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VERY interesting statistical analysis of the game...

Corny_McPoo said:
LuCane said:
Corny_McPoo said:
Have someone give you a remedial primer on "statistical analysis."
Click to expand...
Don't get confused. This isn't a place for you to be condescending.

Especially when your dissertation comes down to premises like "let's boil down our common opponents to the GT game; where we both played at home."

You may have the advantage on Saturday, but it's not because you've played in "tougher environments" or have "more experience." It'll be because of what those guys wearing numbers do on the field with the plays the coaches put them in. Individual football games are won based on coaching/player match ups. The transitive property fails. If you care to bring a meaningful analysis of player or system match ups, perhaps it'd be a worthy read.
Click to expand...

There's a lot more meat on those bones than just the GT game.
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No there isn't. Distilled, all that data shows is that the base numbers are in Clemson's favor. That's great, you likely won't get any debate from anyone on this board that the base numbers are the base numbers.

Where is any advanced analytics in those numbers? Some 2 year old went on ESPN and plugged numbers into a spreadsheet and all of a sudden there's "a lot of meat on those bones"? Go do the same with S&P+ data and perhaps your post would have more bite to it. At the moment, all you've proven is that you can make numbers say whatever the author wants them to say if they pick the right numbers. Good on you if you want to hang your hat on it though.
 
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Corny_McPoo said:
Have someone give you a remedial primer on "statistical analysis."
Click to expand...

Right, so your "statistics," if I can call it that, are highly flawed. And before you criticize me as a source, I actually did not attend UM, but attended Columbia and studied statistics and do these analyses daily. Here are the flaws:

- Off to a bad foot using Winning Percentage as a proxy for talent of competition. You only have to look at the SEC to see why. If a team schedules 4 FCS schools as out of conference matches, they will get 4 easy wins, etc. Instead, you should use one of the hundreds of metrics out there for measuring an opponents true strength. An easy one would be SOR, which indicates how hard it would be to achieve the results in the schedule. Clemson is 1st in this metric, but Miami is 7th and not too far away. So they are a lot closer than your flawed analysis would say. (You can also choose more advanced metrics for this, but lets keep it easy).

- Oooff, more mistakes. Cross division record does not mean anything by itself. Each team only plays 2 teams, or 25% of the opposing division. Not enough data points, and skewed matchups can easily tilt the numbers. Just use SOR, or another advanced statistic.

- Only the GT game is comparable? Yes I can't see how choosing only one data point may somehow skew your analysis... I liked the idea of using common opponents, still not as good as using SOR or another advanced statistic that controls for various factors that come from a sample size of just 11 games, but it is by far your best statistic thus far. Congrats. However, you reduce your analysis to only one data point making it unusable. Instead, next time, just use the regular accepted Vegas adjustment for home v. away. Also, as an FYI, the GT game came after a highly emotional win over FSU that left us with a bit of a hangover.

- Winning record analysis, we already discussed this, record does not mean **** for analyzing it. Auburn has only one more loss than VT, yet they are not comparable... ok I will stop beating this dead horse.

-Best road win versus best away win: Your best road win is our best home win, but you chose the statistically inferior ND as our best home win to plump up your narrative. Tsk tsk. Also best home and road win is pretty much a product of luck of scheduling, teams have very little control over these schedules that are done years in advance. See what happened to Alabama with FSU. All you can take away is that they both won.

- Yards per game is flawed because it does not take into account the pace of offenses. You should use yards per play like most advanced analysis do.

- Completion percentage? really? You know who had the highest completion percentage in the NFL last year? Sam Bradford. Aaron Rodgers was 9th out of 30, i.e. slightly above average. Please explain how you would take Bradford over Rodgers. The fact is different offenses have different average length of throws, and completion percentage is easy to skew with a bubble and short passing offense.

- I like the snap count analysis, good to see how much wear and tear on starters. But without data for Miami you're essentially guessing and it's not a statistical analysis, it is just your opinion.

tl;dr learn some statistics
 
Corny_McPoo said:
Zbrod95 said:
Corny_McPoo said:
Zbrod95 said:
Corny_McPoo said:
Have someone give you a remedial primer on "statistical analysis."
Click to expand...

Has*
Click to expand...

[video]https://quipvid.com/watch/MxadP59B[/video]
Click to expand...

https://www.canesinsight.com/thread/canes/127406/5

Here’s what I did to the last guy who thought he “knew the difference” between the teams. You’re not as good as you think you are and your Offense is very flawed. Saturday is going to be really fun.
Click to expand...

We'll see.

Only one thing left to say to you in that case: spot the damned ball.
Click to expand...

$$$$ Will you take Clemson no points and give 5-1 odds? Do you trust those numbers or not.
 
Corny_McPoo said:
LuCane said:
Corny_McPoo said:
Have someone give you a remedial primer on "statistical analysis."
Click to expand...
Don't get confused. This isn't a place for you to be condescending.

Especially when your dissertation comes down to premises like "let's boil down our common opponents to the GT game; where we both played at home."

You may have the advantage on Saturday, but it's not because you've played in "tougher environments" or have "more experience." It'll be because of what those guys wearing numbers do on the field with the plays the coaches put them in. Individual football games are won based on coaching/player match ups. The transitive property fails. If you care to bring a meaningful analysis of player or system match ups, perhaps it'd be a worthy read.
Click to expand...

