Monthly Archives: July 2008

Ron Artest Isn’t Insane, He’s Just Brave!

You see, it takes a real man to go into the stands are start punching some douchebag that threw a coke at you. Oh, and if you disagree, you’re obviously a racist.

“Now, some athletes might shoot up, stand and start looking for the culprit, not really wanting any action. But that’s not because they’re thinking, ‘Oh I gotta be cool here,’ if anything they’re scared of getting their asses kicked (think about how many NBA fights you’ve seen and think about how many of the players involved have given the impression they could actually defend themselves).

Artest, though, is not that scared guy. Any person secure in knowing they can confront that fan’s action with a reciprocal act in kind – will do so.

Artest is that guy.”

(Sports on My Mind: Ron-Ron Comes Strong at Yao and the Rockets)

Cracker.

Ron Artest Has Sick Awesome Contract Provisions

Just when you thought we were finished, Artest pulls us back into the fray! Four Ron posts in just three days? TOO C-C-CRAZY FOR YOU?! C’mon, you know you’re eating it up.

But Ron-Ron’s latest morsel takes the entire situation to a new level of awesome. Behold, CRAZY PILLS hath spoken, and all who are deaf will hear his words and praise his lunacy:

“We’ve still got to make sure there’s still a commitment (from the Rockets),” Artest said. “That’s the main thing, is to make sure there’s still a commitment. When I speak to the powers-that-be of the Houston Rockets’ organization, we’re going to find out how much they really want me there. We’ll find out. I’m still waiting to find out if this is just a trade or if this is like a long-term commitment-type thing. I haven’t spoken to anybody yet. I’m still waiting.”

Yes, you read that correctly — Ron Artest may have just exercised the second known NBA no-trade clause. It’s located in paragraph 2 of section 4.b. of Artest’s contract, under the subtitle that reads: “THIS GUY IS FRICKING INSANE.”

The only person involved in this deal who has less leverage than Artest at this point is named “Future 1st round pick.” Everybody in Sactown did Ron a huge favor here by trading him to a very competitive team where he doesn’t have to do everything for the team to win, and in return he makes a big deal out of a Yao Ming blip. Dude, you’re Ron freaking Artest. Everyone is worried that you might strap a pack of hot dogs and an alarm clock to your chest, pretend it’s a bomb, and hold the Toyota Center hostage for your own amusement. I don’t know if you remember all this, but you punched some fans in the face, wanted to take a season off to make your own rap album, and made fun of your team’s owners’ mother. Frankly, I’d be a bit surprised if Yao wasn’t freaked out.

But the funniest image of the entire Artest-Yao saga: Yao Ming’s giant hands clumsily text-messaging Luis Scola on the world’s tiniest cell phone.

The unfortunate thing about the situation is how overblown it is, considering it’s not even going to matter. Yao’s going to conveniently change his mind in the next few days, they’ll talk about how awesome their chemistry is in a matter of months, and off-court life will be peachy. Well, until that whole hotdog-bomb thing.

The Arbitrarian: Marginal productivity of box score statistics

David Sparks is the contributing statistics writer for Hardwood Paroxysm. His Arbitrarian column runs every Thursday here at HP. For more of his work, you can read his blog. This week’s entry is indeed a true stats column, and is probably the first post on here in a while that doesn’t have the words “snake eggs” in it. David’s our classy guy. This week’s discussion is on his own work with Box Scores. Enjoy.

Thus far, you’ve gotten to read me wax philosophical and discourse on the ideas of others. Today, I’m going to enter the arena, so to speak, and present some of my own work.

Imagine for a moment that you’re interested not only in estimating player value (as in “Most Valuable Player,” not the best player, nor the most talented, nor the most clutch, etc. Value is a direct function of productivity, not ability.), but estimating it well, and doing so for essentially all of professional basketball history. Perhaps you could use (adjusted) plus/minus? Well, no, unfortunately, the play-by-play data necessary to construct plus/minus goes back only a few seasons–no one was keeping track of Bill Russell’s on-court versus off-court team scoring totals.

