APBRmetrics

**Joe** · Joined: 27 Sep 2009 Posts: 94 Location: Long Island, NY

I've never really gotten too much into APM, aside from occasionally glancing at it when trying to analyze a player's defense. I just can't understand when it spits out results like the following, so maybe someone can give me some feedback as to how exactly this is possible.

http://basketballvalue.com/teamplayers.php?year=2009-2010&team=DEN

Going by 1 year APM, the Nuggets only have three above average players this season, and they all play the PF/C positions (Birdman, Nene, Kenyon). Lawson and Billups are massively below average players (so far below average that being above average for either of them doesn't even fall within the SE), and even Melo is below average.

I just want to know, what on earth is going on in games to make the statistic spit out this result? How is it coming to the conclusion that the Nuggets' entire backcourt sucks (including their four highest usage players) in spite of them being the second best team in the West? How are Chauncey Billups and Tywon Lawson playing at a level that suggests they're not even replacement level players?

I get APM is inexact and there's standard error and all this, but when I see stuff like this, it makes me wary about trusting anything, because these results are so unbelievably wonky that it just makes me question everything. I'm really curious as to how exactly this happens, because maybe it can help me better understand what I'm missing here.
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**Joe** · Joined: 27 Sep 2009 Posts: 94 Location: Long Island, NY

And on a slightly related note, if Joe Sill reads this, I'd be curious if you plan on cranking out some RAPM for this season, seeing how we're at the midway point. Would be curious to see how your numbers evaluate this situation, and maybe the Four Factors numbers could give some more insight.
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Crow · Joined: 20 Jan 2009 Posts: 800

Based on the 2 year data at basketballvalue the basic story with Hilario, Martin and Andersen is still positive overall, just far less extreme.

Based on hoopnumbers previous 3 year regularized data Hilario's defensive performance helped more than his offense hurt. Martin helped with both but mainly on defense. Andersen just barely helped on defense and the offensive drag was bigger. The effects are all much more muted and much more believable to me.

Billups, Smith and Melo were all big positives on offense and light to moderate (Melo) on defensive liability by Hoopnumbers regularized.

The stories between these versions of Adjusted +/- are very different.

I too hope to see regularized Adjusted data for this season at some point. I'd feel more comfortable with that and I think less extreme cases / outlier results would go over better with more people. Though that data is still worth seeing and thinking about.

**Joe** · Joined: 27 Sep 2009 Posts: 94 Location: Long Island, NY

DSMok1 · Posted: Wed Jan 27, 2010 3:53 pm Post subject:

I thought I'd post an approximate of what perhaps we SHOULD see: the statistical plus/minus for Denver so far. This should give us an idea of where things may be a little weird:

Crow · Joined: 20 Jan 2009 Posts: 800

Okay, then we differ some.

i think the multi-year products may be more useful than the one year versions even for understanding this season.

But hoopnumbers can produce 1 year regularized and it sounds like we'd both be interested in that.

In the end I'll be as or more interested in a freshened multi-year regularized product. As my main source though I'm for having and using them all.

Crow · Joined: 20 Jan 2009 Posts: 800

Would you agree that SPM misses shot defense and therefore might rate the offensive-biased perimeter guys too high and the defensive-biased interior guys too low?

Crow · Joined: 20 Jan 2009 Posts: 800

DSMok1 you've used stat weights for SPM based on non-regularized Adjusted +/- so far, correct? Any interest in pushing on to using stat weights for SPM based on regularized Adjusted +/-?

Any other ways you see for the two methods to help improve each other?

Any valid for SPM to help improve the initial APM that in turn helps the SPM and so on?

What is your view on after-production blends of them? Equal or mostly statistical or different ratios for offense and defense?

Mike G · Posted: Wed Jan 27, 2010 4:09 pm Post subject:

I was browsing bv.com also, and was struck by how many teams, if they went with their 5 best (APM) players, would be using either 4 bigs and a SF, or 4 guards and a F.

As emphatically as I don't understand these things, DSMok's synopsis has a definite ring of believability: Teams which very rarely use 'big' or 'small' lineups can get wacky results from APM, based on the results of relatively few minutes.
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DSMok1 · Posted: Wed Jan 27, 2010 4:24 pm Post subject:

Crow · Joined: 20 Jan 2009 Posts: 800

Mike, I was about to check into how polarized overall Adjusted +/- is for interiors vs perimeters and try to understand more about the teams that are polarized one way vs. another vs. not. I assume that the offensive and defensive splits tend to be even more polarized.

DSMok1 so would you consider going roughly 80% Statistical / 20% Adjusted like Dan Rosenbaum did with his Overall Statistical shortly after the beginning of all this as 1) a step back or 2) not much of an improvement or 3) select your own phrase?

I think the results of regularized APM are overall better than the non-regularized, more so for players at each extreme, but leave that to jsill to address if he wishes.

DSMok1 · Posted: Wed Jan 27, 2010 4:55 pm Post subject:

biggles · Joined: 15 Apr 2009 Posts: 2

Preface: A good player not falling within a standard error of the zero average (using a small sample size): not a cause for concern. Many good players not falling within 2 SEs of zero: maybe the model is busted.

If (the basketballvalue version of) APM had a thought process, it would be something like:

Afflalo/Anthony/Billups/Nene/Martin: 398 minutes, raw rating 10.61

"hey the Nuggets starting lineup is doing reasonably well, some of the players must be good"

Afflalo/Andersen/Nene/Lawson/Smith: 58 min, rating 38.75

"whoa this lineup is even better! but it's a small sample so let's keep looking"

Andersen/Anthony/Carter/Nene/Smith: 38 min, rating 50.16

"this is their best common lineup! in fact all the common lineups with Nene seem to do well. it's probably because Nene's awesome. but if Nene's awesome, then why doesn't the starting lineup do better? somebody on it must suck."

Andersen/Anthony/Billups/Lawson/Martin: 15 min, rating -42.86

"wow this lineup sucks. it can't be because of Andersen, because most lineups with him do better than the starters. that means all the rest of the guys suck. especially Billups, he never turns up on any great lineups, he must be horrible. oh but this is only 15 mins so let's put huge standard errors on everything."

***

Even though APM depends less on low minute lineups than high minute ones, it's still heavily influenced by outliers, and maybe if you're going you want to use APM for single seasons for some reason, you should downweight the low minute lineups even more. (I don't have a good mathematical idea of how best to do this.) Or just go back to elementary school and use unadjusted +/-, which for small samples is probably more accurate in some sense, at the expense of losing the ability to differentiate between teammates.

**Joe** · Joined: 27 Sep 2009 Posts: 94 Location: Long Island, NY

Crow · Joined: 20 Jan 2009 Posts: 800

I too would like to see a run that "downweights the low minute lineups even more" or even eliminates the really small and see how much difference that makes.

In the case of Denver this season using a 0.5% of total team minutes lineup cutoff you'd still have 2/3rds of the data. Use a 1% cutoff you'd still have half the data but maybe not enough especially in a single season set. Just downweighting it might be better but if you had the time, check out each.