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Dan Rosenbaum
Joined: 03 Jan 2005
Posts: 541
Location: Greensboro, North Carolina
PostPosted: Wed Aug 10, 2005 2:10 pm Post subject: Predictors of Adjusted Offensive and Defensive +/- Ratings Reply with quote
(This was inspired by the thread started by Nikos, but once this post got really long, I figured it probably made sense to start a new thread.)
Below I have included regression results relating my adjusted offensive and defensive plus/minus rating to various box score statistics. These are not quite the series of regressions I used to produce my statistical plus/minus ratings, but I think these should be useful in talking about how box score statistics related these offensive and defensive adjusted plus/minus ratings.
Here are some important points. The way you should read the coefficients is the following. In the offenive regression, the offensive adjusted plus/minus rating increases by 0.70 points per 40 minutes with every one point increase in points per 40 minutes, holding all of the other variables (including true shot attempts) constant.
1. The offensive regression has a much higher R-squared than the defensive regression, which confirms the expectation that our box score statistics do a better job explaining offensive effectiveness.
2. There is slightly more variation in offensive ratings than defensive ratings.
3. The results suggest that holding the other variables constant, a player with better than a 37% true shooting percentage tends to increase offensive efficiency. My interpretation is that the reason this is not higher is that players who can create shots are valuable, i.e. that most players will see their true shooting percentage fall as their true shot attempts increase.
4. Interestingly, even after accounting for points scored, players with more three point attempts tend to have higher offensive adjusted plus/minus ratings. This suggests that in addition to the points they score, the ability of three point shooters to spread the floor is very important for offenses. Also, note that more three point attempts is not associated with worse defense. It does not appear that the long rebounds from missed three pointers is typically leading to easy transition points.
5. Players who go to the line more, holding the other variables constant, tend to be more effective on offense and defense. In fact, the effect is larger on defense.
6. As expected, offensive rebounds predict offensive effectiveness and defensive rebounds predict defensive effectiveness. Note, however, that the offensive rebounds appear to be more important.
7. Holding the other variables constant, players who turn the ball over tend to be not only less effective offensive players, but also less effective defenders.
8. Holding the other variables constant, steals are almost as important a predictor of offensive effectiveness as they are of defensive effectiveness. Part of this may be that steals often generate high percentage scoring opportunities for teammates, but I wonder if part of this isn't that players who get steals tend to do a better job of spacing and collecting loose balls on the offensive end. This may help explain why steals may not be a good predictor of team success, but are important at the individual level. Players who steal the ball a lot may do a better job helping their teammates avoid turnovers and bad shots.
9. For the whole sample there is not a strong relationship between assists and defensive effectiveness. But when I limit the sample to big men, I find that better assisters tend to better defensive players, holding the other variables constant.
10. Holding the other variables constant, blocks predict defensive effectivenss, but not offensive effectiveness.
11. Holding the other variables constant, players with more personal fouls tend to be more effective defenders, with little effect on offensive effectiveness.
12. Holding the other variables constant, players who play more minutes per game tend to be more effective on offense and defense. This is pretty strong evidence that coaches do observe contributions that players make that are not picked up in box score statistics.
Code:
The SAS System 14:08 Wednesday, August 10, 2005 63
Model: MODEL1
Dependent Variable: OFF1
Analysis of Variance
Sum of Mean
Source DF Squares Square F Value Prob>F
Model 12 9291008.6501 774250.72084 118.118 0.0001
Error 1081 7085843.2932 6554.8966634
C Total 1093 16376851.943
Root MSE 80.96232 R-square 0.5673
Dep Mean -0.42353 Adj R-sq 0.5625
C.V. -19115.86189
Parameter Estimates
Parameter Standard T for H0:
Variable DF Estimate Error Parameter=0 Prob > |T|
INTERCEP 1 -7.056284 0.61411305 -11.490 0.0001
PTS 1 0.702730 0.06387650 11.001 0.0001
TSA 1 -0.525243 0.06276998 -8.368 0.0001
FTA 1 0.083834 0.06323568 1.326 0.1852
TA 1 0.327152 0.04249266 7.699 0.0001
AS 1 0.640857 0.04863086 13.178 0.0001
OR 1 0.733202 0.10084425 7.271 0.0001
DR 1 -0.138614 0.05560930 -2.493 0.0128
TO 1 -1.042591 0.14327755 -7.277 0.0001
ST 1 0.713849 0.14956205 4.773 0.0001
BK 1 -0.111075 0.10316250 -1.077 0.2819
PF 1 -0.093128 0.08545434 -1.090 0.2760
MPG 1 0.043603 0.01161761 3.753 0.0002
The SAS System 14:08 Wednesday, August 10, 2005 64
Model: MODEL2
Dependent Variable: DEF1