It would be nice if we had a good way of measuring defense, other than just blocks and steals–maybe it would be possible to pore over video of every game ever played and count the number of “shots changed” and “ball-handlers pressured” for each player… except I’m not sure if video would be available for all 50,000+ games played. Last week, when I asked if there was still room for development in NBA analytics, the overwhelming response was “yes” and the second most overwhelming response was “Defense!” Apparently, it is well-known that box score stats fail to capture some of what makes a player a good defender. Two commonly-cited examples of good defensive players undervalued by traditional statistics are Shane Battier and Bruce Bowen; both are often assigned to guard the opponent’s best perimeter player, but judging from box score statistics alone, it might be hard to see why.

If one is interested in historical comparison, the data options are somewhat limited. Even certain box score stats, like steals, blocks, three-pointers (which are a relatively modern addition to the rulebook), and offensive/defensive rebounds have not been tracked for all of basketball history. However, I contend that for any season prior to roughly 05-06, box score-based metrics are the best option, given that they are essentially the only option. Further, what I propose here goes a long way toward indirectly capturing some “unmeasured” defensive ability, and though it may still be systematically biased against certain lockdown-type defenders, such players are (subjectively) relatively rare.

Defining value through productivity

I will go into much more depth next week on the topic of value, but for now, I will suggest that value is a function of productivity. In “counting stat” terms, basketball productivity can be seen as the accumulation of points, rebounds, steals, personal fouls, and so on, by a player or group of players. However, each of these possible production items is worth something different: a player who contributes 5 fouls in a game is certainly affecting the final score in a different way than a player who contributes 5 points in a game, ceteris paribus. Offensive and defensive rebounds might be differentially productive, as might be missed free throws and missed field goals. It should be fairly obvious to most observers of the game that merely “adding the good and subtracting the bad” is not an appropriate way to estimate productivity (See “Efficiency“), though it may be better than focusing heavily on scoring numbers alone.

That different box score contributions have different values is generally widely accepted; a problem arises in identifying the appropriate/actual set of weightings to use. Is an assist worth one-half of a point? How much more (or less) is an offensive board worth than a defensive rebound? The problem, as I’ve noted before, is that a statistic can be developed to support any conclusions you wish to find. Do you think that the Allen Iverson/Carmelo Anthony duo is the greatest of all time? Weigh scoring heavily relative to other contributions, and assign small (if any) negative values to missed shots. Think Mark Eaton and Dikembe Mutombo’s defensive prowess make them the best ever? Well, when you consider that a blocked shot prevents two points and may also give the blocking team possession, it’s really worth three times the value of a point–it all adds up. My point is that, intentionally or not, biases may easily slip into our analysis. This is why it is important to make public any metric-determining methodology, and subject it to review and criticism.

At any rate, I plan to construct a productivity metric based on a linear-weighting system not too dissimilar from that of Berri and Hollinger, although it differs in the exact weights, and makes fewer “adjustments.” Such linear systems are often criticized, but as I have outlined above, they are one of only a few options open to those with an interest in assessing the players of the past. Further, my value metric (as opposed to my productivity metric, if you’re still with me… there is a difference) incorporates more than just the linear-weighting system, as you will see next week. The key contribution I’m making today is to put forward what I believe to be highly significant, verisimilar linear regression results that help us find “true” weightings.

A data problem

I will not bore you with the details, but this is an endeavor I have attempted many times. Regression analysis allows us, in one interpretation, to estimate the marginal value (in terms of a dependent variable) of an additional unit of an independent variable, on average. For example, a model estimating baseball production might find that for every additional home run hit by a team, their runs scored total increases by 1.44. In baseball, regressing things like singles, doubles, triples, home runs, steals, ground-into-double plays, walks, etc. on runs scored works like a charm (maybe I’ll post analysis this if it’s a very slow news day, but I imagine the baseball metricians have already covered it).

In basketball, at the season level, such is not the case. Regressing box score stats on wins doesn’t really seem to work (by which I mean coefficients which “should be” positive come out negative, for example), nor does regressing on average point differential, points scored, points against, and so on. One option is to do as Dr. Berri has done, and develop a somewhat indirect, albeit reasonably convincing, system by which to connect individual player productivity to team success. (See his 1999 paper here.) Another option is to increase the resolution, and use game-level data:

Box score contributions to team scoring margin

Using a sample of tens of thousands of modern NBA game box scores, I set up a regression using the following formula¹:

MARGIN = B1 + ISHOME*B2 + MIN*B3 + UBX*B4 + FTX*B5 + AS*B6 + OR*B7 + DR*B8 + ST*B9 + BK*B10 + OUST*B11 + PF*B12 + OUBX*B13 + OFTX*B14 + OAS*B15 + OOR*B16 + ODR*B17 + OST*B18 + OBK*B19 + OUST*B20 + OPF*B21


Where:

  • MARGIN = Team total points scored less opponent total points scored
  • ISHOME = A dummy variable indicating whether or not the team of interest is playing at home
  • MIN = Duration of the game in minutes
  • UBFGX = Un-blocked missed field goals = team missed field goals less opponent blocks
  • FTX = Missed free throws
  • AS = Assists
  • OR = Offensive rebounds
  • DR = Defensive rebounds
  • ST = steals
  • BK = blocks
  • UST = Un-stolen turnovers = team turnovers less opponent steals
  • PF = Personal fouls
  • The “O” prefix indicates the same variable measured for the team’s opponent

This regression returns the following output:


Residuals:
Min 1Q Median 3Q Max
-21.90690 -3.57014 -0.04017 3.56452 22.23100

Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.124810 1.113502 -1.010 0.3124
mp 0.009060 0.004918 1.842 0.0654 .
ishome 0.070037 0.073806 0.949 0.3427
tubx -1.059533 0.013189 -80.334 <2e-16 ***
tftx -0.606574 0.013822 -43.886 <2e-16 ***
tas 0.346423 0.007267 47.669 <2e-16 ***
tor 1.052038 0.015221 69.117 <2e-16 ***
tdr 0.531251 0.013246 40.107 <2e-16 ***
tst 1.580819 0.012076 130.903 <2e-16 ***
tbk 0.952582 0.016660 57.177 <2e-16 ***
tust -1.462616 0.014012 -104.381 <2e-16 ***
tpf -0.209380 0.009467 -22.116 <2e-16 ***
oubx 1.004537 0.013118 76.578 <2e-16 ***
oftx 0.567970 0.013906 40.843 <2e-16 ***
oas -0.352181 0.007303 -48.223 <2e-16 ***
oor -1.007247 0.015194 -66.294 <2e-16 ***
odr -0.491897 0.013352 -36.840 <2e-16 ***
ost -1.625631 0.011970 -135.807 <2e-16 ***
obk -1.009805 0.016927 -59.657 <2e-16 ***
oust 1.433541 0.013909 103.065 <2e-16 ***
opf 0.240950 0.009476 25.427 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 5.292 on 24689 degrees of freedom
Multiple R-Squared: 0.8492, Adjusted R-squared: 0.849
F-statistic: 6949 on 20 and 24689 DF, p-value: < 2.2e-16

Here are the coefficients, along with standard errors, expressed in graphical form:

Note that the standard errors are all pretty small (essentially invisible), and all of the coefficients are significantly different from zero.

To arrive at the weightings I use for my linear productivity estimator, I averaged the magnitude of the Team and Opponent coefficients for each statistic, resulting in the following weights:


tubx -1.0320351
tftx -0.5872716
tas 0.3493022
tor 1.0296423
tdr 0.5115741
tst 1.6032249
tbk 0.9811934
tust -1.4480786
tpf -0.2251647

The great thing here is that (almost) all of these weights seem to make perfect theoretical/subjective sense: A missed field goal is worse than a missed free throw, since many missed free throws are the first of two attempts and cannot be rebounded, and the shooting team is often in a better position to defend a missed free throw defensive rebound counterattack. Offensive rebounds are worth more than defensive, because though both indicate the capturing of a possession, an offensive rebound puts teams in a better position to score than a defensive rebound, which must be moved up the court and is subject to turnover and likely a more difficult shot attempt. A steal is worth (slightly) more than the typical turnover, because a possession change resulting from a steal probably generally results in an easier shot attempt than a possession change coming from, for example, an inbound from a three-second violation. Personal fouls, though they sometimes result in free throws for the other team (and are thus detrimental), are also often used to prevent an easy two-point scoring opportunity or to disrupt the flow of an offense, and are often employed for strategic purposes with the intent of increasing the fouling team’s score relative to that of their opponent.

