You Are Here > Basketball-Reference.com > BBR Blog > NBA and College Basketball Analysis

SITE NEWS: We are moving all of our site and company news into a single blog for Sports-Reference.com. We'll tag all Basketball-Reference content, so you can quickly and easily find the content you want.

Also, our existing Basketball-Reference blog rss feed will be redirected to the new site's feed.

Basketball-Reference.com // Sports Reference

For more from Neil, check out his new work at BasketballProspectus.com.

Layups: Best Defenders in 2011

Posted by Neil Paine on April 13, 2011

At Back Picks, ElGee took a look at the top individual defenders of the 2010-11 NBA season.

ShareThis

18 Responses to “Layups: Best Defenders in 2011”

  1. AHL Says:

    "Top Individual Defensive Players from Top Teams that I Happen to DVR Their Games This Season and Analyze" therefore Mike Miller is a top defender.

  2. Matt Says:

    I agree with #1. The sample sizes are laughably small.

  3. huevonkiller Says:

    Mike Miller has terrible counterpart per on 82games.com, so that should be incorporated into the analysis.

  4. Nathan Walker Says:

    @Huevonkiller

    Counterpart PER doesn't pass the laugh test - while Howard is #2, Garnett is #28.

    Garnett is #2 in defensive win-shares, and #1 in regularized defensive plus-minus (7th in unadjusted Net defensive Plus-Minus).

    But--Kevin Love is the prime reason why PER is so obviously wrong -- rebounds are NOT that important (as was highlighted by Engalmann's study. He is 4th in 82games' play-by-play PER and 6th in Net PER, yet his impact is somewhere between neutral and a little above neutral.

  5. ElGee Says:

    Oh, I agree with #1 too that sample size is a problem. The stat-tracking information should be balanced against other information -- that's why the sample sizes are provided. (And if one has a synergy account, that too.) The Defensive EV is merely a sorting tool here, it's not a definitive ranking.

    My question is, would rather have none of the information, or 5-25 games of data to work with? (It's19 Heat games...I wouldn't call Miller's sample "laughably small.")

  6. Ed Says:

    Okay, I'm glad to see that I'm not the only one who thought this was a fairly bizarre analysis.

  7. AHL Says:

    #5 - No, it's not Miller's sample that's laughably small, his sample is actually laughably big. The problem is I'd rather this article not proclaim to be an analysis of the "NBA season's best defenders" when it's not actually looking at the entire NBA season. It says right there in the methodology that data is pulled from games recorded on DVR, and that last place teams didn't get enough data, so I can only assume the entire season wasn't actually considered, and probably only nationally televized games were recorded (hence Mike Miller's large sample). Like how can you only have 23 possessions of Iguodala, who would make a fantastic topic when discussion this year's best defenders?

  8. ElGee Says:

    In a Neil Paine special, I've added a D RAPM run to the final table (I thought I had that in originally but apparently not).

    #7 That's 23 "used" defensive possessions for Iguodala. I'm including him because of all the defenders who are in the discussion, he's really the main guy who is really small-sampled for my stat. Wings have a lower defensive usage on average than bigs, so it takes more time to accrue large samples of "relevant" defensive events. I only have 4 76er games because, sadly, they aren't on TV much (and that will double in the playoffs, at minimum.)

    Again though, this should be looked at as a cross-section of defensive information. It's my contention that we are grossly lacking defensive stats in basketball, and this is an attempt to look at the rough tools we have and paint a picture. Call me crazy, but I don't think overlooking Minnesota, New Jersey, Toronto, Washington, Cleveland and Sacramento is doing a disservice to this discussion. What good defender is left out there, anyway?

  9. huevonkiller Says:

    Nathan your list is laughable, stop being a hypocrite. Your list is sure getting cute, don't know about reasonable though. Chris Bosh above Wade and Bryant? Steve Nash? I'll go with SPM if I want to incorporate plus-minus. Not adjusted plus minus nonsense.

    Nathan you're painting a fuzzy picture aren't you? Rebounds aren't that important, yet you're citing the win shares formula that clearly demonstrates Kevin Love is an elite player? What is your point? The Timberwolves are surrounded by incompetent defenders, not named Kevin Love. This has led to their struggles, counterpart PER also reflects that.

    Counterpart PER is the study cited in this article, and it doesn't do that correctly. So it should be mentioned.

  10. Jerry Says:

    #4
    1. There was no study, just numbers
    2. If you cite someone's name, try to at least get it somewhat right

  11. AHL Says:

    #8: If Mike Miller and Brandon Jennings can make it to the tops of your lists, anything is possible!

  12. P Middy Says:

    #8 - first of all, good on you for giving this a shot. I agree that there are problems with some of the method, but I like the effort. I know I wouldn't have spent the time required to make that post happen.

    However, the thing about stats is that you never know what is hiding in there. I'd rather analysis skip Minnesota, Toronto, New Jersey, Cleveland, and Sacramento because of time/resource constraints than an assumption that there will not be valuable data.

  13. Nathan Walker Says:

    @Huevonkiller

    Study after study have shown that PER overvalues rebounds. Dean Oliver's ORTG on which Win Shares are based doesn't particularly have this issue. Why are you throwing out all these ad hominem attacks on me? I'm just presenting an argument.

  14. Nathan Walker Says:

    @Huevonkiller

    Ridge plus-minus numbers have two benefits that no other statistic can give us.

    First, that it is extremely conservative: a player must show continued, repeatable performance in order to do well in ridge +/- (and vice versa) because of the penalty factor. One way of thinking about it is that the algorithm basically only changes the values (up or down) when it is 'very confident.'

    Second, that it is extremely predictive: using these numbers to predict any given possession is by far the most accurate of any single system, as has been shown by its very low standard errors. Next, in terms of predictive accuracy, would be statistical plus minuses and non-regularized adjusted plus-minuses...next would be something that is shown to have decent equal predictive value like Win Shares per 48 or even PER.

    A theory's ability to explain the past (i.e. Points Per Game, or, Games Won) is NOT the best explainer of 'true ability.' My philosophy thesis briefly touches on the subject, so here's a primer:

    http://en.wikipedia.org/wiki/Predictive_power

    I'm not saying this to be condescending, rather to just throw out there that explaining the past is a good guess, but predicting the future is a much, much better guess.

  15. Nathan Walker Says:

    (when I say "no other statistic can give us" I mean to say "that few other statistics can give us)

  16. huevonkiller Says:

    http://www.basketball-reference.com/blog/?page_id=9221

    That isn't perfect but appears far more reasonable. I don't rely on one metric but I prefer this one much more.

  17. Matt, Colombia Says:

    How is extending or ending a possession not important? That's what rebounding does for a team.

  18. ElGee Says:

    #12 - Good point. I have data on every team, just less than 5 games on those weaker clubs who are rarely on TV.