You must not be that crazy if it only took me 2 guesses.View attachment 165782
View attachment 165785
Not saying we should expect an NBA career like Grant Hill had but as far as Senior Year AA season and style, tell me where the gap is.
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You must not be that crazy if it only took me 2 guesses.View attachment 165782
View attachment 165785
Not saying we should expect an NBA career like Grant Hill had but as far as Senior Year AA season and style, tell me where the gap is.
So maybe it’s primarily that Torvik discounts our buy game blowouts (and maybe doesn’t care that Purdue was 25 point instead of 15pt win? But that’s not a mismatch) whereas KenPom just adjusts for opponent quality and keeps every possession of ever game.
It’s weird though because some of the lowest quality games were buy games
I've been wondering how some of the different systems phase out last year's data. If they keep all of last season's data together and phase it out as a group as we get farther into the new season that would yield different results for us than if they start phasing out the oldest games from the previous year until it is all gone. Because our metrics were better for the first half of last year than the second half.In addition to @Sigmapolis's post, I thought I saw somewhere that Pomeroy adjusted his formula before this year to more aggressively move teams based on current-season results (that is, lose the preseason information faster).
Now I can't find anywhere where he said that, but it does seem like it could be true this year with how Iowa State shot up on Kenpom. I think in Otz's early seasons, it was flipped, with Torvik reacting faster to Iowa State overperforming. Or I might be completely misremembering.
I ran it by my wife, she says I am f'ing crazy but she doesn't even know who Grant Hill.You must not be that crazy if it only took me 2 guesses.
That's a good question, but I'm pretty sure it's more similar to the first one. Because the preseason ratings aren't just taking data from the last season.I've been wondering how some of the different systems phase out last year's data. If they keep all of last season's data together and phase it out as a group as we get farther into the new season that would yield different results for us than if they start phasing out the oldest games from the previous year until it is all gone. Because our metrics were better for the first half of last year than the second half.
That has always been my assumption, but I'm starting to wonder. And I wouldn't think they remove them one by one as the season goes one, but some type of phase out that emphasizes most recent data points. It sure has felt like on Torvik and a couple other metrics that we have faced headwinds over the last month or so that keep our overall rankings below what they would be if it was just this years data, when it feels like it should be the opposite and we keep slowing moving up as last years data falls away.That's a good question, but I'm pretty sure it's more similar to the first one. Because the preseason ratings aren't just taking data from the last season.
The preseason ratings come from formulas that include transfers, recruits, and outgoing players, and those players' prior production (or recruiting rankings, for freshmen) to calculate the projected offensive rating. Then the defensive ratings do more heavily lean on the program's previous years' defensive ratings, because individual defensive metrics don't translate as much as a coach's defensive success from year to year.
If all of that is accurate, I don't think you could simply remove games from the prior year in the formula as you get further into the current season. My assumption has always been that it's more of a weighted average. For instance, after game 1, Bartthag might be 95% preseason and 5% current season, while after game 10, it might be 85% current season and 15% preseason.
10 quad 1 games in the remaining 15 games. its nuts that this team is projected to win 27 or 28 games, but they are that good.
Curious who our projected Q2 loss is.
It's probably just more of an assumption that statistically based on the number of quad 2 games we have remaining we will lose one of them rather than it being a specific opponent.Curious who our projected Q2 loss is.
I agree. Luckily we're not going to find out.Michigan drops 3 spots with a home loss against unranked Wisconsin. If we lose at KU, I bet any amount of money that we drop much further.
If we lose a close game at Kansas and win at Cincinnati, I would take that bet we don't fall below Purdue, Duke, and Houston. None of those three play a ranked team this week and its still in people's consciousness that we killed Purdue at Mackey. We would almost certainly fall below UConn and Michigan.Michigan drops 3 spots with a home loss against unranked Wisconsin. If we lose at KU, I bet any amount of money that we drop much further.
Shane Mettlen, Daily News RecordWho did we get our #1 vote from?
David Jablonski (Cox Media Group) has us 5th, after UA, Nebby, Mich & Vandy. I think that's the lowest. Most have us #2. A good number have UConn 2 and us 3.Shane Mettlen, Daily News Record