The only theoretically problematic coefficient is…

The troublesome assist

I believe the regression results. Given the apparent verisimilitude of each other coefficient, I think that these estimates are reasonably accurate reflections of reality, and that each additional assist adds only 0.348 to the final margin, on average. However (subjectivity alert!), I do not think that an assist fully captures the contribution of the player doing the assisting. Not only are many good passes made on missed field goals, but some credit might be given to players for moving the ball up the court, running the offense, etcetera, above and beyond attribution for the single penultimate act of passing to the player who scores. Thus, since without such an adjustment, point guards are almost entirely absent from the upper echelons of the productivity list, I re-estimate the assists coefficient:

To do so, I regress team and opponent assists alone on final margin. Using the resulting coefficients (1.196574 and -1.188791, respectively), I take an average as done above, to find my operating coefficient: 1.192683.

Thus far, our coefficients allow us to approximate the number of points a player helped to create for his team, the number of points a player prevented his own team from scoring, the number of points a player allowed the other team to score, and the number of points he prevented them from scoring. To this, we add the most direct contribution to winning margin: points scored. Each player is credited with “all” of his points–there is a direct, one-to-one relationship between each additional point scored and final scoring margin. Thus, I give you an elegant linear-weighted box score-based productivity metric, Model-Estimated Value:

MEV = pts – 1.032*fgx – 0.587*ftx + 1.193*as + 1.030*or + 0.512*dr + 1.603*st + 0.981*bk – 1.448*to – 0.225*pf

Note: In past seasons, offensive and defensive rebounds were not recorded separately. Thus, for such years, I replace the OR and DR factors with (total rebounds) * 0.669, which is the weighted average of the value of all rebounds since offensive and defensive boards have been counted as distinct. Also in years past, turnovers, blocks, and steals were not tracked. I feel that it would be inappropriate to impute estimates of such statistics for historical players, and so I am more or less content to allow no penalty for all unrecorded turnovers past, nor give credit for uncounted blocks and steals. The value metric I’ll detail next week should make this a more comfortable accommodation.

Pre-emptive rebuttals to likely criticism

Certainly this metric is not perfect, and there are many criticisms which could be leveled against it. Here, I will try to address some likely concerns, while avoiding straw men.

C: MEV is box score-based, and so fails to adequately capture, among other things, defense, hustle, heart, desire, clutch, etc.

R: I tried to address this to some extent in my preamble above. I would be happier if MEV did a better job of capturing all aspects of the game (especially defense, though the enhancement I detail next week, I feel, helps somewhat), but given data restrictions, I have decided that box-score statistics are an evil necessary to a universally applicable estimator.

C: A steal (rebound, three-pointer, turnover, etc.) in the last seconds of a close contest is worth much more than at another point in time, and is certainly worth more than in a blowout contest.

R: The first clause is highly debatable: a steal made in the middle of the second quarter might obviate the need for any late-game heroics, and all points scored are given equal credit in their accumulation toward the final score. The second clause is similarly misguided: any additional box score stat will contribute just as much to the final scoring margin, on average, in any game.

C: You keep saying “on average,” but there is no “average” blocked shot. Some are rebounded by the shooting team, some are swatted out-of-bounds, others prevent the game-tying shot, etc.

R: I say “on average” because that is what my methods permit me to say. Part of this is a data availability problem. Until the day we have exhaustive categorizations of every single event and its result, for all NBA games past and future, I am content to make do with the average. Further, over the course of many observations, the averages should not systematically bias the estimates in favor of, or against, any single player. Michael Jordan had many “significant” field goals, but he also had many less “significant” ones.

Incidentally, this argument is often proffered by those opposed to statistical approaches in general. It may indeed be true that some nuance is lost when dealing with recorded numerical observations of the game as compared to narrative, subjective observations. However, it is my contention that the gains in objectivity, accuracy, and consistency afforded by a statistical approach vastly outweigh the losses associated with the possibility that Big Shot Rob doesn’t get more credit for his Biggest Shots (in fact, he will get credit next week, to some extent). Further, as I have mentioned before, I do not see qualitative/quantitative approaches as a binary dichotomy.

C: MEV overweights/underweights statistic X, Y, and Z.

R: I have attempted here to be as transparent as possible in detailing exactly how I arrived at my estimates. I think there may exist some room for disagreement on some of the scalars, but I have detailed the reasons that these coefficients are theoretically satisfying, and empirically-derived. I would be willing to consider an argument with a sound theoretical basis and empirical verification (by which I mean, run your own regression), but for now, I am very comfortable with the weights as they stand.

