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KenPom 2015-2016: Back on Top: #1 in Luck (1/11)

RChildress107 said:
I think what Dv7 is saying is that the "luck" portion of Kenpom is really just "all of the variables that are not captured in these efficiency ratings which combine to explain why a team's record deviates from what these efficiency ratings would predict"

Kenpom choosing to call that collection of variables "luck" doesn't really solve the debate. We could argue all day about why Wake is 6-2 when Kenpom rankings suggest we should be 4-4 (or something). It could be that we are lucky, that we are clutch, that Manning would rather send a message or test guys out than put teams away, that we are point shaving, that we were lucky against UMBC, clutch against Indiana and UCLA, tired against Rutgers and lazy against Arkansas, etc.
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Yeah it acts as the error calculation and I view it generally as you might view a margin of error calculation in polling
 
Demonwolverine said:
One man's "luck" is another man's "clutch."

TJDK
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In the same vein that DV7 doesn't really believe in luck, I don't really believe in clutch.

Consistently, good players will continue to be good players in the waning moments of a game, while "lesser" players will continue to be "lesser" players in the waning moments of a game. Does that mean that some good players will falter down the stretch? Of course. Does that mean that "lesser" players will often times exceed what their established baseline for "skill" and "talent" is? Of course. That may even occur over the course of a career.

I would argue that those are mostly statistical outliers, however, and the overall indicator of how well a player will perform with the game on the line is how good they are as a player overall. I would take a .350 hitter in baseball in the 9th inning every single time over a .250 hitter in the 9th inning (all other things equal), regardless of the fact that the .250 hitter has 10 game winning hits in 15 at-bats, while the .350 hitter has 5 in 15 at-bats.
 
Deacsfan27 said:
In the same vein that DV7 doesn't really believe in luck, I don't really believe in clutch.

Consistently, good players will continue to be good players in the waning moments of a game, while "lesser" players will continue to be "lesser" players in the waning moments of a game. Does that mean that some good players will falter down the stretch? Of course. Does that mean that "lesser" players will often times exceed what their established baseline for "skill" and "talent" is? Of course. That may even occur over the course of a career.

I would argue that those are mostly statistical outliers, however, and the overall indicator of how well a player will perform with the game on the line is how good they are as a player overall. I would take a .350 hitter in baseball in the 9th inning every single time over a .250 hitter in the 9th inning (all other things equal), regardless of the fact that the .250 hitter has 10 game winning hits in 15 at-bats, while the .350 hitter has 5 in 15 at-bats.
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I think it's probably somewhere in the middle. I think most of what people think of as "clutch" is just good players trying a little bit harder at the end of games. I think this is especially true at the collegiate level.
 
DeacsATS said:
Just to clear something up (or at least attempt to): The luck factor has nothing to do with the KenPom rating calculation.

Said another way... The fact that Wake Forest is #1 in luck does not play into why we are #85 in the overall rankings. But, yeah, because we've played close games against terrible opponents (UMBC, Rutgers, Arkansas), the #85 Wake Forest ranking is lower than our record & SOS would otherwise suggest.
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The stat in and of itself is not used but the stat represents factors included in his analysis indirectly doesn't it? So teams with high Luck numbers are going to be lower in his ranking compared to other teams..ie they are presumed to be not as good as their record. What I'm not sure is how he starts the year. Apparently it's based on prior efficiencies of the returning players or something like that. Is that used throughout the season?

One issue he mentions: "It [his system] likes a team that loses a lot of close games against strong opposition more than one that wins a lot of close games against weak opposition." So the way Manning manages the team against weaker competition, we are doing the latter. Once we get into ACC play our ranking should move up even if we lose games (and our Luck drops).

I also keep tabs on the projected RPI which I believe mirrors the numbers used by the selection committee....and we suddenly jumped up into the 60s for some reason. We were in the 80s and 90s.

http://realtimerpi.com/rpi_Men.html

https://www.teamrankings.com/ncb/rpi/
 
I read the thread title as we were preseason #60 in luck.
 
pourdeac said:
The stat in and of itself is not used but the stat represents factors included in his analysis indirectly doesn't it? So teams with high Luck numbers are going to be lower in his ranking compared to other teams..ie they are presumed to be not as good as their record. What I'm not sure is how he starts the year. Apparently it's based on prior efficiencies of the returning players or something like that. Is that used throughout the season?