There's a lot more meat on those bones than just the GT game.
Click to expand...
It's cherry-picked data to fit a conclusion. But, I suspect you're aware since you didn't address the primary point of my response.
 
Statistical analysis? Statistical Analysis?

I have an MS in Statistical Modeling and Predictive Analytics from a top-5 program, and can attest to the fact that Clemson and the word "statistics" are a complete oxymoron.

Anyone in the field of statistics that attended Clemson did so because they were too DUMB to be admitted anywhere else.

Your posits in this thread validate the fact that "statistics" and Clemson are antonyms!
 
LuCane said:
Corny_McPoo said:
Have someone give you a remedial primer on "statistical analysis."
Click to expand...
Don't get confused. This isn't a place for you to be condescending.

Especially when your dissertation comes down to premises like "let's boil down our common opponents to the GT game; where we both played at home."

You may have the advantage on Saturday, but it's not because you've played in "tougher environments" or have "more experience." It'll be because of what those guys wearing numbers do on the field with the plays the coaches put them in. Individual football games are won based on coaching/player match ups. The transitive property fails. If you care to bring a meaningful analysis of player or system match ups, perhaps it'd be a worthy read.
Click to expand...

Gotta love a write up that contradicts itself....talking about Syracuse "just proves the transitive property does not apply to College Football." and then proceeds to dive into an analysis built on transitive logic of common opponents and results.
 
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I can tell you Clemson has no advantage with the number of snaps it gets out of its two-deep. Miami rotates a ton on offense and defense.

Atlantic is slightly better than the Coastal from top to bottom head to head, but most of the games have been decided by 7 points or less. Notre Dame rolled through the Atlantic and got embarrassed by Miami.

That Auburn team you beat in September turned the ball over and look awful the following week against Mercer. Auburn beats you this time around most likely. They aren't close to the same team they were in September.

Clemson crapped the bed at Syracuse. Miami did so at Pittsburgh.

BTW, Clemson should have drilled Virginia Tech last year and Tech had a chance to tie the ballgame on the last drive. Clemson by no means ran North Carolina out of the stadium the year before.

My sense is Clemson is going to get the angry Miami team on Saturday evening. Should be a good one.
 
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ND spent all week telling us about how the "stats" said there was zero chance they would lose.

That worked out well
 
We’re freerolling bud. 2 years ahead of schedule. Let me just say we’re ****ed off & disrepected again. We’re 2-0 in such spots this season. GL.
 
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Chrisarg72 said:
Corny_McPoo said:
Have someone give you a remedial primer on "statistical analysis."
Click to expand...

Right, so your "statistics," if I can call it that, are highly flawed. And before you criticize me as a source, I actually did not attend UM, but attended Columbia and studied statistics and do these analyses daily. Here are the flaws:

- Off to a bad foot using Winning Percentage as a proxy for talent of competition. You only have to look at the SEC to see why. If a team schedules 4 FCS schools as out of conference matches, they will get 4 easy wins, etc. Instead, you should use one of the hundreds of metrics out there for measuring an opponents true strength. An easy one would be SOR, which indicates how hard it would be to achieve the results in the schedule. Clemson is 1st in this metric, but Miami is 7th and not too far away. So they are a lot closer than your flawed analysis would say. (You can also choose more advanced metrics for this, but lets keep it easy).

- Oooff, more mistakes. Cross division record does not mean anything by itself. Each team only plays 2 teams, or 25% of the opposing division. Not enough data points, and skewed matchups can easily tilt the numbers. Just use SOR, or another advanced statistic.

- Only the GT game is comparable? Yes I can't see how choosing only one data point may somehow skew your analysis... I liked the idea of using common opponents, still not as good as using SOR or another advanced statistic that controls for various factors that come from a sample size of just 11 games, but it is by far your best statistic thus far. Congrats. However, you reduce your analysis to only one data point making it unusable. Instead, next time, just use the regular accepted Vegas adjustment for home v. away. Also, as an FYI, the GT game came after a highly emotional win over FSU that left us with a bit of a hangover.

- Winning record analysis, we already discussed this, record does not mean **** for analyzing it. Auburn has only one more loss than VT, yet they are not comparable... ok I will stop beating this dead horse.

-Best road win versus best away win: Your best road win is our best home win, but you chose the statistically inferior ND as our best home win to plump up your narrative. Tsk tsk. Also best home and road win is pretty much a product of luck of scheduling, teams have very little control over these schedules that are done years in advance. See what happened to Alabama with FSU. All you can take away is that they both won.

- Yards per game is flawed because it does not take into account the pace of offenses. You should use yards per play like most advanced analysis do.

- Completion percentage? really? You know who had the highest completion percentage in the NFL last year? Sam Bradford. Aaron Rodgers was 9th out of 30, i.e. slightly above average. Please explain how you would take Bradford over Rodgers. The fact is different offenses have different average length of throws, and completion percentage is easy to skew with a bubble and short passing offense.

- I like the snap count analysis, good to see how much wear and tear on starters. But without data for Miami you're essentially guessing and it's not a statistical analysis, it is just your opinion.

tl;dr learn some statistics
Click to expand...
They're actually not even statistics, they are comparative data points. Understandable he'd be confused, at best, he went to Clemson.
 
Numbers lie. You can't compare stats for a team that has played 12 games to stats for a team that has played 11 games. IMO.
 
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