The one exception is the value credited to an assist, which I may have under-justified. I do feel like (subjectivity alert again!) 1.192 is not an unreasonable amount of credit, falling as it does between the value of an offensive rebound, block, or missed field goal, and the value of a made two-pointer, turnover, or steal. Also, one would have to feel bad for all those point guards who spend all their time trying to pass instead of shooting, and hardly get any credit for it. Please, think of the point guards.

C: MEV should, but does not, account for pace, playing time, strength of opponent, and the quality of one’s teammates.

R: You are right that it does not, but next week I will deliver a pace-agnostic value metric. Further, I am interested in measuring productivity and value, not quality, ability, or technique (all of which are much harder to measure). Productivity per unit time will be addressed next week, but corrections for other players and teams, or positions played, have nothing to do with production. If the player scores a point, it matters not where he is, how big he is, or who else is on the court, it still adds +1 to the final margin. In the playoffs, when the stakes are high, and There Can Be Only One, a missed shot is still going to set your team back about 1.018 points. I may, at a future date, look into estimating quality or talent, but for now, I’ll leave that to my more subjective brethren.

C: Team-level MEV does not correlate well with team wins, and even if it does, that’s only because points are included.

Though MEV does correlate positively and significantly with team wins, this is not a relevant concern. It is directly derived from game-level team scoring margin, and teams only win games if this margin is positive. Further, next week, I will introduce a value measure which incorporates MEV and, at the team level, correlates perfectly with team wins.

The most productive

For those of you who have stayed with me, here’s the payoff. Using MEV, as derived above, we can estimate the productivity of every player who has ever played professional basketball. Here is a table of every player (each team played for) for the 2007-08 season, sorted by a commonly-seen value measure, points per game:

Now, click on the “MEV/G” tab at the bottom, to see the second sheet, which ranks each player by their MEV per game. The list changes fairly substantially. King James, who has a pretty well-rounded game, is still near the top. But Bryant and Iverson drop a spot or two, as do Wade and Anthony. Where does Kevin Martin go? Michael Redd? Richard Jefferson? Corey Maggette? Kevin Durant??? On the other side of the coin, here comes Chris Paul, Dwight Howard, Kevin Garnett and Deron Williams, to the top of the productivity rankings. Click on the third tab, “Value Added,” to see each player’s MEV less points scored, per game. This is an estimate of the non-scoring ways in which each individual helps his team and hurts the other team. Pass-first point guards, defensive-minded bangers, and well-rounded contributors rise to the top. Chuckers (see: Ben Gordon), often characterized by flashy scoring numbers, sink to the bottom. These players still contribute positively, through their ability to score, but their positive value is diminished by the number of shots they miss, turnovers they give up, and the other things they fail to do to help their team improve that final margin.

What if we expand our analysis to the careers of the NBA’s all-time greats? Below is a set of three tables, mirroring those above, except that it covers the duration of 500 of the NBA’s most productive playing careers, according to MEV.

Jordan’s and Chamberlain’s greatness is still validated by MEV; both players contributed through much more than just scoring. Other NBA legends, such as Bill Russell, Magic Johnson, and Oscar Robinson, however, are inadequately captured by their PPG numbers. Again, at the bottom of the Value Added barrel, we see some famous score-first players.

Conclusion

I hope you have found this loquacious discourse both interesting and convincing. I have attempted to develop a theoretical grounding for the appraisal of player value, and used empirical data to estimate a set of scalars with a high degree of face validity. I believe that much of the justification for the accuracy of this metric can be found in its application to actual players. Many individuals commonly known to contribute above and beyond their scoring ability are identified as such by MEV, while those whose points come at a cost are likewise singled out. It is my impression that this productivity estimator finds a happy medium, at which theory meets regression output; scorers are punished for missing, not for just shooting; and credit and blame are meted out fairly.

Please come back next week, when I will go into similarly lengthy detail about value estimates!

¹ This analysis is somewhat similar to that performed by Dan Rosenbaum in estimating statistical plus/minus. I encountered his work after estimating my own regression, and tend to prefer my variable choices and results, but in the interest of openness, I wanted to reference this prior work.

Oh, It’s Already Gold. Gooey, Snake Eggy Gold.

Ron Artest is on his way to the Lonestar State. Next stop, Houston! This is Plano. But hey.

Sam Amick, you’re our hero of the day.

