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2015 Maui Invitational: Hudson & Watson to Play in 3rd Place Game v. UCLA 7:30 ESPN2

Number of teams ranked #80 or better in Kenpom with a worse defense adjusted rating than us? One.

You have to drop beyond 110 before you hit more than 5.
 
BobStackFan4Life said:
I'd like for Doofus or Numbers to explain this.
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2 things: KP rankings early in the season are a mix of actual game data and preseason rankings. So they aren't super valuable early in the season.

Also KP doesn't really look at "wins and losses" in a binary sense. To their models, winning a game by 1 point and losing a game by 1 point are approximately the same.
 
Shouldn't have let UCLA get that gimme layup at the end then. Gonna hurt our kenpom.
 
Per ESPN this was our first game against UCLA since the 1962 NCAAs. I could have sworn we played them at some point in the late 80s or early 90s. 53 years!

Great job in Maui, Deacs.
 
Adding a team's RPI # and a team's Kenpom # will project the NCAA at large field with impressive accuracy (lowest combined scores get in). Usually will predict 34/36 or so each year.

Makes sense because it is a balance of win/loss resume (RPI) and actual team strength (Kenpom). And these are the two things the committee will qualitatively try to balance.
 
inspectah said:
Per ESPN this was our first game against UCLA since the 1962 NCAAs. I could have sworn we played them at some point in the late 80s or early 90s. 53 years!

Great job in Maui, Deacs.
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I know that we haven't played them much but it's pretty cool that Wake Forest has never lost to UCLA or Indiana in basketball.
 
I'm shocked we won this game without Crawford.

Full strength and we have a legit squad.

Big ups to Crab tonight. He is a key player for us. Also Mitch really showing me something. We need guys who can lead like him
 
KP means nothing until February. It is still based largely on personal opinions and not data. Mostly personal opinions since there isn't near enough data. They shouldn't even put it out until January.
 
88Deac said:
KP means nothing until February. It is still based largely on personal opinions and not data. Mostly personal opinions since there isn't near enough data. They shouldn't even put it out until January.
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This is not true either. I think by about 10 games into the season KP has phased out the preseason rankings.

And there is no personal opinion involved in the preseason rankings - it is all data driven too. It looks at average player progressions from their database (i.e. how much a freshman's minutes, efficiecncy, etc. improve to their sophomore year on average) and apply that to each returning player. And then gives freshman production for highly rated recruits in accordance with their RSCI ranking. It's a little fuzzy, and Ken admits as much, but there is certainly no personal opinion.
 
I mean that I thought he had pretty good skills, particularly offensive rebounding. But he has given us nothing and seems lost out there. No intensity. Can't even make free throws.
 
One game at a time, but I like our chances in the next 4. 8-2 (with some nice wins in there) would be nice before the schedule gets much tougher.
 
From the Ken Pomeroy himself on preseason ratings:

The components and weighting is based on a regression of the past nine seasons. The system is, by 2015 standards, pretty simple. It doesn’t try to project playing time for individual players. It doesn’t know about transfers, and all but 5-star recruits are virtually ignored. If you think your favorite team is ranked too low, the reason is probably that there are really good transfers or recruits arriving.

In the most general sense, the main ingredient in the system is inertia. If a team has been good in the recent past, it’s likely to be rated well in the preseason. As much as we like to think of college basketball as this crazy sport where anything can happen, there’s just not much class mobility in the game. I think we all understand that the Big Ten will always be better than the SWAC, but even within conferences there’s a clear power structure that might vary from year to year but is very predictable over the long term.

Returning personnel is considered as well. Generally, the more players returning, the better. However, the quality of the player is also a factor. Losing a high-usage/high-efficiency player hurts a team’s offense a lot more than losing a role player. In fact, a low-usage inefficient role player that returns can actually hurt a team’s rating. So while chasing off a player is not the most ethical practice, it is apparently a good sign for the program when a struggling player seeks a new school.

A new addition this year is accounting for injured players from the previous season. If a returning player played a partial season, then his future impact is considered to be more than it was in previous versions of the system. Note that his doesn’t account for cases where a player completely missed the previous season. Michigan is the team that benefits most from this, with both Caris LeVert and Derrick Walton returning after having missed large portions of last season.

There is also a penalty for a coaching change, with a greater hit for teams ranked higher. Basically, teams that change coaches tend to underperform their counterparts that have not changed coaches, all other things being equal.

The predictions are calibrated on end-of-season ratings. However, in a departure from previous practices, the national averages I’ve subjectively imposed are designed to capture conditions at the beginning of the season. Currently, I’ve got an efficiency of 100 as the national average. The end-of-season number will undoubtedly be higher than that. Likewise, the average tempo of 68.5 should be an overestimate of the season-long average. Although, that is less certain.

While the projections for offense and defense are no longer state-of-the-art, I think the tempo projections are the best around. (Mainly because I’m not aware of any competition.) It’s far more accurate to project a team’s pace using their head coach’s history than the team’s history, and that is how this season’s tempo projections work. In the case of rookie head coaches, there’s just some regression to the mean applied to the team’s tempo from its previous season. But for coaches with a history there’s a lot of weight placed on that history.
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Basically Wake is really hard to predict. Our two freshmen are exceeding their projections (basically they don't weigh in at all to begin with because they aren't top 100 RSCI players), one of our best players and point guards hasn't played yet, and arguably our 3rd best player just started playing last night.

Since Wake is hovering around where they were projected to be with a full roster, I think exceeding expectations moving forward is a real possibility.

Also, there aren't "personal opinions" in the ratings other than how it is designed as a whole by KenPom. It's a predictive and analytical statistical model.
 
simosfrostyone said:
I mean that I thought he had pretty good skills, particularly offensive rebounding. But he has given us nothing and seems lost out there. No intensity. Can't even make free throws.
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Maybe he was one of the guys with the flu?
 
inspectah said:
Per ESPN this was our first game against UCLA since the 1962 NCAAs. I could have sworn we played them at some point in the late 80s or early 90s. 53 years!

Great job in Maui, Deacs.
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We played Jason Kidd-led Cal during that span. Might be what you're thinking about.
 
All things considered, I think that UCLA win was the best and biggest win of the last 6 years. We have beaten higher ranked teams at home during that time, but beating what should be a bubble/NIT quality team on a neutral site without either of our starting guards was really a great win.
 
Agreed. It sets the stage to pull off more wins against a tough schedule and to be tested come ACC season.
 
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