Early look at next year's SEC (Subject to change)

#78
#78
knowthevols said:
Not with 18 wins.
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Pearl's last team only won 19 games and they got in as a 9 seed. And Boise St and Villanova only had 19 wins this season. Michigan St got in with only 18 wins in 2011 so it's obviously not an issue if the rest of your resume stacks up.
 
#79
#79
zansdad said:
It was the collective impression that play in the MWC was elevated this season and the committee rewarded a 9 team mid-major conference with 5 invites for "going out an playing people" when it turns out that they really didn't do that.......
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Might want to look at their OOC schedules and rethink that.
Their (MWC) schedules(ooc) were every bit as tough as ours and ours was one of the tougher ones in the SEC.
Unless you consider Michigan State, Syracuse, UCLA, Creighton, etc. patsies.
 
#80
#80
calban said:
Might want to look at their OOC schedules and rethink that.
Their (MWC) schedules(ooc) were every bit as tough as ours and ours was one of the tougher ones in the SEC.
Unless you consider Michigan State, Syracuse, UCLA, Creighton, etc. patsies.
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One team here or there per team is not 'playing people'. Many times those games (like UT's games vs Oklahoma State and Georgetown) are set by outside parties.
 
#81
#81
zansdad said:
One team here or there per team is not 'playing people'. Many times those games (like UT's games vs Oklahoma State and Georgetown) are set by outside parties.
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Guess I just don't get your point.
I don't see the effect of playing div 2s having any bearing on rpi.
Boise played 12 ooc games and finished 10-2 (div 1) pre conference. they were 1-1 against top 50.
We were 8-4. 1-3 against top 50 teams.
My point was that Martin needs to win the big games early to fix the rpi problems he encounters late every season.
The question was asked if we'd have gotten in with an rpi in the 40s. Go 2-2 early against the top 50s and yes, we'd have been in the 40s and dancing.
 
#82
#82
calban said:
Guess I just don't get your point.
I don't see the effect of playing div 2s having any bearing on rpi.
Boise played 12 ooc games and finished 10-2 (div 1) pre conference. they were 1-1 against top 50.
We were 8-4. 1-3 against top 50 teams.
My point was that Martin needs to win the big games early to fix the rpi problems he encounters late every season.
The question was asked if we'd have gotten in with an rpi in the 40s. Go 2-2 early against the top 50s and yes, we'd have been in the 40s and dancing.
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Agree with you here. I see more negatives in playing a D-2 opponent than positives. And even though it worked out for a few teams this year, it didnt go unnoticed by the 'basketball guru's'. I heard several folks bashing BSU for the Walla Walla and Corban U games.
 
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#83
#83
calban said:
Guess I just don't get your point.
I don't see the effect of playing div 2s having any bearing on rpi.
Boise played 12 ooc games and finished 10-2 (div 1) pre conference. they were 1-1 against top 50.
We were 8-4. 1-3 against top 50 teams.
My point was that Martin needs to win the big games early to fix the rpi problems he encounters late every season.
The question was asked if we'd have gotten in with an rpi in the 40s. Go 2-2 early against the top 50s and yes, we'd have been in the 40s and dancing.
Click to expand...

Boise State won exactly the same number of top 25 OOC games UT did.

Also, what started this debate between us was your assertion that you weren't sure about Martin's scheduling savvy. That's all I'm talking about. Obviously if UT wins games against top 50 teams that increases their chances of getting in.

However there is also obviously something going on with scheduling D2 schools. The MWC is apparently the only conference that seemed to have done it across the board and it got them the highest conference RPI, 3rd highest conference SOS, the 2nd highest percentage of conference members in the tourney, and tied for 3rd highest number of bids. Strange that those numbers could come from a mid-major conference sprinkled with D2 teams on their schedule if that wasn't somehow beneficial.
 
