Remember computer "polls"?

[Cincydawg]

https://www.masseyratings.com/cf/compare.htm

Still around, barely noticed at all by anyone.  Kinda funny.

[ELA]

https://www.masseyratings.com/cf/compare.htm

Still around, barely noticed at all by anyone.  Kinda funny.

I post that each week in the power rankings thread.

I think each on its own has major flaws, but taken as a whole are pretty useful.

I also think they were a lot more impressive in the 80s and early 90s when there were just a couple and they were noteworthy.  Now anyone with some time can do one pretty easily, and as that composite shows, there are a glut of them.

Not to mention we don't rely on them to determine anything anymore, but personally, I'd be cool with scrapping the committee and going with the top 4 from that under the current model.

[MarqHusker]

I listen to Cade Massey on his Wharton 'moneyball' show on XM each week.    He and his cohort Wharton Profs do a nice job, and Massey's ratings always come up.

[FearlessF]

I feel the computers have less bias than the humans

computers don't have eyeballs for the eyeball test

[MaximumSam]

The bloggers and whatnot have largely moved to advanced stat metrics like S+P.  These tend to use statistics from the games to derive how good the teams are and not simply the final score.  S+P aims at beating Vegas about 54%.  A lot of computer models just use the final scores of games, and when there are only 12-14 games in a season, that ain't too much in the way of inputs.

Advanced stats are also way more interesting than computer rankings, because they look at many facets of the game and give lots of fodder for long winded posts and podcasts.

[Cincydawg]

I feel the computers have less bias than the humans

computers don't have eyeballs for the eyeball test

The have "bias" from their algorithms, or "Al Gore Rhythms".

[FearlessF]

I know they do, just believe it's less than humans and the bias doesn't change from week to week like the humans.

When Osborne was on the committee he used advanced stat metrics like S+P.

[mcwterps1]

I feel the computers have less bias than the humans

computers don't have eyeballs for the eyeball test

I agree wholeheartedly. 

[MichiFan87]

It's important to distinguish results based rankings from predictive metrics, because they serve different purposes, and therefore can have discrepancies between them.

A team like Air Force is ranked higher in predictive metrics than results-based ones because it has played a fairly tough schedule so far. Conversely, Army has done well against a rather weak schedule to date, so it's results based ranking is higher than predictive metrics. Consequently, you shouldn't be surprised if Air Force ends up dominating them when they play each other this year.

In basketball, Kenpom is the best predictive metric, but it shouldn't be considered in the NCAA tournament selection or seeding process or teams like Clemson and Indiana would've been in the field last year instead of USC and VCU. There's still a strong correlation, to be sure, though. The RPI has its own flaws as far as results-based algorithms go (and it's a rather simple calculation), but so do other algorithms and formulas.

[OrangeAfroMan]

The best models incorporated multiple years to combat the small single-season sample size.  Also the ones that used margin of victory were the most valid.  The worst part about when the computers were included was that none of them were as-is.....they were all compromised, lesser versions of themselves.

I miss them.

[MaximumSam]

A team like Air Force is ranked higher in predictive metrics than results-based ones because it has played a fairly tough schedule so far. Conversely, Army has done well against a rather weak schedule to date, so it's results based ranking is higher than predictive metrics. Consequently, you shouldn't be surprised if Air Force ends up dominating them when they play each other this year.

By S+P Army is 71 and Air Force is 86

[ELA]

It's important to distinguish results based rankings from predictive metrics, because they serve different purposes, and therefore can have discrepancies between them.

A team like Air Force is ranked higher in predictive metrics than results-based ones because it has played a fairly tough schedule so far. Conversely, Army has done well against a rather weak schedule to date, so it's results based ranking is higher than predictive metrics. Consequently, you shouldn't be surprised if Air Force ends up dominating them when they play each other this year.

In basketball, Kenpom is the best predictive metric, but it shouldn't be considered in the NCAA tournament selection or seeding process or teams like Clemson and Indiana would've been in the field last year instead of USC and VCU. There's still a strong correlation, to be sure, though. The RPI has its own flaws as far as results-based algorithms go (and it's a rather simple calculation), but so do other algorithms and formulas.

As this is the distinction too many people fail to recognize, and both have their pros and cons.

[MaximumSam]

Honestly I don't see much point for "results based" computer rankings in college football.  What's the point?  Why use them over predictive based models?  The things that are easy to see - overall record, head to head results, conference championships are pretty easy to see.  For the things that are not easy to see, why not use the system that more reliably predicts a result?

[ELA]

Honestly I don't see much point for "results based" computer rankings in college football.  What's the point?  Why use them over predictive based models?  The things that are easy to see - overall record, head to head results, conference championships are pretty easy to see.  For the things that are not easy to see, why not use the system that more reliably predicts a result?

For message board debate and gambling, sure.
For determining entry into the CFP, or the NCAA tourney in hoops, I have no use for the predictive models.