Editor's note: This post was written by Rafe Bartholomew, author of Pacific Rims: Beermen Ballin' in Flip-Flops and the Philippines' Unlikely Love Affair with Basketball.

One of my close friends studies at MIT's Sloan School of Business, and when he emailed me a few months ago to ask if I'd be interested in attending Sloan's Sports Analytics Conference, I jumped at the opportunity. Bill Simmons coined the name Dorkapalooza to describe the Sloan Conference, and I thought of the event as the time of year when the apostles of Moneyball in all major sports gathered to spread the gospel of quantitative analysis.

As my love for Willie Miller might suggest, I'm more of a basketball aesthete than a results-minded stats guy. I can forgive the missed free throws, two-for-thirteen games, and the fact that nearly every PBA fan accuses him of selling games as long as Willie converts one of his patented quick spins on the left wing to set up a bank shot.


Rafe loves him some Willie Thriller

Still, I've been reading about advanced stats for years and hoped the Sloan Conference would intrigue and beguile me with innovative and counterintuitive basketball metrics. The icing on the cake – also hooked up by my Sloan insider – was that 150 copies of Pacific Rims were being given away in the panelists' gift bags, meaning bigwigs like Mark Cuban, R.C. Buford, Del Harris and many others could potentially be reading about the Ginebra mystique (or my infamous turn as an artista) by the time Jaemark posts this.

The conference opened with a keynote discussion moderated by Malcolm Gladwell, author of bestsellers The Tipping Point and Outliers. The panel sought to apply an idea Gladwell wrote about in Outliers -- that true mastery in any field requires 10,000 hours of dedicated practice -- to the development of professional athletes.

Joining Gladwell on stage were Jeff Van Gundy, Houston Rockets GM and conference organizer Daryl Morey, NFL player Justin Tuck and the bullet-headed Mark Verstegen, who would probably be playing drill sergeants in hokey war films today if he weren't running Athletes' Performance, the personal training firm he founded that provides health, fitness and conditioning consulting to elite athletes like Kevin Garnett.

Gladwell's questions were Gladwellian -- Are players who've logged the 10,000 hours to achieve mastery more valuable than more talented athletes who haven't spent as much time in the gym? Is there such as thing as a "natural" athlete and if so, would you even want him on your team? Why can't NBA players make free throws?" You could almost sense him teasing out anecdotes for an upcoming New Yorker piece.

Van Gundy drew laughs with caustic humor and blunt contempt for NBA players: "Soft, selfish and stupid -- you can be one of those, but you can't be two." Morey admitted that all of his great-character, advanced-stats overachievers in Houston would never make a contender without a star scorer to lead them. And Tuck and Verstegen seemed to recognize that they were sitting on the sidelines of an NBA discussion and chipped in just enough to make their attendance worthwhile.

Nothing lit up the sports blogosphere like the moment when Jeff Van Gundy cracked wise about Tracy MacGrady's poor work ethic; T-Mac defenders rallied behind the lazy-eyed assassin, but fewer bloggers were willing to take up the cudgels for Bonzi Wells, whom Van Gundy called fat.


Jeff Van Gundy and Tracy McGrady did not have the best relationship in Houston

The discussion merely grazed the issue of sports analytics and not one panelist revealed a mind-blowing statistical measure that made the audience look at basketball or American football in a new way. Gladwell's final question -- Who is the most gifted athlete you've seen who didn't make it? -- led to when Morey named Marcus Banks.

Banks was my favorite Summer League player ever. He came out of UNLV in 2003, a 6-foot-1 point guard with amazing quickness and a devastating crossover. Man, was he fun to watch, but whatever he needed to improve on to become a solid NBA player -- a jumper and decision-making would have been good places to start -- never materialized.

And even though his talent was scintillating, Morey said NBA teams had noticed red flags in their pre-draft interviews with Banks. For starters, when asked what job he'd like to have more than any other in the world, Banks replied, "male fashion model."

Revelations like this -- NBA marginalia, glimpses of things that only league insiders know -- were one of the coolest aspects of the conference, and the best of these footnotes came when Golden State owner Joe Lacob, who had considered buying NBA teams several times before purchasing the Warriors last year, acknowledged that David Stern used to call him a "tire kicker." If you're having trouble making sense of the term, think of a customer milling around a used car lot without any intention to buy, just tapping the tires with his toes to check for air.

Maybe it's fitting that a pop-science guru like Gladwell headlined the conference, since throughout the two-day event I don't think I saw a single presentation that tested the limits of my high school math education. Panel after panel – injury analytics, basketball analytics, referee analytics, soccer analytics – followed the same pattern: Experts from all sides of the world of sport climbed the stage to explain how franchises that were open to statistical evaluation gave themselves a competitive advantage over those that remained mired in old school methods of talent evaluation and game-planning. What was never discussed in much detail, however, were advanced stats – which measures work, how to apply them, or even which metrics exist.

One explanation is that teams invest big money to develop analytic tools, and once they find something that works they're loath to reveal a trade secret. But something else was going on. It wasn't just that GMs were protecting their proprietary data. The conference program included as many business-oriented panels like New Sports Owners, Athlete Branding in the New Age, and “Sports Labor Relations” as it did stats panels.

Strolling down the Boston Convention Center hallway, I crossed paths with as many salesmen as statisticians, and I realized that the geeks weren't running “Dorkapalooza.” This was Suitapalooza, a sports business convention and networking opportunity. I'm not exactly complaining here. The business panels were often more illuminating than the stats discussions. But "SSAC" became a misnomer in 2011. The event has grown and so has its scope.

