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  1. #1
    Join Date
    Feb 2007

    MBB: Dork Polls 2018-19 Edition (starting w/ the NCAA's first release of NET)

    I complained last week that the NCAA hadn't released NET (the replacement for RPI) yet. And apparently they listened to me ;-)

    Here are the first NET rankings (which apparently will be updated daily):

    https://www.ncaa.com/rankings/basket...l-net-rankings

    Early season results are going to be wonky, of course.


  2. #2
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    I'd love to know what metrics they are using. Kansas has beaten good teams and yet cannot even crack the top 10. Virginia has played one of the worst schedules in all of D1, embarrassingly weak, and yet they are the #2 team. Loyola Marymount is the #122 KenPom team with the #314th weakest schedule... on what planet does any metric make them the #10 team in the country?

    I'm hoping this is just early season wonk and not some indication of a really fundamentally flawed formula.
    Why are you wasting time here when you could be wasting it by listening to the latest episode of the DBR Podcast?

  3. #3
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    Quote Originally Posted by JasonEvans View Post
    I'd love to know what metrics they are using. Kansas has beaten good teams and yet cannot even crack the top 10. Virginia has played one of the worst schedules in all of D1, embarrassingly weak, and yet they are the #2 team. Loyola Marymount is the #122 KenPom team with the #314th weakest schedule... on what planet does any metric make them the #10 team in the country?

    I'm hoping this is just early season wonk and not some indication of a really fundamentally flawed formula.
    A computer ranking system that overvalues UVA and Wisconsin?! Get right outta town!!! /s

    Funny little aside--KenPom also has a POY calculator/predictor, and when Zion was boasting a PER of 50+, the algorithm still had Ethan Happ as the favorite for POY based on early season metrics. Grant Williams (Tenn) was second. I imagine that's changed in one or many ways since I last looked, but thought it was funny. Maybe not 'haha' funny, but 'Zach Galifianakis doing math in his head' funny. It's pretty useless to look at the analytics-based rankings this early in the season, but useless =/= without some entertainment value.

  4. #4
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    Dec 2007
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    Google claims that AI algorithms are used in the formula. Maybe our robot overlords have seen the future and this is what it holds. Could someone call John Connor? Seriously, this poll is nonsensical. If there’s insufficient data to apply the formula then they should wait another month before releasing it.

  5. #5
    NC State is 31st with the easiest schedule in the world...what's not to like about these new metrics

  6. #6
    scottdude8's Avatar
    scottdude8 is online now Moderator, Contributor, Zoubek disciple, and resident Wolverine
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    Thanks for starting this thread Trouble, I was about to do it myself

    My initial reaction to this metric is that, while still (obviously) imperfect, it's a huge step forward over RPI, which was archaic at best. SI has an article I found explaining the NET rankings in a bit of detail: https://www.si.com/college-basketbal...system-explain
    To me the biggest issue/unknown is how that "Team Value Index" is calculated... it definitely takes into account a variety of factors that I think are good, it just doesn't explicitly say what formula is used to get the final index. I'm also curious as to how the five factors are weighted, which is another detail that wasn't presented there. Perhaps there's a more detailed explanation somewhere else on the interwebs.

    But again, this is a big improvement over RPI. The fact that the home/road factor is taken into account in two of the five factors makes me happy (I ranted and raved about the importance of that in evaluating teams for seeding a lot last year, haha). If it were me I might have eliminated scoring margin as it's own individual factor and instead made it a part of the "Team Value Index", because without context the margin of victory can be misleading (consider an 8 point margin that came about because the opposition fouled for the last minute and couldn't score, turning a close game into a larger margin, versus an 8 point margin that came about due to some late buckets with backups in the game). It also seems a bit silly to me to have both a pure and adjusted win percentage included. But maybe how the five factors are differentially weighted takes that into account.

    A spork from my end to the first person who can find either A) the direct formula used for the "Team Value Index" or B) any clear explanation as to how each of the five factors are weighted, haha.
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  7. #7
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    Quote Originally Posted by scottdude8 View Post
    Thanks for starting this thread Trouble, I was about to do it myself

    SNIP...