Analysis of Variance
Sum of Mean
Source DF Squares Square F Value Prob>F
Model 12 4432015.5876 369334.6323 48.579 0.0001
Error 1081 8218599.2007 7602.7744687
C Total 1093 12650614.788
Root MSE 87.19389 R-square 0.3503
Dep Mean 0.30028 Adj R-sq 0.3431
C.V. 29037.83409
Parameter Estimates
Parameter Standard T for H0:
Variable DF Estimate Error Parameter=0 Prob > |T|
INTERCEP 1 -3.683703 0.66138060 -5.570 0.0001
PTS 1 -0.067574 0.06879300 -0.982 0.3262
TSA 1 -0.105195 0.06760132 -1.556 0.1200
FTA 1 0.179179 0.06810286 2.631 0.0086
TA 1 0.007954 0.04576327 0.174 0.8620
AS 1 0.035210 0.05237392 0.672 0.5015
OR 1 -0.126936 0.10860612 -1.169 0.2428
DR 1 0.393748 0.05988948 6.575 0.0001
TO 1 -0.382290 0.15430545 -2.477 0.0134
ST 1 1.080512 0.16107366 6.708 0.0001
BK 1 1.014717 0.11110280 9.133 0.0001
PF 1 0.309126 0.09203166 3.359 0.0008
MPG 1 0.057194 0.01251181 4.571 0.0001
Dependent variable first regression - adjusted offensive plus/minus rating
Dependent variable second regression - adjusted defensive plus/minus rating
PTS - points per 40 minutes
TSA - true shooting attempts per 40 minutes
FTA - free throw attempts per 40 minutes
TA - three point attempts per 40 minutes
AS - assists per 40 minutes
OR - offensive rebounds per 40 minutes
DR - defensive rebounds per 40 minutes
ST - steals per 40 minutes
BK - blocks per 40 minutes
PF - personal fouls per 40 minutes
MPG - minutes per game
All variables are pace adjusted and the regressions are using data from 2002-03 through 2004-05 and are weighted by minutes played.
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kjb
Joined: 03 Jan 2005
Posts: 865
Location: Washington, DC
PostPosted: Wed Aug 10, 2005 3:01 pm Post subject: Reply with quote
I think this is GREAT stuff. I'll let others comment on the math, but I love stuff like:
Quote:
7. Holding the other variables constant, players who turn the ball over tend to be not only less effective offensive players, but also less effective defenders.
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Eli W
Joined: 01 Feb 2005
Posts: 402
PostPosted: Wed Aug 10, 2005 3:06 pm Post subject: Reply with quote
Sorry if this is obvious, but what's the formula for true shooting attempts? I haven't seen that terminology.
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Dan Rosenbaum
Joined: 03 Jan 2005
Posts: 541
Location: Greensboro, North Carolina
PostPosted: Wed Aug 10, 2005 3:12 pm Post subject: Reply with quote
John Quincy wrote:
Sorry if this is obvious, but what's the formula for true shooting attempts? I haven't seen that terminology.
Good question. It is just the denominator of true shooting percentage.
True shooting attempts = FGA + 0.44*FTA
True shooting percentage = (PTS/2)/(FGA + 0.44*FTA)
Sometimes I think I also refer to "true shooting attempts" as "true shot attempts."
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olcoach43
Joined: 10 Aug 2005
Posts: 28
Location: Indianapolis, Indiana
PostPosted: Wed Aug 10, 2005 3:45 pm Post subject: Defensive predictor #7 Reply with quote
Dan I assume that these ratings are a function of what happens to the team when a given player is on floor? (If not can you clarify?)
If so, the defensive performance is most likely negative when a poor ballhandler (turnovers) is on the floor, because of two perfectly logical factors:
1. There may well be a points off of turnovers factor, depending upon where and what type of turnover occurs. Eg, a quick basket
2. Even if the turnovers do not lead directly to quick baskets, points per possession will suffer while turnovers are occuring, and chemistry and defensive effort will break down within the team concept.
On the bench we would be focused upon breaking a negative momentum and assistants would be hollering for me to get his a** out of there! Smile
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Eli W
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Posts: 402
PostPosted: Wed Aug 10, 2005 4:03 pm Post subject: Reply with quote
Dan, this stuff is great. I've already plugged in the coefficients to an Excel formula and gone to work. One initial thing I noticed was how poorly Ben Gordon came out defensively. I didn't use any pace adjustments, but I have him ranking third worst in the league for 04-05 (behind Troy Hudson and DeShawn Stevenson). You have Hudson and Stevenson both ranked in the 0 percentile in defensive statistical plus/minus in your 82games article, but Gordon is listed as in the 52nd percentile. Is this big difference for Gordon due to the fact that you used slightly different regressions (or due to pace adjustments)? Or did I err in my calculations?
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olcoach43
Joined: 10 Aug 2005
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Location: Indianapolis, Indiana
PostPosted: Wed Aug 10, 2005 4:17 pm Post subject: Ben Gordon Reply with quote
John,
I am not capable of doing the statistical work you just described. However, I am heartened by your findings. My work shows Gordon to be one of the worst "off the ball" players in the NBA, ranked 5th from the bottom of all 500+ players.
His A/TO ratio is .88 and he contributes virtually nothing in any other categories. He is a known poor defender, so I have been
wondering about this issue as well.