There were a handful of stat geeks lurking around the Convention Center. Most often they could be found in Room 204, far down the hall from the amphitheater-like Room 210, which hosted the marquee panels. The research room was literally pinakadulo – like walking from one end of SM Megamall to the other – and its academic presenters tended to be a tad clumsy behind a podium and outfitted in suits and ties that didn't quite pop with bold colors like their counterparts down the hall.

The implicit message – perhaps unintentional, but noticeable nonetheless – was that A-listers like Malcolm Gladwell, Michael Wilbon, Mark Cuban, and Celtics owner Wyc Grousbeck shouldn't be anywhere near the actual dorks.

I caught a handful of presentations in Room 204. The basketball research tended to confirm things we already knew about the sport – players are more productive in a contract year, overmatched teams should slow the game down and chuck threes. Even Sandy Weil's extremely cool optical tracking research, which uses cameras mounted all around certain NBA arenas to capture and analyze every movement and location of NBA players, anywhere on the court, mostly told us things we already know: tight defense or being farther from the basket lowers shooting percentages.

Of course, Weil's quantitative data allows us to be more specific and say that players shoot 12 percent worse when defenders are within three feet of them, and that's pretty cool. Weil's data also showed that players shoot abnormally well in catch-and-shoot situations, and my intuition tells me this is because they're expecting to shoot before they catch the ball.

In my experience (which is probably too lowly to warrant comparison to NBA basketball), when I'm in a catch-and-shoot position, I think “I have to shoot this ball” or “I'm taking this shot” as soon as I see the pass coming. I don't think about making a better decision. I just shoot it, and that mental priming seems to lead to better results.

Weil's presentation was the hit of the conference for stat geeks, and Rob Mahoney of the New York Times' basketball blog called optical tracking data a "perfect marriage of technology and analytical potential," but the conference's Soccer Analytics panelists urged caution. They've been using optical tracking in the English Premier League and many Champions League stadiums for years, and while the analysts say they've gleaned some fascinating football insights, they also admit that so far the coaches on the pitch only pay attention to one stat derived from the new technology: how much ground players cover over the course of the game.

That makes sense -- running and stamina may be more important in soccer than any other sport. But the panelists explained how quantifying exactly how much players ran backfired -- the athletes caught on and started running needlessly to inflate their mileage stats. One panelist recalled a game where a goalkeeper clocked the most miles by running back and forth in the box whenever the ball was on the other side of the pitch.

None of this is to say that the data is worthless or that the technology should be abandoned. Coaches will learn to accept and implement advanced stats. Analysts will learn which stats are more likely to lead to wins and which are destined for little more than lengthy blog dissections. Mahoney and Weil and the geeks are right. This is a new frontier in basketball analytics, but life on the frontier may be a bit disorganized at first.

One more question rattled around my mind during the conference. How much could PBA teams benefit from the use of advanced stats? A lot, I'm guessing. From what I've seen, most PBA teams spend a good deal of time and effort breaking down video and devising game plans against their opponents. Coaches develop a sense for which directions and spots they want to shade Jay Washington or James Yap toward through conventional scouting, and stats can only improve their observations by telling coaches precisely where those guys shoot poorest from over the course of an entire conference or season.

For teams like Rain or Shine and Alaska, which try to compete for titles without the seemingly infinite budgets of SMC and MVP teams, stats might lead to better personnel decisions and more “Wacky” Trillo deals. My experience with Alaska, however, tells me that the team's front office is like the San Antonio Spurs organization – they've had a coach and a system in place for so long, and they know it so well, that they can pretty reliably identify players who fit into it and place them around the designated stars.

Their basketball minds are crunching the numbers, and maybe they aren't deriving Pi to the 3,000th decimal point, but they're sharp enough to make good decisions. The free-spending teams like San Miguel and TNT probably don't need stats to tell them which players to hire – they pursue the most talented players in the league, no matter what – but maybe analytics would help coaches manage their all-star rosters more effectively.


Teams like Alaska need to outwit richer teams to keep winning championships

The PBA has one huge statistical monkey wrench that the NBA doesn't need to worry about – imports. During import conferences, everyone's stats get out-of-whack. First, a starter has to move to the bench. One of the first guys off the bench is moving a few seats down. Most of the time, an import is going to come in and be his team's main option. Even an all-around guy like Rosell Ellis, who was known as a “non-scoring” import, got as many touches and averaged more points than Willie Miller on the 2007 Alaska squad.

It's hard to evaluate the imports on their own, since they aren't really around the league long enough to put up statistically significant reams of data. They just don't defy analysis, but they skew the stats for all the locals so that comparing Ranidel de Ocampo's numbers from an All-Filipino conference to an import conference are no longer comparing apples to apples. Of course, that's the kind of complexity that hardcore stat geeks love to try to account for in their models, and I think their solutions and results would be fascinating to think about, and hopefully also useful for PBA franchises.

Regardless, I think advanced stats will be coming to the PBA soon. These franchises are as competitive as any others in the world of professional sports (never mind Air21), and they're constantly looking for the slightest edge. Not to mention that quantitative analysis has a lot of buzz in the States, and Manila's hoops elite tend to notice such developments.

Finally, there's a generation of smart, young basketball fans in the Philippines who know the NBA as well as they know the PBA and follow both leagues. A few of those fans are probably stat geeks with the math and science chops to do for PBA teams what Sandy Weil can do for potential NBA clients. It's only a matter of time before some forward-thinking team manager decides to give one of them a chance. (Ed: At least two Pinoy blogs, Patay ang Butiki and Pasa Ball, attempt to write about advanced basketball metrics.)

Then again, this is a league where some coaches still call double-teams and match-up zones “scientific” basketball, so don't start lining up to buy tickets for the Mapua Institute of Technology's first annual Torpepalooza.

Rafe's book Pacific Rims is still available online and at bookstores across the Philippines. Check out his blog at RafeBartholomew.com.