01-28-2021, 07:38 PM
UConn staying at #1 with their best win being over DePaul while NC State drops despite losing in OT without their best player and centerpiece of their offense and defense?
WBB: VTech 83 NCST 72 ot
01-28-2021, 07:56 PM
The delta between NET and RPI for UConn is surprisingly large. Also, Oregon (4th by NET and not in the top 8 by RPI).
BC
BC
The delta between NET and RPI for UConn is surprisingly large. Also, Oregon (4th by NET and not in the top 8 by RPI).
BC
BC
01-28-2021, 09:03 PM
guess we will see what the next few weeks bring. otherwise if UConn ranked as a 1, we could see them lose to a 2!
01-29-2021, 07:48 AM
(01-28-2021, 07:56 PM)BostonCard Wrote: The delta between NET and RPI for UConn is surprisingly large. Also, Oregon (4th by NET and not in the top 8 by RPI).
Well, RPI was never really a power ranking, sort of an iffy strength of schedule ranking.
As of right now (through games of 1/28) the NET is:
1. Stanford
2. UConn
3. South Carolina
4. Oregon
5. Baylor
6. Louisville
7. UCLA
8. Maryland
8. Ohio State
9. Indiana
11. NC State
13. Arizona
Apparently, NET doesn't think much of Louisville's close wins over average teams.
While NET appears to be a reasonably strong statistical approach, it does give up a lot in terms of transparency.
(01-28-2021, 07:56 PM)BostonCard Wrote: The delta between NET and RPI for UConn is surprisingly large. Also, Oregon (4th by NET and not in the top 8 by RPI).
Well, RPI was never really a power ranking, sort of an iffy strength of schedule ranking.
As of right now (through games of 1/28) the NET is:
1. Stanford
2. UConn
3. South Carolina
4. Oregon
5. Baylor
6. Louisville
7. UCLA
8. Maryland
8. Ohio State
9. Indiana
11. NC State
13. Arizona
Apparently, NET doesn't think much of Louisville's close wins over average teams.
While NET appears to be a reasonably strong statistical approach, it does give up a lot in terms of transparency.
01-29-2021, 08:44 AM
I'm a brobdingnagian fan of Massey ratings, which have more often been predictive of post-season outcomes than RPI or AP rankings. He has:
1. South Carolina 9.33
2. Stanford 9.31
3. Connecticut 9.11
4. Oregon 9.01
5. Baylor 8.85
6. UCLA 8.73
7. Louisville 8.67
and other notables:
12. Arizona 8.23
20. Washington St. 7.69
45. Arizona St. 7.03
48. Colorado 6.90
49. USC 6.89
Per Massey, we have the 6th most efficient offense and most efficient defense in the country. That seems about right. Louisville is as low as they are because they have the 18th most efficient defense but only the 11th most efficient offense. (And per Massey, Louisville has yet to play, let alone beat, a top 30 team. As we saw last night w. UConn, soft schedules can paper over looming weaknesses.)
1. South Carolina 9.33
2. Stanford 9.31
3. Connecticut 9.11
4. Oregon 9.01
5. Baylor 8.85
6. UCLA 8.73
7. Louisville 8.67
and other notables:
12. Arizona 8.23
20. Washington St. 7.69
45. Arizona St. 7.03
48. Colorado 6.90
49. USC 6.89
Per Massey, we have the 6th most efficient offense and most efficient defense in the country. That seems about right. Louisville is as low as they are because they have the 18th most efficient defense but only the 11th most efficient offense. (And per Massey, Louisville has yet to play, let alone beat, a top 30 team. As we saw last night w. UConn, soft schedules can paper over looming weaknesses.)
I'm a brobdingnagian fan of Massey ratings, which have more often been predictive of post-season outcomes than RPI or AP rankings. He has:
1. South Carolina 9.33
2. Stanford 9.31
3. Connecticut 9.11
4. Oregon 9.01
5. Baylor 8.85
6. UCLA 8.73
7. Louisville 8.67
and other notables:
12. Arizona 8.23
20. Washington St. 7.69
45. Arizona St. 7.03
48. Colorado 6.90
49. USC 6.89
Per Massey, we have the 6th most efficient offense and most efficient defense in the country. That seems about right. Louisville is as low as they are because they have the 18th most efficient defense but only the 11th most efficient offense. (And per Massey, Louisville has yet to play, let alone beat, a top 30 team. As we saw last night w. UConn, soft schedules can paper over looming weaknesses.)
1. South Carolina 9.33
2. Stanford 9.31
3. Connecticut 9.11
4. Oregon 9.01
5. Baylor 8.85
6. UCLA 8.73
7. Louisville 8.67
and other notables:
12. Arizona 8.23
20. Washington St. 7.69
45. Arizona St. 7.03
48. Colorado 6.90
49. USC 6.89
Per Massey, we have the 6th most efficient offense and most efficient defense in the country. That seems about right. Louisville is as low as they are because they have the 18th most efficient defense but only the 11th most efficient offense. (And per Massey, Louisville has yet to play, let alone beat, a top 30 team. As we saw last night w. UConn, soft schedules can paper over looming weaknesses.)