Last edited by olcoach43 on Wed Aug 10, 2005 4:42 pm; edited 1 time in total
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jkubatko
Joined: 05 Jan 2005
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Location: Columbus, OH
PostPosted: Wed Aug 10, 2005 4:31 pm Post subject: Reply with quote
Dan, did you look into the problem of multicollinearity at all? If you are just interested in obtaining predictions, then multicollinearity is not a big deal. But if your goal is to understand how each predictor influences the response, then multicollinearity is a *big* problem. Based on your initial post it seems like you are interested in the latter.
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Dan Rosenbaum
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Location: Greensboro, North Carolina
PostPosted: Wed Aug 10, 2005 6:28 pm Post subject: Reply with quote
John Quincy wrote:
Dan, this stuff is great. I've already plugged in the coefficients to an Excel formula and gone to work. One initial thing I noticed was how poorly Ben Gordon came out defensively. I didn't use any pace adjustments, but I have him ranking third worst in the league for 04-05 (behind Troy Hudson and DeShawn Stevenson). You have Hudson and Stevenson both ranked in the 0 percentile in defensive statistical plus/minus in your 82games article, but Gordon is listed as in the 52nd percentile. Is this big difference for Gordon due to the fact that you used slightly different regressions (or due to pace adjustments)? Or did I err in my calculations?
It won't give the same results for a few different reasons.
1. Pace adjustments - although for the Bulls I cannot imagine this matters much.
2. Different coefficients - First, I use a slightly different specification of variables, which probably makes a slight difference. Second, I use the results from several regressions to get the statistical plus/minus ratings. One regression uses the whole sample, but others limit the sample by position or by true shooting attempts. Thus, the coefficients that I use are different than those in the post above.
3. I adjust the statistical defensive plus/minus ratings by team so that they add up to the defensive rating. I do the same with the adjusted plus/minus ratings, but those adjustments are small. But the stats do such a poor job predicting defensive effectiveness, the adjustment is sometimes pretty large, especially for a team like the Bulls in 2004-05.
4. Remember my ratings are predictions for 2005-06. And remember I find that rookies improve a lot. Throwing in the improvement due to getting older as well and I bet that adjustment adds a point or two to Gordon's rating.
Another thing to remember is that the percentiles that I give are weighted and by position. Shooting guards tend to have low defensive adjusted plus/minus ratings, so overall Gordon is rated much lower than the 52 percentile with the statistical rating.
But none of this takes away that in 2004-05, Gordon's defensive adjusted plus/minus rating was phenomenal. This is not affected by these adjustments above and it was higher than what I am projecting for 2005-06. So yes, the stats are saying the Gordon is a so-so defender or worse if I don't make the adjustments above, but the Bulls played great defense when he was in the game in 2004-05.
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Dan Rosenbaum
Joined: 03 Jan 2005
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Location: Greensboro, North Carolina
PostPosted: Wed Aug 10, 2005 6:39 pm Post subject: Reply with quote
jkubatko wrote:
Dan, did you look into the problem of multicollinearity at all? If you are just interested in obtaining predictions, then multicollinearity is not a big deal. But if your goal is to understand how each predictor influences the response, then multicollinearity is a *big* problem. Based on your initial post it seems like you are interested in the latter.
In general, I am mostly concerned about prediction with these results, but for the discussion in this thread I am trying to make statements about how each variable is correlated with the adjusted plus/minus ratings, holding the other variables constant.
Multicollinearity, in the classic case, does not bias coefficient estimates. It just results in larger standard errors. But most of the coefficient estimates are fairly precisely estimated, so I do not really have a standard error problem. (The standard errors are probably a bit overstated, because I have not accounted for autocorrelation in the errors of multiple observations of the same player.)
Now it is possible that in cases of severe multicollinearity where the model is misspecified that multicollinearity might bias coefficient estimates. But except for the two rebounding variables, this is probably not a big problem in these regressions. So I disagree that multicollinear is a "big" problem in these regressions.
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jkubatko
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PostPosted: Wed Aug 10, 2005 9:40 pm Post subject: Reply with quote
Dan Rosenbaum wrote:
Players who go to the line more, holding the other variables constant, tend to be more effective on offense and defense. In fact, the effect is larger on defense.
Based on your SAS output, the coefficient for free throw attempts is not statistically signifcantly different from 0. Since true shooting attempts is a linear combination that includes free throw attempts, I'm wondering if the correlation between true shooting attempts and free throw attempts (which is likely to be at least 0.85) is causing this.
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Dan Rosenbaum
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PostPosted: Wed Aug 10, 2005 10:27 pm Post subject: Reply with quote
jkubatko wrote:
Dan Rosenbaum wrote:
Players who go to the line more, holding the other variables constant, tend to be more effective on offense and defense. In fact, the effect is larger on defense.
Based on your SAS output, the coefficient for free throw attempts is not statistically signifcantly different from 0. Since true shooting attempts is a linear combination that includes free throw attempts, I'm wondering if the correlation between true shooting attempts and free throw attempts (which is likely to be at least 0.85) is causing this.
