Dean Oliver on Quantitative Analysis

Well Bryan, would it change your mind if the half that did “dabble” were among the most successful franchises? Now it doesnt take a genius to realize building around a player like Kobe can lead to a competitive squad, the true value in statistics lay in building the core around that special player or in building a team sans superstar. Take Daryl Morey for example;

The Houston Rockets were able to field a competitive team despite being crippled by the absence of 2 MAX players, think about that, thats like the Lakers losing Kobe and Pau and still going .500. The Rockets were able to accomplish something no other team has ever done due to the fact that they were continuously able to find diamonds in the rough in the draft and free agency in large part because of their statistical markers.
Now this can be accomplished without the use of stats but the fact of the matter is this, if we were to replace all the decisions made in the draft as a result of “intuition” with the selections a computer model projects as the superior prospect, chances are your team will be better off.

I dont know what gives you the impression that stat geeks are “loud” or that they represent a majority movement when the article you just read contradicts that very statement.
I understand Dean O doesnt represent every stat head out there but in my experience we are well aware of where we stand among the masses. All you have to do is visit truehoop to see how often they refer to themselves as outsiders or geeks. Still the movement is happening, you can either get with the program and optimize your decision making process with tons of useful information, or you could be like the Clippers and be left behind.

The interviewer worked but I don’t think Oliver really gave him that much back with any depth or precision. Has he even opened the door for any interns? If not, that would be disappointing.

I like the section on possession based analysis (p3). Overall though, at times he seems almost evasive — not a slam really, maybe just the nature of being a quantitative guy — or maybe coy and protecting his data? Would love to watch a game with him and learn more. Hard to quantify how much the stats reveal the game or conversely, whether the true nature of the game gets obscured by the chess match of coaches in real time. For example, does someone like Phil Jackson has an ace up his sleeve that will appear during the playoffs in something as small as resting a guard a few minutes earlier in the game yet keeping total minutes the same.

Playing and coaching Cal Tech was probably about the same level as a run of the mill high school team.

@Chronz: If by “successful” you mean that half of the teams that “dabble” in analytics in some form or fashion finishes a season .500 or better, does that really equate success? No matter how you slice it, the end game in professional sports is a championship. Fans (people who buy tickets) are only going to accept the notion of, “Our team had a great season” for so long. As of a year ago, only 9 teams have an analytics department: Boston, Cleveland, Dallas, Denver, Houston, New Jersey, Oklahoma City, Portland, and San Antonio. Of those 9, only Boston and San Antonio have won championships and it can be argued that in the case of the Celtics, analytics had almost nothing to do with it. As for the Cavs, they had LeBron James. The real test (and value) of their analytics department will come this season. Will they be like Morey’s Rockets and not have their ship sink totally with their marquee and franchise guy gone? That remains to be seen. And what about the Nets? Analytics didn’t help them. They won 12 games last season. OKC’s analytics department seems to be doing a great job in constructing their team, but even with a great player like Kevin Durant, can they really win a title? And the rest of the other teams are really just middle of the pack. They have great regular seasons, but are no real threat to win a title. Not even the Spurs anymore. I just think that analytics in basketball makes mediocrity acceptable and teams that integrate it into their decision making process will be just that and the teams that rely more on traditional talent evaluation of players and assess value that way will continue to outshine them. The notion that a computer model can build a better team than good, old-fashioned basketball “intuition” is silly, IMO and I ask you, are these computer modeled teams being built to win something tangible — like an NBA Championship trophy — or just a good amount of regular season games?

I agree with you to a certain extent Bryan. I think the real value in quantitative analysis in hoops is not so much in determining who’s good and who’s not. But in determining which groups play well together, and which players would play well in a certain system. For example there are some players in the league that can only be successful in an uptempo system and if you put this in a half court system they would be far less effective. And to an extent you see that with OKC, and houston. All the players on those squads really fit the systems being used there

@Tom: Sometimes, it’s not always about the best fit that gets it done. Even though they won, was Ron Artest really a better “fit” in LA than Trevor Ariza? Sure, it works now, but are the guys surrounding Kevin Durant really championship caliber pieces? Sometimes, you have to go away from what the numbers say that works and put a squad together that you know is going to be capable of winning it all when the time comes. That’s all I’m saying. Sure, certain systems fit certain players better, but if you’re always looking for the “right fit,” your team is not going to be very good. Sometimes, you have to be unconventional if you want to compete for something other than just regular season victories and whether it suits a player or not, these guys are pros. They’ll adjust.

@Chronz: I hate it how the writer of Truehoop calls himself a geek despite not having the remote qualifications or brainpower to be considered one. He just uses the word to indirectly call himself “smart”. At least, the one use of quantitative analysis is to prevent GM’s from handing out bloated contracts largely based on scoring alone.

WOW that totally didnt work out the way I envisioned, Ill just copy my retorts to your claims

On Success:
Yes, like I said from the start. It doesnt take a genius or any sort of intuition to know building around Kobe will lead to success. But to try and say there is only 1 successful franchise per year is nonsensical IMO. Only 1 franchise obtains the ultimate level of success sure, but there are various levels of success. I guess this comes down to how you want to evaluate success

On Consumer Tendencies
Based on? People buy tickets for a variety of reasons, just look at the Clippers. Theyve been turning a profit for decades and it has nothing to do with their success so a blanket statement like this is meaningless.

On the C’s title
Not really, Rondo was a stud by draft measurements and Perks signing screams moneyball tactics

On your system for evaluating success
So let me get this straight, you can credit the success to players but all the blame gos on stats for them losing? Thats pretty poor system man. I based success on whats expected of the team and what they control. For example, if a team drafts a solid prospect late in the draft due to analytics then its made a successful decision ala Ty Lawson. I dont look at raw W-Ls because there are alot of factors that go into that

On OKC Building Plan
I dont know, nor do I care. All I know is that awhile back they were nowhere near where they are now. Thats a SUCCESSFUL TURNAROUND. One that actually only happened because Portland actually went against what the stats and models said to do and went with conventional wisdom of taking big over small when every metric out there said to take Durant

On Draft Models being better indicators of talent vs intuition
They are meant to be an upgrade, whether you win a title or not is dependent on so many external factors that trying to pin them down to a single aspect is laughable, that you find it silly is again irrelevant when you look at the historical results of draft rating models this decade, it is a quantifiable fact that they have done a better job of landing impact talent.

@Chronz: I hate it how the writer of Truehoop calls himself a geek despite not having the remote qualifications or brainpower to be considered one. He just uses the word to indirectly call himself “smart”. At least, the one use of quantitative analysis is to prevent GM’s from handing out bloated contracts largely based on scoring alone.

This may be true but I consider myself a statgeek and at the risk of tooting my own horn and coming off just as egotistical, I hold a certain amount of respect in the blogoshphere/forums because of this openness to statistics, yet compared to the likes Dean, Kevin and Hollinger, Im a nobody.

I dont think you should hate someone taking pride in their work, atleast when they admit their flaws, which Ive seen Henry do.