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#84
#84
There's a lot of general misunderstandings about the RPI. I'm not going to get into all of them, but I can explain to you, mathematically, the advantages of scheduling division 2 opponents over very bad division 1 opponents.
Our variables (some courtesy of live-rpi)-
Tennessee's RPI- 0.5688 (59th in country)
Tennessee's SOS- 0.5544
Tennessee's AWP- 0.6119
Tennessee's Adj record- 16.4 wins 10.4 losses
Kennesaw State's SOS- 0.4565
Kennesaw State's AWP- 0.0942
Presbyterian SOS- 0.4372
Presbyterian AWP- 0.1570
Our formulas:
RPI = (AWP * 0.25) + (SOS * 0.75)
SOS impact = (AWP * 0.66) + (OWP * 0.33
SOS = (OWP *0.66) + (OOWP * 0.33)
In this case, the OWP is actually our opponent's AWP, and the OOWP is their OWP.
Assumptions-
We don't have our opponents' OWP. We have their SOS, which uses the OWP as a heavy weight, but also contains the OOWP. To get the OWP would require nested for loops parsing ~900 data points per team. Since this is by hand, that ain't happening, so let's assume OWP and OOWP are roughly equal and make our SOS stats for those teams their OWP. This means our final answers won't be entirely accurate, but it will only affect it by a spot or two in the rankings and not necessarily against UT's favor. A further note, contrary to popular belief, the venue does NOT affect the opponent's weight on the schedule. Neither does winning or losing. SOS is taken by adding up all your opponent's adjusted records and all their opponent's adjusted records to produce OWP and OOWP. The weighting for venue affects these adjusted records, but there is no further weighting.

We also don't have the opponent's weight on our SOS. Instead, we're going to multiply UT's SOS by 32 and assume each opponent is equal weight. This will actually negatively affect UT by a few spots because of the way OWP is calculated. As most of you know, wins/losses are of different values depending upon venue. Because of this, teams that lose a great deal, such as our opponents above, have a heavier weight due to all those home losses. On an unrelated note, the converse is true for dominant teams due to their success on the road.

Calculations:
So now with variables and assumptions out of the way, let's assume we're getting rid of Kennesaw State and Presbyterian and replacing with division 2 opponents who don't count towards RPI. First, we have to remove those adjusted wins from our adj. win column. Since they were both home wins, we need to remove 1.2
New Adj. record= (16.4-1.2) wins 10.4 losses
= 15.2 wins 10.4 wins
New AWP- 15.2/(15.2+10.4) = .5938
Note: Adjusted record was calculated from UT's schedule using a for loop by hand.

Now let's get our SOS. As stated above, we'll multiply our current SOS by 32(#games) to get a number we can subtract from.
SOS * #games = 0.5544 * 32 = 17.7408
OK, now let's get the SOS impact for both K-state and Presbyterian.
K state impact = ((0.0942 * 0.66) + (.4565 * 0.33)
= .2128
Pres impact = (.157 * 0.66) + (0.4372 * 0.33)
= .2479
Now let's subtract these impacts from our number above
New SOS * #games = 17.7408-.2128 - .2479 = 17.2801
Now, we divide this number over our new number of games, 30.
New SOS = 17.2801/30= .5760
Finally, with our New SOS and AWP, let's calculate RPI.
New RPI = (New SOS * 0.75) + (New AWP * 0.25)
RPI = (.5760 * 0.75) + (.5938 * 0.25) = .5805

So, what would have been the impact of playing d-II opponents instead of those two games? Well, with that number, Tennessee would have finished 52nd, a good 7 spots higher and in front of Cal and Nova. Given our assumptions potentially negative impact on UT, the high 40's is definitely within our error. Regardless of whether we get in or not with those numbers, its clear that in terms of RPI it's smarter to schedule division 2 teams over bottom feeder d-1 teams.
 
#85
#85
zansdad said:
Boise State won exactly the same number of top 25 OOC games UT did.

Also, what started this debate between us was your assertion that you weren't sure about Martin's scheduling savvy. That's all I'm talking about. Obviously if UT wins games against top 50 teams that increases their chances of getting in.

However there is also obviously something going on with scheduling D2 schools. The MWC is apparently the only conference that seemed to have done it across the board and it got them the highest conference RPI, 3rd highest conference SOS, the 2nd highest percentage of conference members in the tourney, and tied for 3rd highest number of bids. Strange that those numbers could come from a mid-major conference sprinkled with D2 teams on their schedule if that wasn't somehow beneficial.
Click to expand...
Maybe Boise isn't the team to use to prove your point.
They played the same number of OOC teams that we did. Included bottom feeders. 300+
Still not sure about Martin's scheduling. Needs a couple of lessons from Tony Jones.
You'll never convince that games that don't count, influence RPI in any way shape or form. So we'll agree to disagree.
 