First, I should add, that looking at the FTA coefficient (or the TA coefficient), holding the other variables constant, means that we are holding true shot attempts and points constant. In other words, it is giving us the effect of subsituting free throw attempts for two or three point field goal attempts without total points scored changing.
The correlation is a bit lower than 0.85 at 0.66842 and yes, that contributes to a larger standard error. But a 95% confidence interval between -0.05 and 0.22 seems reasonably precise to me.
The most highly correlated variables are points and true shot attempts, which have a correlation over 0.96. But I am able to separately identify these two variables in the offensive rating equation, but as expected I am not able to identify them in the defensive rating equation. Partially for this reason, I use a little different specification when I compute the statistical ratings.
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jkubatko
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PostPosted: Wed Aug 10, 2005 10:35 pm Post subject: Reply with quote
Dan Rosenbaum wrote:
The correlation is a bit lower than 0.85 at 0.66842 and yes, that contributes to a larger standard error. But a 95% confidence interval between -0.05 and 0.22 seems reasonably precise to me.
Ah, I forgot you were using rates per 40 minutes rather than the raw totals. That explains my overestimate of the correlation coefficient.
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jkubatko
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PostPosted: Wed Aug 10, 2005 10:49 pm Post subject: Reply with quote
Dan, have you thought about using FTA/FGA instead of FTA? I'm just curious how that would influence the results.
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Eli W
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PostPosted: Thu Aug 11, 2005 2:07 pm Post subject: Reply with quote
What are the coefficients for estimating overall adjusted plus/minus? Are they just the sums of the offensive and defensive coefficients?
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Dan Rosenbaum
Joined: 03 Jan 2005
Posts: 541
Location: Greensboro, North Carolina
PostPosted: Fri Aug 12, 2005 12:38 am Post subject: Reply with quote
jkubatko wrote:
Dan, have you thought about using FTA/FGA instead of FTA? I'm just curious how that would influence the results.
Yes, I have wondered what it would mean to add a variable like that in these regressions. It would, kind of, be identifying a player type, although is a guy who shoots half as many free throws and field goals the same player type regardless of whether he shoots 10 FGA per 40 minutes or 20 FGA per 40 minutes. Even if the variable fit the model better, I just am struggling how to interpret what it would mean in that context.
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Dan Rosenbaum
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PostPosted: Fri Aug 12, 2005 12:41 am Post subject: Reply with quote
John Quincy wrote:
What are the coefficients for estimating overall adjusted plus/minus? Are they just the sums of the offensive and defensive coefficients?
The overall adjusted plus/minus rating combines (1) the offensive adjusted plus/minus rating, (2) the offensive statistical plus/minus rating, (3) the defensive adjusted plus/minus rating, and (4) the defensive statistical plus/minus rating.
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Dan Rosenbaum
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PostPosted: Fri Aug 12, 2005 1:12 am Post subject: Reply with quote
I am not sure that anybody will be interested in this, but it appears that Winston and/or Sagarin might be checking in on our board here every once in awhile.
http://mb15.scout.com/fillinoisinsiderf ... 21&stop=40
I really wish one or the both of them would participate on the board. There surely would be ways short of giving away the store where they could benefit from interacting on this board. They are working for a team (the Mavs), but not in an intregral way like Sam Presti of the Spurs for whom it would be too compromising to participate in this forum.
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olcoach43
Joined: 10 Aug 2005
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PostPosted: Fri Aug 12, 2005 6:27 am Post subject: Reply with quote
For those of you on the technical and scientific side of these issues I am curious as to where you think the emphasis should be placed- what is measured and included in your formula, or the methodology? I ask this question here because of your reference to Cuban's guys. Cuban was quoted in an article that he felt that the key to improving upon a system was to measure the right things.
If that is true, I am curious as to whether he, his coaches, or Sagarin/Winston decided on what to put in the original WINVAL?
I found this quote over at the illini board as well, and from the basketball side, it has relevance. I know that Dan might disagree, but I feel it is counter productive to ignore how the people you may want to sell to sees certain things. I am not suggesting that MagicTX is a GM,but I do agree with his assessemnt.
MagicTX86
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(8/11/05 11:55:37 am
No reason to eat crow over such a call, true, but you did make a very definitive prediction on this matter with little basis to back up your position. All indications to date point to Paxson being very high on Duhon's role on the team and that he has just been waiting for Duhon to get an offer to set the market. He will be a Bull next season.
It's an art for GMs to build a team of top flight role players around the team's stars and
Paxson, so far, is showing that he really grasps this. Many GMs clearly do not.
Could it be that there could coexist competing views and systems, since basketball is/may not be like baseball due to its more dynamic nature? What I might want included and measured in a player evaluation system as a coach/GM on the basketball side may be different than what another coach/GM may want.
I think Cuban is onto something in terms of better identifying WHAT we measure. I am confident that the analysis process too often enagages irrelevant facts, data, etc.