Sure, we could focus on the possibility of Artest sabotaging this deal after Yao got all uppity, and believe me, if Artest gets stranded in Sacramento for what I can only imagine will be the most uncomfortable situation in NBA history, but really, that will come on its own terms.

No, what we’d like to talk about right now is this little beautiful segment of Crazy Pills’ ramblings from his conversation with the delightful Mr. Amick (who also frequents the Cheesecake Factory in Vegas it turns out. The plot thickens.)…

“My first few years weren’t as good as my last few years and my last seven years have been really consistent, so if they want me I’m gone and even if they don’t want me, I still love Tracy McGrady.”

Besides the fact that last year wasn’t as good as some of his previous ones, and that the Malice was in the last seven years, there’s still the amazing stream of consciousness here. Note how the thoughts don’t follow any linear path, but instead seem to flow like a beautiful river through a city of ruin.

What’s next, you ask?

“This is Tracy and Yao’s team, you know. I’m not going to take it personal. I understand what Yao said, but I’m still ghetto. That’s not going to change. I’m never going to change my culture. Yao has played with a lot of black players, but I don’t think he’s ever played with a black player that really represents his culture as much as I represent my culture.”

So you pretty much are taking it personal, aren’t you Crazy Pills? Furthermore, Yao didn’t mention anything about you being ghetto. You running into the fans and assaulting the guy didn’t have anything to do with you being ghetto. It had a lot to do with you being completely batsh*t insane. Which is why we love you. Don’t sell yourself short. Also, after that last sentence, the NAACP just set itself on fire. I think we know who Obama’s VP will be!

Obama/Arest 08: “We’re still ghetto.”

I also love how even in print, you can see Amick essentially cocking his head and asking “Wait… what?” And that’s before…

“He probably reads all the headlines and doesn’t understand. He automatically believes all the propaganda. He probably should’ve called me first. But at the same time, it’s Yao Ming’s team. If he tells me to jump off the building, I’ll jump off the building.”

Come on, Yao. You can do it. Nothing tall. Just, like, a shack or something. We’ll put a trampoline under him. Come on. You know you want to know, Yao. You know.

But my favorite?

“Once Yao Ming gets to know me, he’ll understand what I’m about. Sometimes it’s hard to get to know Ron Artest because I’m so down to earth to a fault.”

That’s exactly what I thin of when I think of Ron Artest. “Down to earth to a fault.”

God Bless you, Sam Amick. You’ve brought a very special dose of Crazy Pills into our lives.

And Ron, we can’t wait for your arrival in Texas. Can’t wait. After all, Texas is the ghetto-ist of the states.

Stress Fracture Or Dislocated Kneecap?

There’s quite the great debate of our time being waged over at frequent HP commenter Khandor’s Sports Blog.

Would you take Andrew Bynum or Yao Ming?

Now, if you want to get into longterm franchise flexibility, salary cap management, and upside, of course Bynum’s your guy. But as I’ve said before, I’m not entirely sold on the Laker rah-rah wagon of “Bynum’s going to come back 100% AND THEN we’re going to kill everybody because we rule AND THEN we’re going to beat the Hornets by 40 and sweep them AND THEN we’re going to beat those stupid lucky Celtics by 100 AND THEN we’ll be the best team EVARRRRRR” wagon. I tend to think a guy that had 35 good games needs a little more evaluation, especially coming off of a significant knee injury that kept him out much, much longer than it was originally expected to before we start calling him the next Kareem Abdul Jabbar. But hey, I’m crazy pills like that.

Anyway, hop on over there and join the fray. So far it looks like we’ve established from the commenters that Chinese people are soft, that Bynum is obviously way better than the multiple time All-Star who’s widely considered one of, if not the best center in the game, and that a stress fracture in the foot that’s actually healed on its expected schedule is way worse than a dislocated kneecap. Good times. Flame on, brothers and sisters!

Stuck In A Moment: How The Los Angeles Clippers Take One Step Forward, Then Immediately Collapse Into A Ball Of Suck Again

I pull for the Clippers.

I mean that in every way. I’m an underdog guy. I can admit that, as passe as it may be. So the bastard child team of Los Angeles holds a special place in my heart. The 2006 Western Conference Semifinals between the Phoenix Suns and the Los Angeles Clippers will always hold a very dear place in my heart. High scoring, fun, energetic. Watching Brand having his coming out party was startling, even if it did only last for that precious few weeks. Tim Thomas was a damn hero in that series, for God’s sake.