One issue he mentions: "It [his system] likes a team that loses a lot of close games against strong opposition more than one that wins a lot of close games against weak opposition." So the way Manning manages the team against weaker competition, we are doing the latter. Once we get into ACC play our ranking should move up even if we lose games (and our Luck drops).

I also keep tabs on the projected RPI which I believe mirrors the numbers used by the selection committee....and we suddenly jumped up into the 60s for some reason. We were in the 80s and 90s.

http://realtimerpi.com/rpi_Men.html

https://www.teamrankings.com/ncb/rpi/
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See below.

Preseason ratings were posted over the weekend. Here’s a reminder as to what goes into them…

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.

Over the next decade, it’s a near certainty that Arizona will win more Pac-12 games than Washington State, Kansas will win more Big 12 games than TCU, and Duke will win more ACC games than Boston College. So in the absence of looking at specific players, the projection first relies on recent team performance. Projected offense is largely determined by the quality of a team’s offense over the previous three seasons and its defense from last season. Projected defense uses similar variables.

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.

For the sake of accountability, here’s how various pre-season systems did last season, measured by average error in predicting conference wins across all 350 teams.

Hanner/SI 2.15
Hess/TeamRankings 2.16
Pomeroy 2.26
Adamson/Matchup-Zone 2.26
Torvik/T-Rank 2.35
It would be better to use overall regular-season record but the issue of in-season tournaments makes this quite a bit more difficult. At any rate, as has occurred in previous seasons, Hanner sets the standard in projections, although TeamRankings is a very, very close second. If you want your preseason ratings considered in future editions of this post, please send your conference predictions along before the season begins.
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RChildress107 said:
I think it's probably somewhere in the middle. I think most of what people think of as "clutch" is just good players trying a little bit harder at the end of games. I think this is especially true at the collegiate level.
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Or coaches being particularly adept at managing end-of-game situations either through subs, clock management, instilling calmness and confidence, working the refs. Where would "outcoaching" show-up?

Not saying that this is necessarily our situation... there are many valid arguments suggesting our 'coaching' may have actually made the games closer than they need be, but still, we've done a pretty good job in late game situations.
 
Deacsfan27 said:
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.
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Oh my God! We were penalized for getting rid of Bz.
 
So in his system:

..in the absence of looking at specific players, the projection first relies on recent team performance. Projected offense is largely determined by the quality of a team’s offense over the previous three seasons and its defense from last season. Projected defense uses similar variables.

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.

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.
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What I was wondering is if those data are used in the ranking once the season starts....as some sort of 'momentum' factor.
 
Let's focus away from the team as a whole and look at the example of a good three point shooter. The best single season NBA 3 point percentage I found is Kyle Korver in 09-10 at 54%. If he had a chance to hit the buzzer-beating game-winner in 15 games, you would expect him to make it 8 times and the team to go 8-7. If he happens to make his 54% shot every time and the team goes 15-0 over that stretch, you would say they are "lucky" under the KP model. If he happens to miss his 54% shot every time and the team goes 0-15 over that stretch, you would say they are "unlucky" under the KP model. It's not a matter of whether each individual shot is lucky or not, because it's close to a 50-50 shot each time. It's just that over time you expect the results to roughly match the probability. Flip a coin enough times and you will get streaks of mostly heads or mostly tails; if you were gambling on heads or tails in that stretch you would be "lucky" or "unlucky," as it went. Or, clutch.
 
SpringChicken said:
Let's focus away from the team as a whole and look at the example of a good three point shooter. The best single season NBA 3 point percentage I found is Kyle Korver in 09-10 at 54%. If he had a chance to hit the buzzer-beating game-winner in 15 games, you would expect him to make it 8 times and the team to go 8-7. If he happens to make his 54% shot every time and the team goes 15-0 over that stretch, you would say they are "lucky" under the KP model. If he happens to miss his 54% shot every time and the team goes 0-15 over that stretch, you would say they are "unlucky" under the KP model. It's not a matter of whether each individual shot is lucky or not, because it's close to a 50-50 shot each time. It's just that over time you expect the results to roughly match the probability. Flip a coin enough times and you will get streaks of mostly heads or mostly tails; if you were gambling on heads or tails in that stretch you would be "lucky" or "unlucky," as it went. Or, clutch.
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Or you would say Kyle Korver was clutch. Kyle Korver is not a coin and a player's shot percentage fluctuates given time, score, how closely defended the shot is, spot on the floor, etc.