I have read and digested from a basketball perspective the highly acclaimed book "blink" by Malcolm Gladwell and he offers great insights into the decision making process.
He refers to a concept called "thin slicing", where the great talents (Wooden, Jackson, Brown, Dean Smith, Knight, etc) are able to quickly discard irrelevant facts and make great decisions.
A classic example of this may be that of Jackson turning to the Triangle Offense and a non conventional handler (MJ) in the face of adversity (playing with the worst Post man in the league). I would call this coaching artistry, and it is a simple response that says, "Why would I want to play within a system that requires point guards and centers, when only mediocre or poor ones are availabale to me"?
I am also curious as to whether a challenge to repeat this process, with Kobe as a stand in for Jordan, is what drives Jackson back and why Kobe just may buy in.
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Eli W
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Posts: 402
PostPosted: Fri Aug 12, 2005 8:44 am Post subject: Reply with quote
Dan Rosenbaum wrote:
John Quincy wrote:
What are the coefficients for estimating overall adjusted plus/minus? Are they just the sums of the offensive and defensive coefficients?
The overall adjusted plus/minus rating combines (1) the offensive adjusted plus/minus rating, (2) the offensive statistical plus/minus rating, (3) the defensive adjusted plus/minus rating, and (4) the defensive statistical plus/minus rating.
Thanks. I guess what I meant to ask was whether the coefficients for overall statistical plus/minus would just be the sums of the coefficients for offensive statistical +/- and defensive statistical +/-.
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Dan Rosenbaum
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PostPosted: Fri Aug 12, 2005 8:51 am Post subject: Reply with quote
John Quincy wrote:
Dan Rosenbaum wrote:
John Quincy wrote:
What are the coefficients for estimating overall adjusted plus/minus? Are they just the sums of the offensive and defensive coefficients?
The overall adjusted plus/minus rating combines (1) the offensive adjusted plus/minus rating, (2) the offensive statistical plus/minus rating, (3) the defensive adjusted plus/minus rating, and (4) the defensive statistical plus/minus rating.
Thanks. I guess what I meant to ask was whether the coefficients for overall statistical plus/minus would just be the sums of the coefficients for offensive statistical +/- and defensive statistical +/-.
In the old version, I did not split things up into offensive and defense. But in this version the statistical plus/minus rating would be equal to the sum of the offensive and defensive statistical plus/minus ratings. (That's a mouthful.)
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Dan Rosenbaum
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PostPosted: Fri Aug 12, 2005 9:09 am Post subject: Reply with quote
olocoach, you indirectly bring up a good point about context. Put a player in a different role and his value may change quite a bit. When I find myself giving advice to basketball people, I find myself talking about roles a lot.
Most players are not asked to dramatically change roles, even if they switch teams. So how effective they were in past roles usually is a good indicator of how effective they will be in future roles. And, of course, in the cases where a player's role changes dramatically, subjective analyses are also going to have difficulty predicting what might happen to a player's effectiveness.
And on Duhon, my system probably rates him higher than almost anyone else. And by all reports, it is Skiles who has pushed for Duhon; Paxson, I think, was leaning towards sending him to Europe last season.
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olcoach43
Joined: 10 Aug 2005
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PostPosted: Fri Aug 12, 2005 9:36 am Post subject: Reply with quote
Dan,
Actually, Duhon is a very highly rated player (34th overall) when measured by our BBIQNET system. (IQ, non-scoring positives, etc). Gordon is one of the lowest in the league due to turnovers and lack of assists, etc)
Skiles asks for two different things from them, and I think ver wisely so. As an old point guard in charge of things, Skiles wants stability at the point. Gordon can not provide that. That is why Duhon started 73 games and Gordon 3. There may be a better option for the Bulls at the point, but the answer does not lie in a choice between Duhon and Gordon. They play two different roles and offer Skiles two different things when it comes to job security. Long run, players like Gordon are a dime a dozen, while young intelligent players like Duhon are actually a rarity in the league. If I were in Skiles shoes, I would have argued for the same thing.
Tim Russell
Former College Coach
russellratings.com
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Mike G
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PostPosted: Fri Aug 12, 2005 9:51 am Post subject: Reply with quote
olcoach43 wrote:
... players like Gordon are a dime a dozen, while young intelligent players like Duhon are actually a rarity...
Holy cow, are you kidding? It looks to me that Ben Gordon is one of the top 30 scorers in the league. And he's a rookie, meaning he should get a lot better.
Overall, I've got him ranked #78 (in something I call eWins-per-minute). These rankings suggest he could easily start and be the top scorer on some NBA team. You must be talking about a very big dime.
Duhon doesn't have stats that make him look too impressive. So without looking, I'm impressed by a system that recognizes his value. The Bulls had a good year, and their coach seems to know something.
Yes, we are neighbors. (And I am less likely to let fellow Hoosiers get away with loose talk.) If you're in my area, look me up.