And even when Brand got hurt and they fell apart last year, worse than they had the season before, I still found them fascinating. Al Thornton was the guy when I looked at the first round draft picks, I thought “Why is no one talking about this guy?” When he turned into an offensive albatross, I was exhilirated. The Clippers weren’t that bad last year. Mediocre? Sure. But not bad.

So I headed into the 2008 offseason with a lot of hope for this club. The seventh pick in the draft. Cap space if they let Maggette go. The opportunity to lock up Brand. The rising young scorer guard forward. These guys could make a run.

Then, the Clippers’ patented disaster two-step began.

They entered draft night needing help at guard. Plain and simple. Livingston was enough of a question mark for them to renounce him. They’re in a prime position. They can attempt to work something to move up, but they don’t really need to, given Kevin Love’s meteoric rise and the increasing likelihood of Russell Westbrook being taken highly. They can bring in a capable combo guard with an abrasion of offensive skills, terrific handle, and lightning fast speed. His name is Jerryd Bayless.

The Clippers draft “the future fatter Ben Gordon,” Eric Gordon.

Fail.

Having taken the player most likely to be blocked in the NBA draft, they then turned their heads toward free agency.

When Baron Davis opted out, it was a unique opportunity to land the kind of guy that could put a club full of almost-rans and Elton Brand over the top. The Clippers’ management displayed an uncharacteristic amount of vision and leadership in signing Davis to a large but reasonable contract, that also allowed them the room to resign Elton Brand.

Win!

Elton Brand then signs with the Philadelphia 76ers.

Fail.

The Clippers then make an offer to Kelenna Azubuike, who would fill several holes for them and give them a productive bench guy they need.

Win!

The Warriors match the offer sheet.

Fail. Not their fault, but still. Fail.

The Clippers also lose Corey Maggette, but that’s fine as he was expendable. At this point, even with Brand’s crushing departure, the Clippers have enough money to make some moves. They contact Josh Smith, but are unable to seal the deal.

They manage to salvage things, somewhat, though. They send almost nothing to Denver and get Marcus Camby. For all the discussion (destruction) of his game by media and bloggers, it’s still a former defensive player of the year who has veteran leadership and a hard nosed approach to defense.

Win!

They then sign Ricky Davis, a shoot first guard that specializes in shooting first, then shooting, then shooting, and finally getting paid too much money to shoot.

Fail.

I don’t have an NBA team of my own (yet). But if I did, and it was the Clippers? I would throw myself off a very small cliff. Not enough to kill myself, just enough to make it hurt really, really bad. Anything to distract me from the frustration. It’s not like it’s so bad you can’t have hope. They give their fans hope. Then they turn around and take a big crap on that hope. Then they brush it off and show it to you again, and even though it’s still covered in crap, you’re still like, “Oh, hope. I like hope.” Then they set it on fire. Then they rehabilitate it. Repeat. They’re like this Phoenix that never takes flight.

And now I look at that team, and I see a team that could have had this 10 man rotation:

Boom Dizzle, Jerryd Bayless, Al Thornton, Chris Kaman, Elton Brand, Jason Hart, Cuttino Mobley, Tim Thomas, DeAndre Jordan, Nick Fazekas.

And there’s not much difference in that and the projected starting five. But those two players are pretty huge.

I’ll still pull for the Clippers. But last season it was for the guy you know who breaks both of his legs and has to go through physical therapy to walk again.

This time it’s for the guy who keeps making dumb decisions and is then amazed when the consequences are terrible. Yeah, he’s got terrible luck, but you’ve also got to think things through.