01-29-2021, 11:25 AM
(01-29-2021, 09:59 AM)WBB fan Wrote: Can anyone explain the NET rating system to me?
https://www.ncaa.com/news/basketball-men...-explained
BC
(01-29-2021, 09:59 AM)WBB fan Wrote: Can anyone explain the NET rating system to me?
https://www.ncaa.com/news/basketball-men...-explained
BC
01-29-2021, 05:15 PM
(01-29-2021, 11:25 AM)BostonCard Wrote:(01-29-2021, 09:59 AM)WBB fan Wrote: Can anyone explain the NET rating system to me?
https://www.ncaa.com/news/basketball-men...-explained
BC
Thanks!
(01-29-2021, 11:25 AM)BostonCard Wrote:(01-29-2021, 09:59 AM)WBB fan Wrote: Can anyone explain the NET rating system to me?
https://www.ncaa.com/news/basketball-men...-explained
BC
Thanks!
01-30-2021, 06:05 AM
(01-29-2021, 11:25 AM)BostonCard Wrote:This is about WBB, so I think this is a better reference(01-29-2021, 09:59 AM)WBB fan Wrote: Can anyone explain the NET rating system to me?
https://www.ncaa.com/news/basketball-men...-explained
BC
https://www.ncaa.com/news/basketball-wom...ne-article
(01-29-2021, 11:25 AM)BostonCard Wrote:This is about WBB, so I think this is a better reference(01-29-2021, 09:59 AM)WBB fan Wrote: Can anyone explain the NET rating system to me?
https://www.ncaa.com/news/basketball-men...-explained
BC
https://www.ncaa.com/news/basketball-wom...ne-article
In a MBB post, a reference was made to this site for playing with & evaluating different lineups.
It also has data for WBB. Here's Stanford WBB.
I didn't do that yet, but I thought I'd grab the baseline evaluation for each of some of the top teams.
A bit of info overload, but you can get a feel for the strengths & weaknesses of the top teams.
![[Image: WBB20210129.png]](https://i.ibb.co/F54915L/WBB20210129.png)
Note TO% for virtually all the top teams is worse than average. Interesting.
It also has data for WBB. Here's Stanford WBB.
I didn't do that yet, but I thought I'd grab the baseline evaluation for each of some of the top teams.
A bit of info overload, but you can get a feel for the strengths & weaknesses of the top teams.
Note TO% for virtually all the top teams is worse than average. Interesting.
In a MBB post, a reference was made to this site for playing with & evaluating different lineups.
It also has data for WBB. Here's Stanford WBB.
I didn't do that yet, but I thought I'd grab the baseline evaluation for each of some of the top teams.
A bit of info overload, but you can get a feel for the strengths & weaknesses of the top teams.
Note TO% for virtually all the top teams is worse than average. Interesting.
It also has data for WBB. Here's Stanford WBB.
I didn't do that yet, but I thought I'd grab the baseline evaluation for each of some of the top teams.
A bit of info overload, but you can get a feel for the strengths & weaknesses of the top teams.
Note TO% for virtually all the top teams is worse than average. Interesting.
01-30-2021, 09:30 AM
(01-30-2021, 06:05 AM)M T Wrote:(01-29-2021, 11:25 AM)BostonCard Wrote:This is about WBB, so I think this is a better reference(01-29-2021, 09:59 AM)WBB fan Wrote: Can anyone explain the NET rating system to me?
https://www.ncaa.com/news/basketball-men...-explained
BC
https://www.ncaa.com/news/basketball-wom...ne-article
I don't think either of those explain NET very well. I have read a few technical articles, though those haven't been very complete. I haven't really tracked down details.
My best understanding is that this is basically an opponent adjusted efficiency stat. So it's some version of points per possession divided by opponents' points per possession allowed plus the equivalent for defense. That's basically the FEI stat for football applied to basketball.
Then there are adjustments for home/away and perhaps a few other things. The weights for each are determined each time they run the program by the entire women's division 1 results data base.
As I stated above, my general understanding is that it is fairly sophisticated statistically but the complexity makes it inherently opaque. There are pluses and minuses to that.
(01-30-2021, 06:05 AM)M T Wrote:(01-29-2021, 11:25 AM)BostonCard Wrote:This is about WBB, so I think this is a better reference(01-29-2021, 09:59 AM)WBB fan Wrote: Can anyone explain the NET rating system to me?
https://www.ncaa.com/news/basketball-men...-explained
BC
https://www.ncaa.com/news/basketball-wom...ne-article
I don't think either of those explain NET very well. I have read a few technical articles, though those haven't been very complete. I haven't really tracked down details.