Last edited by Mike G on Fri Aug 12, 2005 11:31 am; edited 1 time in total
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olcoach43
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PostPosted: Fri Aug 12, 2005 10:10 am Post subject: Reply with quote
Mike,
I didn't mean to light such a big fire on the Gordon comment. Smile
Gordon may well get even better, and meet very high expectations as a top player/scorer. If so it will hinge upon his improving as handler, passer, defender, rebounder and decision maker.
The dime a dozen comment is directed at all the players out there who do not want to do anything but shoot the ball. That may not apply to Gordon...he may want to, but is not yet skilled enough to do so.
Tim Russell
Former College Coach
russellratings.com
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kjb
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PostPosted: Fri Aug 12, 2005 10:57 am Post subject: Reply with quote
I hadn't really looked all that closely at Gordon's season numbers until I read the last couple posts. He's an interesting player. I saw him up close for six games during the playoffs, in which I tracked his (and everyone else's individual defense). Links to the game-by-game defensive box scores are below. I can't seem to find game 6 for some reason.
Gordon does score a lot of points, but he's a turnover machine. He shoots the ball effectively -- in part because of a good percentage from 3pt range. His 4.5 turnovers per 48 minutes were 8th most in the league for everyone with more than 500 minutes. His PSA suggests someone who should have an offensive rating (DeanO's pts produced per 100 possessions) of around the league average, but the turnovers (and lack of assists) gave him an Ortg of 100 vs. a league avg. of 106. His PER comes in right at the league average.
I saw firsthand in the playoffs just how dangerous he could be so I'm not discounting his abilities. I guess I'd sorta figured his numbers would be a little better given his reputation. The bright side is that the turnovers are fixable -- his "Most Similar At Age" is Gilbert Arenas, who cut his turnovers per 48 from 5.3 in 03-04 to 3.5 last season.
The defensive box score links:
http://www.geocities.com/wizardskev/wizbullsgame1.htm
http://www.geocities.com/wizardskev/wizbullsgame2.htm
http://www.geocities.com/wizardskev/wizbullsgame3.htm
http://www.geocities.com/wizardskev/wizbullsgame4.htm
http://www.geocities.com/wizardskev/wizbullsgame5.htm
And, (just to pimp the hell out of myself) the SI.com article I did about the first few games of the series: http://sportsillustrated.cnn.com/2005/b ... 4/defense/
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Mike G
Joined: 14 Jan 2005
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PostPosted: Fri Aug 12, 2005 11:29 am Post subject: Reply with quote
WizardsKev wrote:
... His 4.5 turnovers per 48 minutes were 8th most in the league... an offensive rating ... around the league average, but the turnovers (and lack of assists) gave him an Ortg of 100 vs. a league avg. of 106. His PER comes in right at the league average.
I saw firsthand in the playoffs just how dangerous he could be so I'm not discounting his abilities. I guess I'd sorta figured his numbers would be a little better given his reputation. ..
An average-to-worse player that by firsthand observation and reputation seems to be very good... That, combined with DanVal's take, certainly indicate a statistical quandary.
Is it possible some of these measures aren't truly reflecting Gordon's worth?
Do ORtg and PER consider that his TS% was better than any other perimeter player the Bulls had (excepting the seldom-used Piatkowski)? He should probably have had about .5 fewer TO in his 24 MPG. Is that really enough to consider him an average-or-below offensive producer, given his scoring rate?
I'll take the extra 14 points and 1.3 TO from Gordon, over Duhon's extra 4 assists (per-36 rates). At the same time, I know Skiles is a better coach than I.
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Ben F.
Joined: 07 Mar 2005
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PostPosted: Fri Aug 12, 2005 11:42 am Post subject: Reply with quote
Is it possible to Allen Iverson corollary applies here (that I talked about in my post on Usage vs. Efficiency)?
Gordon's worth might be derived from being able to use a good number of possessions, without his efficiency dropping TOO far (although admittedly it is fairly low). He was 9th in the NBA last year in Usage, for players playing over 500 minutes, and the Bulls did seem like a team that didn't have a bona fide perimeter player that could shoulder a possession load - except for Gordon. Perhaps he allowed the other players to maximize their efficiency by playing at their ideal usage?
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kjb
Joined: 03 Jan 2005
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PostPosted: Fri Aug 12, 2005 12:11 pm Post subject: Reply with quote
Mike G wrote:
An average-to-worse player that by firsthand observation and reputation seems to be very good... That, combined with DanVal's take, certainly indicate a statistical quandary.
Is it possible some of these measures aren't truly reflecting Gordon's worth?
Do ORtg and PER consider that his TS% was better than any other perimeter player the Bulls had (excepting the seldom-used Piatkowski)? He should probably have had about .5 fewer TO in his 24 MPG. Is that really enough to consider him an average-or-below offensive producer, given his scoring rate?
I'll take the extra 14 points and 1.3 TO from Gordon, over Duhon's extra 4 assists (per-36 rates). At the same time, I know Skiles is a better coach than I.
The TS% and eFG measures capture what Gordon does when he gets the shot up. Ortg captures the effect of his shooting as well as the effect of his turnovers. I think that what might explain the discrepancy between reputation and season stats could be that Gordon had some games where he was frigging terrific, and other games where he was awful.