#86
#86
volfan199 said:
Regardless of whether we get in or not with those numbers, its clear that in terms of RPI it's smarter to schedule division 2 teams over bottom feeder d-1 teams.
Click to expand...

I'll agree with this.
Not playing 300+ teams helps rpi.
 
#88
#88
volfan199 said:
There's a lot of general misunderstandings about the RPI. I'm not going to get into all of them, but I can explain to you, mathematically, the advantages of scheduling division 2 opponents over very bad division 1 opponents.
Our variables (some courtesy of live-rpi)-
Tennessee's RPI- 0.5688 (59th in country)
Tennessee's SOS- 0.5544
Tennessee's AWP- 0.6119
Tennessee's Adj record- 16.4 wins 10.4 losses
Kennesaw State's SOS- 0.4565
Kennesaw State's AWP- 0.0942
Presbyterian SOS- 0.4372
Presbyterian AWP- 0.1570
Our formulas:
RPI = (AWP * 0.25) + (SOS * 0.75)
SOS impact = (AWP * 0.66) + (OWP * 0.33
SOS = (OWP *0.66) + (OOWP * 0.33)
In this case, the OWP is actually our opponent's AWP, and the OOWP is their OWP.
Assumptions-
We don't have our opponents' OWP. We have their SOS, which uses the OWP as a heavy weight, but also contains the OOWP. To get the OWP would require nested for loops parsing ~900 data points per team. Since this is by hand, that ain't happening, so let's assume OWP and OOWP are roughly equal and make our SOS stats for those teams their OWP. This means our final answers won't be entirely accurate, but it will only affect it by a spot or two in the rankings and not necessarily against UT's favor. A further note, contrary to popular belief, the venue does NOT affect the opponent's weight on the schedule. Neither does winning or losing. SOS is taken by adding up all your opponent's adjusted records and all their opponent's adjusted records to produce OWP and OOWP. The weighting for venue affects these adjusted records, but there is no further weighting.

We also don't have the opponent's weight on our SOS. Instead, we're going to multiply UT's SOS by 32 and assume each opponent is equal weight. This will actually negatively affect UT by a few spots because of the way OWP is calculated. As most of you know, wins/losses are of different values depending upon venue. Because of this, teams that lose a great deal, such as our opponents above, have a heavier weight due to all those home losses. On an unrelated note, the converse is true for dominant teams due to their success on the road.

Calculations:
So now with variables and assumptions out of the way, let's assume we're getting rid of Kennesaw State and Presbyterian and replacing with division 2 opponents who don't count towards RPI. First, we have to remove those adjusted wins from our adj. win column. Since they were both home wins, we need to remove 1.2
New Adj. record= (16.4-1.2) wins 10.4 losses
= 15.2 wins 10.4 wins
New AWP- 15.2/(15.2+10.4) = .5938
Note: Adjusted record was calculated from UT's schedule using a for loop by hand.

Now let's get our SOS. As stated above, we'll multiply our current SOS by 32(#games) to get a number we can subtract from.
SOS * #games = 0.5544 * 32 = 17.7408
OK, now let's get the SOS impact for both K-state and Presbyterian.
K state impact = ((0.0942 * 0.66) + (.4565 * 0.33)
= .2128
Pres impact = (.157 * 0.66) + (0.4372 * 0.33)
= .2479
Now let's subtract these impacts from our number above
New SOS * #games = 17.7408-.2128 - .2479 = 17.2801
Now, we divide this number over our new number of games, 30.
New SOS = 17.2801/30= .5760
Finally, with our New SOS and AWP, let's calculate RPI.
New RPI = (New SOS * 0.75) + (New AWP * 0.25)
RPI = (.5760 * 0.75) + (.5938 * 0.25) = .5805

So, what would have been the impact of playing d-II opponents instead of those two games? Well, with that number, Tennessee would have finished 52nd, a good 7 spots higher and in front of Cal and Nova. Given our assumptions potentially negative impact on UT, the high 40's is definitely within our error. Regardless of whether we get in or not with those numbers, its clear that in terms of RPI it's smarter to schedule division 2 teams over bottom feeder d-1 teams.
Click to expand...