Unless you are Steph Curry.
 
RChildress107 said:
Or you would say Kyle Korver was clutch. Kyle Korver is not a coin and a player's shot percentage fluctuates given time, score, how closely defended the shot is, spot on the floor, etc.

Unless you are Steph Curry.
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He is shooting an averagely-defended shot from the exact top of the arc each time, with his team down 88-90 and 1 second left each time. His percentage, X, may not be 54% but it is a number even if you don't know what it is. Or if it helps you, think of a free throw so the location and "guardedness" are controlled. But I doubt it'll help you based on what you just said.
 
Deacsfan27 said:
In the same vein that DV7 doesn't really believe in luck, I don't really believe in clutch.

Consistently, good players will continue to be good players in the waning moments of a game, while "lesser" players will continue to be "lesser" players in the waning moments of a game. Does that mean that some good players will falter down the stretch? Of course. Does that mean that "lesser" players will often times exceed what their established baseline for "skill" and "talent" is? Of course. That may even occur over the course of a career.

I would argue that those are mostly statistical outliers, however, and the overall indicator of how well a player will perform with the game on the line is how good they are as a player overall. I would take a .350 hitter in baseball in the 9th inning every single time over a .250 hitter in the 9th inning (all other things equal), regardless of the fact that the .250 hitter has 10 game winning hits in 15 at-bats, while the .350 hitter has 5 in 15 at-bats.
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I understand what you are saying but my personal experience, though pathetically limited, is to the contrary. I coached a bit in a few different sports (all youth-level, nothing more serious) and over time I thought there were basically two kinds of players. One kind wanted the ball at the end of the game. In baseball, they wanted to knock in the winning run or they wanted the ball hit to them if they were in the field protecting the lead, for example. The other kind lived in fear of being at the plate with two outs in the last inning or having the ball hit to them with two outs and the bases full. The first kind thrived on the pressure and made the play more often than they would in the non-pressure situation and the second kind made the play less often.

In the case of college or pro players, who have generally spent their lives being one of the best players on any team they were on, most are going to be the type that want the ball. Still, there is a spectrum and some thrive on the pressure more than others. So I pretty much do believe in clutch, meaning I think some players outperform their standard when the pressure is on and other underperform. I could, of course, be completely wrong.
 
The coaching change element is interesting. I think the exact opposite is true -- that it helps -- in football, but in basketball the player turnover that it can create might swing it the other way
 
ericstratton said:
I understand what you are saying but my personal experience, though pathetically limited, is to the contrary. I coached a bit in a few different sports (all youth-level, nothing more serious) and over time I thought there were basically two kinds of players. One kind wanted the ball at the end of the game. In baseball, they wanted to knock in the winning run or they wanted the ball hit to them if they were in the field protecting the lead, for example. The other kind lived in fear of being at the plate with two outs in the last inning or having the ball hit to them with two outs and the bases full. The first kind thrived on the pressure and made the play more often than they would in the non-pressure situation and the second kind made the play less often.

In the case of college or pro players, who have generally spent their lives being one of the best players on any team they were on, most are going to be the type that want the ball. Still, there is a spectrum and some thrive on the pressure more than others. So I pretty much do believe in clutch, meaning I think some players outperform their standard when the pressure is on and other underperform. I could, of course, be completely wrong.
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I mean people think Kobe is clutch and he is one of the worst shooters of all-time in the final seconds. For every guy that exceeds his baseline at the end of a game there is a guy who falls short of his baseline.
 
To simplify this matter, Wake's ranking is poor b/c thus far the defense has been atrocious. If this doesn't change then the season will be another failure & with a 6-12 ACC prediction, KPom is virtually saying Wake sucks & are lucky not to be 3-5/4-4.
 
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