A look at his game log shows him having a few terrible shooting nights, then an eruption followed by bad shooting nights. He appears to have gotten more consistent later in the season.
This may not be the best way to look at this issue, but I'll do it anyway Smile -- I took the game logs for both Gordon and Gilbert Arenas from last season (because Arenas was Gordon's stat comparison at Justin's site). I did a pts per 48 minutes for each player, then had Excel do a Standard Deviation for each player's pts per 48 minutes. Gilbert's was 8.9; Gordon's was 13.0.
Arenas had a pts per 48 for the season of 29.9 -- Gordon 29.6. What this would suggest to me is that Gordon's scoring output was much more volatile than Arenas'. Viewed as a range, the Bulls could expect on most nights that Gordon would score 16-42 pts per 48 minutes while the Wizards could expect Arenas to get them 21-39. (I'm not sure if that's a valid way to look at the numbers -- I'm sure someone better at math can comment.)
I see a similar effect when I look at turnovers, suggesting (to me) that Gordon had a lot of variation in how often he commited turnovers game to game. My guess is that such variance isn't uncommon for rookies.
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Kevin Pelton
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PostPosted: Fri Aug 12, 2005 12:14 pm Post subject: Reply with quote
WizardsKev wrote:
My guess is that such variance isn't uncommon for rookies.
Or bench players. To some extent, the Wizards were forced to stick with Arenas, and his stats probably evened out because of that. The Bulls, on the other hand, might determine Gordon was having an off-night and go with Duhon and Hinrich for more minutes.
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kjb
Joined: 03 Jan 2005
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PostPosted: Fri Aug 12, 2005 12:28 pm Post subject: Reply with quote
admin wrote:
WizardsKev wrote:
My guess is that such variance isn't uncommon for rookies.
Or bench players. To some extent, the Wizards were forced to stick with Arenas, and his stats probably evened out because of that. The Bulls, on the other hand, might determine Gordon was having an off-night and go with Duhon and Hinrich for more minutes.
Good point, which coincides neatly with the next thing I looked -- usage. I ran Hollinger's Usage stat (per 48 minutes instead of per 40) on both Arenas' and Gordon's usage for each game. Here too, there was more volatility in Gordon's usage -- though not nearly as pronounced as the difference in scoring. Gordon's standard deviation on game-by-game per 48 minute usage was 7.2 -- Gilbert's was 5.7.
It's probably coincidental, but this was also virtually the same standard deviations on their minutes per game -- 5.3 for Arenas and 7.1 for Gordon.
One last stat before I do some work I'm getting paid to do -- I checked standard deviation for efg%. Gordon's was .172, Gilbert's .150. Don't know how significant that is, but it's one more piece (to me) that shows greater volatility in Gordon's play.
All of this is a very long way of saying that Gordon had some great games, and some really bad games. Perhaps those fluctuations will begin to even out as he "grows" into the league. In fact, I'd expect them to even out some.
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Mike G
Joined: 14 Jan 2005
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PostPosted: Sat Aug 13, 2005 7:21 am Post subject: Reply with quote
WizardsKev wrote:
The TS% and eFG measures capture what Gordon does when he gets the shot up. Ortg captures the effect of his shooting as well as the effect of his turnovers. I think that what might explain the discrepancy between reputation and season stats could be that Gordon had some games where he was frigging terrific, and other games where he was awful....
Kevin, you've certainly made the case for Gordon's volatility of efficiency. But what I was stabbing at was the comparison of the Bulls' overall offense compared to Gordon's "typical" (if there is such a thing) offense.
With the Wizards, your 3 main guys are also your 3 best scorers. With the Bulls, it's a long drop from scoring specialists Gordon and Curry, down to Hinrich and Harrington. When you consider the Wiz' average score (101-101) vs the Bulls' (94-93), doesn't one consider the value of a scorer relative to the rest of his team?
Curry missed 19 games, mostly late in the year, I think. At that point, Gordon was their only guy capable of scoring in bunches. When he did, the Bulls won; if not, they weren't that much worse off. (I'm guessing here.)
Gordon's modest .526 TS% was actually a lot better than those of Duhon (.471), Deng (.495), Hinrich (.496). How many points offsets 1 turnover in the ORtg formula ?
Hey, I just noticed Gordon's TS% from 3-pt shots was .607. For those other guards, it's .533 .
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kjb
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PostPosted: Sat Aug 13, 2005 11:15 am Post subject: Reply with quote
DeanO could answer questions about the Ortg system better than I could. According to BoP, the rating combines scoring possessions (field goals, assists, free throws) with missed FGs rebounded by the defense, missed FTs rebounded by the defense and turnovers. So, turnovers count as a possession in which the offense didn't score any points.
I'm not sure what the data will show about volume of points and usage. I'm not sure how much Gordon is helping his team by shooting (for example) 0-10 in 16 minutes vs. Toronto (although the Bulls did win that game). Or 6-18 against the Wizards or 5-18 vs. Detroit. Obviously he helped when he went 11-17 against Charlotte. But taking and missing a lot of shots? I'm not so sure. I'd want to look closer -- that's going to take some time going through the Bulls season game by game.