    A spork from my end to the first person who can find either A) the direct formula used for the "Team Value Index" or B) any clear explanation as to how each of the five factors are weighted, haha.
    It seems you're not the only one chagrined at the missing formula(s)--here's an article from earlier today by Jerry Palm of CBSSports (and stoic champ of the RPI): https://www.cbssports.com/college-ba...mula-a-secret/. He specifically cites the very complaints that you mention (ambiguity of TVI, unclear weighting of factors, and seeming redundancy of some factors with others).

    However, the thing that is missing from the what the NCAA revealed with the release of the NET ratings is any of the supporting data that goes into the rankings. All we are being given for now is each team's overall record and breakdown by home/road/neutral/non-Division I. That's it. There is not one piece of useful information on the rankings page except the ranking itself...

    The NCAA has been working very hard in recent years to make the selection process as transparent as possible. Not releasing the formula for this is a significant step backwards in that process. And, while it may be so complicated that nobody on the actual committee can understand it, let alone explain it, surely there is one geek at every school that would. The geek writing this column is confident he would ultimately understand it also.
    Also, KenPom wrote something for The Atlantic in August breaking down NET, but I'm not a subscriber, so I can't speak to whether he was privy to the innards of the tool.

    Here's what the NCAA itself had to say, when describing "everything you need to know about NET" (spoiler alert: it doesn't answer the questions posed): https://twitter.com/marchmadness/sta...etball-ranking

  8. #8
    Apparently a game @Wofford is weightier than a neutral tilt with UK, the Zags, Auburn, etc. Who knew? (dare I say garbage in, garbage out?)

  9. #9
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    Quote Originally Posted by HereBeforeCoachK View Post
    Apparently a game @Wofford is weightier than a neutral tilt with UK, the Zags, Auburn, etc. Who knew? (dare I say garbage in, garbage out?)
    The CHeats are ranked #21 in the NET, which is significantly lower than the human polls. Are you looking at some sort of SOS component?

  10. #10
    Join Date
    Feb 2007
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    Washington, D.C.

    NET

    It may be an improvement over RPI, but almost anything would be. Pitt at #23? You gotta be kidding. tOSU at #1?

  11. #11
    Join Date
    Oct 2009
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    Quote Originally Posted by MChambers View Post
    It may be an improvement over RPI, but almost anything would be. Pitt at #23? You gotta be kidding. tOSU at #1?
    give it a break. any ranking system is going to be highly biased by preseason rankings at this point in the year. Even kenpom says his own numbers are a bit of a crapshoot until the end of january or so...and I can guarantee the NCAA puts less thought into the veracity of their preseason rankings than does he.

    We'll see what it looks like in a couple of months.
    1200. DDMF.

  12. #12
    Nate Silver is not impressed

    Twitter
    "These are the worst rankings I've ever seen in any sport, ever. NCAA needs to go completely back to the drawing board...I guess I'm not sympathetic because a lot of smart people have worked on this problem (power rankings) for a LONG time and the NCAA ignored all that and came up with something that doesn't reflect methodological best practices and which doesn't make sense, basketball-wise"

  13. #13
    Quote Originally Posted by nmduke2001 View Post
    Nate Silver is not impressed

    Twitter
    "These are the worst rankings I've ever seen in any sport, ever. NCAA needs to go completely back to the drawing board...I guess I'm not sympathetic because a lot of smart people have worked on this problem (power rankings) for a LONG time and the NCAA ignored all that and came up with something that doesn't reflect methodological best practices and which doesn't make sense, basketball-wise"
    This is a pretty harsh damnation by Silver, who is in a position to have his opinion taken seriously. Clearly these rankings are absurd. If Duke is only 6th after being 5-1 and beating Kentucky, Auburn and San Diego and barely losing to Gonzaga, then that's a system that will never ever have Duke a top seed. I thought these rankings were foolish before reading Silver's commentary - and afterwards, I'm even more convinced. Sounds like Silver kind of saw this coming.

  14. #14
    Join Date
    Feb 2007
    Quote Originally Posted by nmduke2001 View Post
    Nate Silver is not impressed

    Twitter
    "These are the worst rankings I've ever seen in any sport, ever. NCAA needs to go completely back to the drawing board...I guess I'm not sympathetic because a lot of smart people have worked on this problem (power rankings) for a LONG time and the NCAA ignored all that and came up with something that doesn't reflect methodological best practices and which doesn't make sense, basketball-wise"
    Nate Silver, if he were wise, would be lauding why human analysis of data analytics is important and justifying his expertise as better than ML/“AI”.