mind%20blown.gif
 
#89
#89
volfan199 said:
there's a lot of general misunderstandings about the rpi. I'm not going to get into all of them, but i can explain to you, mathematically, the advantages of scheduling division 2 opponents over very bad division 1 opponents.
Our variables (some courtesy of live-rpi)-
tennessee's rpi- 0.5688 (59th in country)
tennessee's sos- 0.5544
tennessee's awp- 0.6119
tennessee's adj record- 16.4 wins 10.4 losses
kennesaw state's sos- 0.4565
kennesaw state's awp- 0.0942
presbyterian sos- 0.4372
presbyterian awp- 0.1570
our formulas:
Rpi = (awp * 0.25) + (sos * 0.75)
sos impact = (awp * 0.66) + (owp * 0.33
sos = (owp *0.66) + (oowp * 0.33)
in this case, the owp is actually our opponent's awp, and the oowp is their owp.
Assumptions-
we don't have our opponents' owp. We have their sos, which uses the owp as a heavy weight, but also contains the oowp. To get the owp would require nested for loops parsing ~900 data points per team. Since this is by hand, that ain't happening, so let's assume owp and oowp are roughly equal and make our sos stats for those teams their owp. This means our final answers won't be entirely accurate, but it will only affect it by a spot or two in the rankings and not necessarily against ut's favor. A further note, contrary to popular belief, the venue does not affect the opponent's weight on the schedule. Neither does winning or losing. Sos is taken by adding up all your opponent's adjusted records and all their opponent's adjusted records to produce owp and oowp. The weighting for venue affects these adjusted records, but there is no further weighting.

We also don't have the opponent's weight on our sos. Instead, we're going to multiply ut's sos by 32 and assume each opponent is equal weight. This will actually negatively affect ut by a few spots because of the way owp is calculated. As most of you know, wins/losses are of different values depending upon venue. Because of this, teams that lose a great deal, such as our opponents above, have a heavier weight due to all those home losses. On an unrelated note, the converse is true for dominant teams due to their success on the road.

Calculations:
So now with variables and assumptions out of the way, let's assume we're getting rid of kennesaw state and presbyterian and replacing with division 2 opponents who don't count towards rpi. First, we have to remove those adjusted wins from our adj. Win column. Since they were both home wins, we need to remove 1.2
new adj. Record= (16.4-1.2) wins 10.4 losses
= 15.2 wins 10.4 wins
new awp- 15.2/(15.2+10.4) = .5938
note: Adjusted record was calculated from ut's schedule using a for loop by hand.

Now let's get our sos. As stated above, we'll multiply our current sos by 32(#games) to get a number we can subtract from.
Sos * #games = 0.5544 * 32 = 17.7408
ok, now let's get the sos impact for both k-state and presbyterian.
K state impact = ((0.0942 * 0.66) + (.4565 * 0.33)
= .2128
pres impact = (.157 * 0.66) + (0.4372 * 0.33)
= .2479
now let's subtract these impacts from our number above
new sos * #games = 17.7408-.2128 - .2479 = 17.2801
now, we divide this number over our new number of games, 30.
New sos = 17.2801/30= .5760
finally, with our new sos and awp, let's calculate rpi.
New rpi = (new sos * 0.75) + (new awp * 0.25)
rpi = (.5760 * 0.75) + (.5938 * 0.25) = .5805

so, what would have been the impact of playing d-ii opponents instead of those two games? Well, with that number, tennessee would have finished 52nd, a good 7 spots higher and in front of cal and nova. Given our assumptions potentially negative impact on ut, the high 40's is definitely within our error. Regardless of whether we get in or not with those numbers, its clear that in terms of rpi it's smarter to schedule division 2 teams over bottom feeder d-1 teams.
Click to expand...

80085
 
#92
#92
I would be willing to chip in for Kenny Boyton's tuition if he can play one more year.
 
#95
#95
this coming season will be the first time in a while where florida will truly have depth in the front court and the back court in the same year.

they will be a better basketball team next season.
 
#96
#96
zjcvols said:
I would be willing to chip in for Kenny Boyton's tuition if he can play one more year.
Click to expand...
Only if it's junior Kenny Boynton.

Even senior Kenny Boynton played good defense and didn't make dumb decisions with the ball (except a few times late in the game). The jump shot just wasn't there.
 
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#97
#97
GoobieVol said:
LOL glad to have you back Patricia.
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So are we.

Expected. He turned down being an early-to-mid second round pick so that he can get his degree in December. Smart move. Hopefully he develops some kind of jumpshot outside of five feet.
 
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