I just looked at the Bulls' team page at Justin's site -- scanning down the Ortg list, Gordon's 100 wasn't a whole lot worse than any of the other regulars. Hinrich had a 104, which isn't all that efficient; Curry had a 103, Deng a 98. Chandler had the best Ortg on the team at 112, but had the team's lowest usg rate -- probably because he gets a lot of offense from offensive rebounding and open dunks. No wonder the Bulls were 26th in offense.
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MDC
Joined: 11 Jun 2005
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PostPosted: Fri Aug 19, 2005 1:52 pm Post subject: Reply with quote
Dan, is it possible to use your data and methods to obtain adjusted +/- ratings for statistics like rebounds, opponent(team)-TOs, etc.? Assuming you had unlimited time and could conduct these types of studies, do you think they would be insightful?
Certain players, like Jared Collins, are said to have a bigger impact than their glory stats indicate because they box out and take charges. I would think that an adjusted +/- rating of things like defensive rebounds and opposing team turnovers (if that's possible), when compared to the rankings of a player's rebounds and steals as measured by traditional means, could tease out the players who contribute more than box scores indicate. An adjusted +/- rating for assists could help give perspective on the question of who is more responsible, the assister or assistee?
Is this feasible? (again, assuming you had infinite time to actually conduct the studies, or interns/TAs Very Happy )
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dlirag
Joined: 30 Dec 2004
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PostPosted: Sat Oct 29, 2005 8:18 pm Post subject: Re: Adjusted Offensive and Defensive +/- Rating Reply with quote
Dan Rosenbaum wrote:
3. The results suggest that holding the other variables constant, a player with better than a 37% true shooting percentage tends to increase offensive efficiency. My interpretation is that the reason this is not higher is that players who can create shots are valuable, i.e. that most players will see their true shooting percentage fall as their true shot attempts increase.
Adding in the defense coefficients, the point where TS% has no projected effect on overall efficiency is between 49% and 50%. Are these calculations right?
-0.525 / (-2 * 0.703) ~ 0.373 TS% [Off efficiency]
(-0.525 + -0.105) / (-2 * (0.703 + -0.0676)) ~ 0.496 TS% [Both off and def efficiency]
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Mark
Joined: 20 Aug 2005
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PostPosted: Sun Oct 30, 2005 12:32 pm Post subject: Reply with quote
On Ben Gordon: In his sixth man, spark plug / other big gun role his main job is to score points. I wonder if his teammates draw confidence from that and give better effort on both sides of the court ("this is our chance to go on a run") including the defensive energy that shows in the team defensive stats more than Gordon's individual defensive rating. Maybe Gordon does deserve a little of the credit for that indirect impact.
In the world of extended stats to be created by this year's 82games even deeper charting you will soon be able to ask and answer (if you get to see the data) almost any statistical question, I think it would be interesting to see +/- stats for time on the court compared back to season average offensive and defensive ratings or maybe even game average ratings to better understand if the level of play was truly above average or just better than the opponent in that timeframe.
This might further help understanding of starter vs starter data compared to sub vs. sub as these adjusted ratings also strive to understand. And give information about whether starter (actual or "true" based on quality and total time played) vs sub is something to seek out- easier to gain advantage that way? or costs you as much in reverse? or try to do it position by position and put more of your best defense against your opponents' best offense positions and try- if possible to do both- to do the opposite for your leading scorers or at least your scorers who are affected by the quality of their defenders the most?)
Perhaps counterpart production stats versus starters and subs would help you make more of the right choices. Specific matchups affect the applicability of any general conclusion and might dictate more time from a better defender to control a star (even if it is at a different position- a better second line of defense lane clogger-shotblocker to help control a talented wing who drives or a point guard that can help try to keep the ball moving to a specific and spot on the court) or a more of an offensive minded one specifically at times to exploit a weak defender.
I also think it could be interesting to see league data on player performance in first 4 minutes of their time on the court by appearance, the next four and the remainder. Does offense get better in the second 4 minute block? That would be worth knowing for substitution patterns. And who shows a history of being able to heat up quick.
Is the defense in the first 4 minutes the best, or is it the second 4 minute block, after they get in the flow and really know from playing what is really happening? Does it fall off a lot in the remaining time on the floor after 8 minutes? Which time block has the best balance, adjusted for all players if that is possible? How do all these numbers and their volatility compare among the players you have to choose from at a position?
Does it change as the game goes on? Is total time on the floor a better thing to track and make decisions by? Do different coaches really have that different "freshness" mix patterns (Hubie Brown style fresh relatively full change full units vs. spreadout incrementalists or is the perception overstated? Is it possible to draw any conclusions about the comparative results of the time management approaches across team quality?)
I also appreciate Dan taking the time to explain his findings in greater detail. That helps ease and increase the understanding and reduce the potential for misunderstanding.