  15. #15
    Join Date
    Feb 2007
    Quote Originally Posted by fuse View Post
    Nate Silver, if he were wise, would be lauding why human analysis of data analytics is important and justifying his expertise as better than ML/“AI”.
    I was asked via DM to expand what I meant by my comments above.

    Here goes:

    I’m a big believer in data and fact, and have a lot of respect for Nate Silver.

    My main point was really more about flaws in the formula, and that a sharp statistician like Mr. Silver could have used NET as a foil to discuss the differences between data (raw analytics) and information (transforming data into a story).

    It was a bit of a stretch to compare machine learning and artificial intelligence to the blunt tool that is NET (although I would contend NET may make a good case study in inherent bias).

    NET, at best, is just data (or as others have pointed out, it may just be too early for the output of the formula to have any tangible meaning). I’m not sure it will ever produce information.

    A brief aside on data and information.
    An example of data might be, an ostrich lays the biggest bird egg.
    If you’ve never seen an ostrich egg, that data isn’t super meaningful.
    If I know you’ve seen a chicken egg, or assume it is a common enough reference point and add an additional data point, an ostrich egg is equivalent to 24 chicken eggs, now you have information.

    (I resisted temptation to create an example using basketball players and everyone’s favorite unit of measurement.)

    Disclaimer: I’m not a statistician or mathematician, and one of my favorite mantras is “often wrong, never in doubt”.

    With a little luck, maybe someone found this useful or mildly entertaining.

    Let’s Go Duke!

  16. #16
    The NET rankings are starting to look more reasonable/representative (and playing Texas Tech and St John' looks like it will be much better for our SOS than expected pre-season):

    1 Michigan
    2 Virginia
    3 Duke
    4 Texas Tech
    5 Tennessee
    6 Kansas
    7 Gonzaga
    8 Nevada
    9 Michigan St.
    10 Auburn
    11 Wisconsin
    12 Buffalo
    13 Ohio St.
    14 Houston
    15 North Carolina
    16 Nebraska
    17 Oklahoma
    18 NC State-seems a bit high
    19 Louisville-seems a bit high
    20 Indiana Big Ten
    21 San Francisco-high
    22 Marquette
    23 Villanova
    24 Virginia Tech-a little low
    25 Cincinnati
    26 Arizona St.
    27 Mississippi St.-a little low
    28 Furman
    29 Florida St.-a little low
    30 St. John's (NY)
    31 Purdue Big Ten
    32 Syracuse
    33 Kentucky
    34 UCLA
    35 Iowa St.
    36 Utah St.-high
    37 Arizona-high
    38 Liberty-high
    39 LSU
    40 Colorado
    41 Butler
    42 Maryland-probably a little low
    43 Washington
    44 Iowa
    45 Lipscomb
    46 Kansas St.
    47 Northwestern-high
    48 Florida
    49 San Diego-high
    50 North Texas-high

    51-60 include TCU, Minnesota and Creighton, all of whom it's hard to see as behind Northwestern, San Diego and North Texas. But, that's really nit-picking at this point

  17. #17
    Pfftt...State will prove doubters wrong. The NET is just very forward thinking.

  18. #18
    Join Date
    Oct 2009
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    Durham
    Quote Originally Posted by Nugget View Post
    The NET rankings are starting to look more reasonable/representative (and playing Texas Tech and St John' looks like it will be much better for our SOS than expected pre-season):

    1 Michigan
    2 Virginia
    3 Duke
    4 Texas Tech
    5 Tennessee
    6 Kansas
    7 Gonzaga
    8 Nevada
    9 Michigan St.
    10 Auburn
    11 Wisconsin
    12 Buffalo
    13 Ohio St.
    14 Houston
    15 North Carolina
    16 Nebraska
    17 Oklahoma
    18 NC State-seems a bit high
    19 Louisville-seems a bit high
    20 Indiana Big Ten
    21 San Francisco-high
    22 Marquette
    23 Villanova
    24 Virginia Tech-a little low
    25 Cincinnati
    26 Arizona St.
    27 Mississippi St.-a little low
    28 Furman
    29 Florida St.-a little low
    30 St. John's (NY)
    31 Purdue Big Ten
    32 Syracuse
    33 Kentucky
    34 UCLA
    35 Iowa St.
    36 Utah St.-high
    37 Arizona-high
    38 Liberty-high
    39 LSU
    40 Colorado
    41 Butler
    42 Maryland-probably a little low
    43 Washington
    44 Iowa
    45 Lipscomb
    46 Kansas St.
    47 Northwestern-high
    48 Florida
    49 San Diego-high
    50 North Texas-high

