleberry 32710]

27 minutes ago, Fozzz said:

His pre-season projections have tended to overrate Texas, but given where we finished in S&P last year and what we lost from last year's team, I don't see any problem with his projection for next season.  

Only if you are only considering his own ratings' universe and nothing else. His 2018 preseason for Texas was #27. Out of 107 systems that Massey tracks, only 5 systems had 2018 Texas that low at the end of the season (meaning only 4 out of 106 that weren't S&P+). The mean was 16.65 and the median was 16. So no, his preseason ratings don't tend to overrate Texas. You only have to go back to last season to see them underrating Texas pretty significantly.

Edited February 11, 2019 by Huckleberry

[Walden Ponderer 12639]

I don't mind in the least being one of the few consistently "overachieving" outliers on an otherwise solid model -- that would indicate you're on to something that other people haven't figured out yet.

Of course, I have no idea whether or not Connelly's model is an "otherwise solid model" since I've only paid attention to the fact that it's not very predictive of Tom Herman's teams.

[Fozzz 152]

1 hour ago, Huckleberry said:

Only if you are only considering his own ratings' universe and nothing else. His 2018 preseason for Texas was #27. Out of 107 systems that Massey tracks, only 5 systems had 2018 Texas that low at the end of the season (meaning only 4 out of 106 that weren't S&P+). The mean was 16.65 and the median was 16. So no, his preseason ratings don't tend to overrate Texas. You only have to go back to last season to see them underrating Texas pretty significantly.

His pre-season projections are designed to project S&P.  That's literally all they are meant to do.  They aren't intended or designed to project Texas' Dolphin, Hatch, J-Train, Junky's, Hamburgler, etc., rating.  Texas had a projected S&P+ entering 2018 of 27 and finished 32nd.  The year before their projected S&P+ was 16th and they finished 30th.  The year before that their projected S&P+ was 34th and they finished 36th.  So while the pre-season projected S&P+ has been fairly accurate over the past few years, but it generally overrates them a little.  

[Fozzz 152]

1 hour ago, Valmy77 said:

Yeah it seems we are returning total dogshit compared to the rest of the Big 12, we have lost every single good player. I guess we should just be happy the S&P+ is saying we are finishing in 4th place instead of 8th place where we belong according to his "returning production" numbers. Only our recruiting is saving us from a 3-9 type season.

There's no need to cry, Valmy.  

[Huckleberry 32710]

7 minutes ago, Fozzz said:

His pre-season projections are designed to project S&P.  That's literally all they are meant to do.  They aren't intended or designed to project Texas' Dolphin, Hatch, J-Train, Junky's, Hamburgler, etc., rating.  Texas had a projected S&P+ entering 2018 of 27 and finished 32nd.  The year before their projected S&P+ was 16th and they finished 30th.  The year before that their projected S&P+ was 34th and they finished 36th.  So while the pre-season projected S&P+ has been fairly accurate over the past few years, but it generally overrates them a little.  

So they're meaningless. What is the real world meaning behind them? If the only thing they're designed is to forecast S&P+ then they have zero value.

Edited February 11, 2019 by Huckleberry

[Magus Ossis 2784]

1 hour ago, Walden Ponderer said:

I don't mind in the least being one of the few consistently "overachieving" outliers on an otherwise solid model -- that would indicate you're on to something that other people haven't figured out yet.

Of course, I have no idea whether or not Connelly's model is an "otherwise solid model" since I've only paid attention to the fact that it's not very predictive of Tom Herman's teams.

He is, as has been stated, not so much modeling in the sense that an expert in a field should be, but rather data mining and "piling on." He asks the question, "what happened last time in 25 words or less?" He then uses aggregate data to get a quick answer to the  oversimplified question. He stacks a lot of similar answers together and calls it a model. He then uses it, not to predict what overall winning teams will look like in the future, but rather who will win which games by how much.

You could easily make a model yourself with similar accuracy. Use things like internet hits for "coach on hot seat," previous year preseason and final poll rankings, record straight-up and ATS, 4-year running weighted 247 recruiting average, and coach's shoe size. Your model will predict the winner of more games than it will miss, because you have included things that are at least related to how often a given team wins as part of the model. They are by no means causative, but if you judge your model on whether it has some correlation to reality, you don't have to be too picky about being rigorous.

The SAT has been shown in the past to correlate better to the income of the subject's parents than to subsequent grades in college. But only a nut or publicity hound would try to track incomes by giving subjects' kids the SAT.

Connelly needs some friends who understand statistics and to whom he will actually listen.

[Tex Pete 20188]

2 hours ago, fellside said:

As much as it annoys me that S&P punishes teams for playing conservative and winning close games, it would be nice if Texas would start blowing teams out again.

All that matters is the W column. Fuck this clown.

[Fozzz 152]

Just now, Huckleberry said:

So they're meaningless. What is the real world meaning behind them? If the only thing they're designed is to forecast S&P+ then they have zero value.

If you ascribe zero value to S&P+, then yes, they would be meaningless.  I think they have some value, although it's hard to say how much compared to other rating systems as I have not read any systematic study comparing them (as is occasionally done with ZiPS, Steamer, PECOTA, etc.).  However, from judging by this thread, the most valuable rating system is the one that predicts the best performance for your team of choice.  With that in mind, I would predict S&P+ has zero value on this board. 

[Huckleberry 32710]

2 minutes ago, Fozzz said:

If you ascribe zero value to S&P+, then yes, they would be meaningless.  I think they have some value, although it's hard to say how much compared to other rating systems as I have not read any systematic study comparing them (as is occasionally done with ZiPS, Steamer, PECOTA, etc.).  However, from judging by this thread, the most valuable rating system is the one that predicts the best performance for your team of choice.  With that in mind, I would predict S&P+ has zero value on this board. 

No, that's not what I mean at all. Connelly publishes his S&P+ because he thinks it better reflects actual team strengths than final scores. And, on the whole, I agree. He also publishes predictions versus the spread because he wants to show that there is a value in his system with respect to predicting future performance on the field. Therefore it's reasonable to wonder if he intends his preseason projections to predict performance on the field in the upcoming season. I would imagine that he does indeed feel like this is the case.

And so that is a more realistic measuring stick for his projections than his own system's year-end rankings. Otherwise the entire effort is meaningless. Anyone can rank the teams any way they like, and if I say next year San Jose State is going to be the #20 team in the country according to my system and then my system says they're #20 at the end of the year do I get to claim that as proof my system projected the Spartans' team properly? I suppose, but both results are actually evidence that my system is bad.

[fellside 1079]

9 minutes ago, Tex Pete said:

All that matters is the W column. Fuck this clown.

And future Wins as well.  Which are more likely when you are able to rest your starters late in games.  Or build depth by getting younger guys playing time.  And keeping younger players happy as they see the field more and don't decide to transfer, leading to more "W column" additions later on.

Blowing teams out is a good thing.  We knew 2005 Texas was better than 2009 Texas well before the championship game.

[Valmy77 13122]

10 minutes ago, fellside said:

Blowing teams out is a good thing.  We knew 2005 Texas was better than 2009 Texas well before the championship game.

Sure but you shouldn't make too much of it. Sometimes we get overly impressed with a team that blows people out.