Great Exercises in Internet NBA-Related Postings 7.30.08

  • Stern did the right thing and recommended Cuban for the Cubs ownership. Well done. Seattle fans will immediately point out how this is selfish and further reason Stern should be hung from his testicles.
  • Bonzi Wells to Wiz is the talk at Bullets Forever. It definitely sounds like a fit.
  • Another member of the “Oh, Kwame Brown is a devilishly brilliant idea!” crowd. We are not members.
  • Here’s what kills me. I know Wade’s better as a slasher two-guard who doesn’t have to set up the offense. You know Wade’s better as a slasher two-guard who doesn’t have to set up the offense. DWYANE WADE knows he’s better as a slasher two-guard who doesn’t have to set up the offense. So why in the hell is Riley not beating down GMs doors and holding out Marion going “All-Star, primo defender, stat stuffer, still young, expiring contract! GIVE ME YOUR POINT GUARDS!” ?
  • The Jazz are lovable for a lot of reasons. One is their fans, who genuinely believe this team is the bomb. Here are some trade ideas from the frustrated fans who have watches as their team has done nothing in the offseason, outside of matching an offer for a point guard they don’t want who doesn’t want to play there while they have three other great guards on roster. But still, this team is on the verge, baby! The verge! … We’ll be back to this in a second.
  • Fire Richard Justice. FJM, if you’re listening, I’ve got guys like Loren that can do this. Seriously.
  • The Annotated Kwame Brown.
  • Wade, healthy? Not healthy? Healthy? Angry.
  • Blazer Dave is such a realist. While I agree with the premise of “the teams that win–most of them that go to the playoffs and almost every one of them that wins a championship–have one thing in common: on average they have fewer questions about talent, readiness, and suitability than the opponents. “, I don’t necessarily think the Spurs are a member of that group. I think they beneffited from a perfect ability to match up with the teams they faced and a series of fortunate events and decisions which are similar to the breaks that many other championship squads have accomplished. I’m more than willing to say that Tim Duncan is that much better than everyone else. I’m not willing to say the Spurs have been over the last four years.
  • My favorite link section on the web is Posting and Toasting’s Daily Mammal. I have never read it and not laughed.
  • The difficult question of Kyle Lowry continues.
  • Monta Ellis uses the word ‘lovely.’ I don’t know whether that’s lame or awesome.
  • Ziller.
  • This is just good.
  • More Ziller.
  • As a Missouri fan, I heaved a big sigh of relief when the Sixers signed Kareem Rush. Now if I can just get Kleiza out of Denver…
  • I’m the new guy at FanHouse, so I’m not going to comment publically on the disaster that was yesterday. Well, not in non-passive Okafor ways anyway. But this post and the comments are interesting, to say the least.
  • A blog you should be reading on the idiocy that the Bleacher Report can sometimes create.
  • Would you or would you not read a book of these?
  • A rare interview with Skeets. I’m looking forward to this series.
  • I don’t agree with this, but I respect it. I believe you can make a joke about anything. But I also believe that there is an inherent undercurrent to our curent society’s cultural schema that is ripe with homophobia and misogyny. Certain recent events have certainly cast that into light, and it’s clear that this current runs right through our sports culture. It’s not that I don’t see how this could be harmless to someone who’s gay, it’s that I can definitely see how it can be. Just because I’m not offended when someone calls me cracker doesn’t mean it needs to be widely used. To me, it’s not a clear, blaring signal, but one of the more sublte means of expressing an attitude. And it’s an attitude that doesn’t need to be fostered. Plus, I just thought the ads were pretty lame.
  • I’m trying this at my next performance evaluation.
  • Our new writer made Okafor funny. That was pretty much what got him “hired.”
  • Why did no one tell me that Singapore had a freaking basketball team before it was too late?!
  • Lakers fans think they’re tough enough!
  • I don’t agree with everything in this, but I think if you’re a blogger considering applying for credentials, you should definitely read it.

The Return Of Juan Carlos Navarro. For Like, Two Days.

Thank you, Lord! My favorite diminutive, sharply dressed Spanish speedster guard is coming back to America to play two exhibition games with FC Barcelona!

NBATV: You’re on notice. Get them on TV. They play the Lakers in the first game. You like putting them on TV a million times anyway. Make this happen. Give me Navarro. Give me Navarro, now.

A Dark Day for the League

If you follow the NBA, sometimes there are bad days. And sometimes, there are really-really-really bad days. Today…is one of those days.

Today, Shawn Kemp was taken from us…by those damn Europeans. HASN’T SEATTLE ALREADY LOST ENOUGH, YOU CANNOLI-EATING ASS BAGS?!

To the city of Seattle, Shawn Kemp’s 43 illegitimate children, and lovers of all things awesome: I’m sorry.

To the people of Italy: Keep an eye on your wives and daughters.

To Mr. Kemp: Reign o’er l’Italia, big man. Reign o’er ‘em good.

(Heads up from BDL)