    51-60 include TCU, Minnesota and Creighton, all of whom it's hard to see as behind Northwestern, San Diego and North Texas. But, that's really nit-picking at this point
    it makes sense. I still wouldn't be concerned about outliers until the end of january or so...and was kind of dissapointed that Nate Silver railed on it when to a large degree, the naivete of the rankings were due to a lack of preseason rankings...something that makes rankings look like crap early, but is likely a good thing down the road.

    Now, I'd argue that the NCAA shouldn't have bothered to release them...but such is life.
    1200. DDMF.

  19. #19
    Quote Originally Posted by fuse View Post
    I was asked via DM to expand what I meant by my comments above.

    Here goes:

    I’m a big believer in data and fact, and have a lot of respect for Nate Silver.

    My main point was really more about flaws in the formula, and that a sharp statistician like Mr. Silver could have used NET as a foil to discuss the differences between data (raw analytics) and information (transforming data into a story).

    It was a bit of a stretch to compare machine learning and artificial intelligence to the blunt tool that is NET (although I would contend NET may make a good case study in inherent bias).

    NET, at best, is just data (or as others have pointed out, it may just be too early for the output of the formula to have any tangible meaning). I’m not sure it will ever produce information.

    A brief aside on data and information.
    An example of data might be, an ostrich lays the biggest bird egg.
    If you’ve never seen an ostrich egg, that data isn’t super meaningful.
    If I know you’ve seen a chicken egg, or assume it is a common enough reference point and add an additional data point, an ostrich egg is equivalent to 24 chicken eggs, now you have information.

    (I resisted temptation to create an example using basketball players and everyone’s favorite unit of measurement.)

    Disclaimer: I’m not a statistician or mathematician, and one of my favorite mantras is “often wrong, never in doubt”.

    With a little luck, maybe someone found this useful or mildly entertaining.

    Let’s Go Duke!
    I believe Mr Silver would agree with me here in that humans still play an important (the most important?) role in most ML/AI models, namely in designing/creating the features of the model. AI/ML is not just chucking a ton of data into some black box that figures it all out. Thus the importance of human decisions to, as Jason Evans relayed, cap the win margin at 10. That's a major decision made by a human. I'm not sure what goes into NET vs Nate Silver's models versus Ken Pomeroy's models, but I bet Nate's and Ken's are better...

  20. #20
    Join Date
    Oct 2009
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    Quote Originally Posted by JayZee View Post
    I'm not sure what goes into NET vs Nate Silver's models versus Ken Pomeroy's models, but I bet Nate's and Ken's are better...
    I don't think you'll find disagreement among dorks that the latter 2's models will be better...but they're trying to accomplish different things. Two of them are predictors, one of them is attempting to seed teams both on absolute strength as well as reward for doing certain things that the NCAA likes to see...like winning games. So far as the results aren't as far out of whack as some of the RPI ones were, I'm fine with bumping a team up a seed line or two if they won a bunch of big games, even if they were close, over a team that lost the close games and beat everyone else a bit more.

    So saying "we won't reward you for winning by more than 10" does two things:

    1) it never encourages you to pour it on (though 10 is likely low)
    2) you get more value by playing teams that are closer to you in ranking

    Say I'm being compared to some other team. We both play Cupcake state. Team light blue wins by 15, and we win by 20. The system considers that the same even though there is some amount of predictive value in comparing those results. Now, instead we both play a slightly heavier weight team...like pound cake polytechnic...they win by 7 and we win by 10. Now we look better than they do...and that distinction would have been lost if we had played cupcake.

    So even if it discards some predictive value, it encourages teams to play teams more equal in strength. I have no problem with that. I also have no problem rewarding more than 2 "points" worth of distinction between a 1 point win and a 1 point loss. You want to reward teams for actually winning the game, even if it has less predictive value.

    I'm fine with these things. You should be rewarded for them. This system is getting far more flac than it should.
    1200. DDMF.

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