My best understanding is that this is basically an opponent adjusted efficiency stat. So it's some version of points per possession divided by opponents' points per possession allowed plus the equivalent for defense. That's basically the FEI stat for football applied to basketball.
Then there are adjustments for home/away and perhaps a few other things. The weights for each are determined each time they run the program by the entire women's division 1 results data base.
As I stated above, my general understanding is that it is fairly sophisticated statistically but the complexity makes it inherently opaque. There are pluses and minuses to that.
01-30-2021, 09:45 AM
(01-30-2021, 09:30 AM)CTcard Wrote:(01-30-2021, 06:05 AM)M T Wrote:(01-29-2021, 11:25 AM)BostonCard Wrote:This is about WBB, so I think this is a better reference(01-29-2021, 09:59 AM)WBB fan Wrote: Can anyone explain the NET rating system to me?
https://www.ncaa.com/news/basketball-men...-explained
BC
https://www.ncaa.com/news/basketball-wom...ne-article
I don't think either of those explain NET very well. I have read a few technical articles, though those haven't been very complete. I haven't really tracked down details.
My best understanding is that this is basically an opponent adjusted efficiency stat. So it's some version of points per possession divided by opponents' points per possession allowed plus the equivalent for defense. That's basically the FEI stat for football applied to basketball.
Then there are adjustments for home/away and perhaps a few other things. The weights for each are determined each time they run the program by the entire women's division 1 results data base.
As I stated above, my general understanding is that it is fairly sophisticated statistically but the complexity makes it inherently opaque. There are pluses and minuses to that.
Thanks for all this -- that definitely helps
(01-30-2021, 09:30 AM)CTcard Wrote:(01-30-2021, 06:05 AM)M T Wrote:(01-29-2021, 11:25 AM)BostonCard Wrote:This is about WBB, so I think this is a better reference(01-29-2021, 09:59 AM)WBB fan Wrote: Can anyone explain the NET rating system to me?
https://www.ncaa.com/news/basketball-men...-explained
BC
https://www.ncaa.com/news/basketball-wom...ne-article
I don't think either of those explain NET very well. I have read a few technical articles, though those haven't been very complete. I haven't really tracked down details.
My best understanding is that this is basically an opponent adjusted efficiency stat. So it's some version of points per possession divided by opponents' points per possession allowed plus the equivalent for defense. That's basically the FEI stat for football applied to basketball.
Then there are adjustments for home/away and perhaps a few other things. The weights for each are determined each time they run the program by the entire women's division 1 results data base.
As I stated above, my general understanding is that it is fairly sophisticated statistically but the complexity makes it inherently opaque. There are pluses and minuses to that.
Thanks for all this -- that definitely helps
01-30-2021, 12:15 PM
NC State plays at #1 Louisville on Monday at 4 pm pacific. Come on, Wolf Pack!
"We have an unwritten rule around here not to do anything stupid."
-Casey Jacobsen, Feb 3, 2000
NC State plays at #1 Louisville on Monday at 4 pm pacific. Come on, Wolf Pack!
"We have an unwritten rule around here not to do anything stupid."
-Casey Jacobsen, Feb 3, 2000
01-30-2021, 12:56 PM
This is a little bit like the bias/variance tradeoff in statistics.
It seems like in order to avoid biases in a statistical measure of a team quality, you wind up incorporating more and more variables and making the measure increasingly convoluted and less reproducible (and sometimes more proprietary). Things like the NET and the FEI wind up giving you a summary that is not obviously confounded by things like opponent quality, but it winds up being a bit of a black box.
As always, George Box' aphorism applies: All models are wrong; some models are useful.
BC
It seems like in order to avoid biases in a statistical measure of a team quality, you wind up incorporating more and more variables and making the measure increasingly convoluted and less reproducible (and sometimes more proprietary). Things like the NET and the FEI wind up giving you a summary that is not obviously confounded by things like opponent quality, but it winds up being a bit of a black box.
As always, George Box' aphorism applies: All models are wrong; some models are useful.
BC
This is a little bit like the bias/variance tradeoff in statistics.
It seems like in order to avoid biases in a statistical measure of a team quality, you wind up incorporating more and more variables and making the measure increasingly convoluted and less reproducible (and sometimes more proprietary). Things like the NET and the FEI wind up giving you a summary that is not obviously confounded by things like opponent quality, but it winds up being a bit of a black box.
As always, George Box' aphorism applies: All models are wrong; some models are useful.
BC
It seems like in order to avoid biases in a statistical measure of a team quality, you wind up incorporating more and more variables and making the measure increasingly convoluted and less reproducible (and sometimes more proprietary). Things like the NET and the FEI wind up giving you a summary that is not obviously confounded by things like opponent quality, but it winds up being a bit of a black box.
As always, George Box' aphorism applies: All models are wrong; some models are useful.
BC
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