They come by the thousands, armed with laptops and tablets and degrees in math, statistics and engineering.
And they come with dreams. Big, data-driven dreams.
For the uninitiated, the Sloan Sports Analytics Conference is basically their Super Bowl, a two-day opportunity to geek out that has been increasingly flooded with technology and concepts to pitch to the teams and analysts in attendance.
Michael Lewis's Moneyball put sports analytics into the mainstream ages ago, but Sloan is where the results of that obsession now play out on an annual basis, with legions of college students from nearby MIT and Harvard – or even Ryerson and the University of Toronto – all pursuing jobs in the big leagues.
They don't necessarily want to be Billy Beane, the Oakland Athletics GM who became the face of the movement; they'll settle for being his brainy sidekick, who was memorably portrayed by a befuddled Jonah Hill on the big screen a few years ago.
The only problem? The movement has become so complex that, for many in attendance with a big idea or innovation, it's already passing them by.
When the conference opened on Friday, sports website Deadspin declared, "There's less and less low-hanging fruit for guys like Billy Beane, who were early to the notion of, well, simply bothering to look."
When it comes to baseball and basketball, at least, the Beane story seems almost quaint. More than a decade later, Sloan's research paper competition was won on Saturday by two remarkably detailed academic studies on defensive play in the NBA and advanced strike zone analysis in baseball.
Both make use of the advanced tracking technology now available in the two sports, and the $30,000 total for first and second place was split among six eggheads, including a visiting scholar at Harvard (Kirk Goldsberry) and a high-end data-driven company known as Baseball Info Solutions.
The depth this year at Sloan was enough for even analytics-heavy sites like Nate Silver's fivethirtyeight.com to pose questions such as: "Are basketball teams now so saturated with data that it's hard to use them for a competitive advantage?"
More and more, sports analytics are becoming as professionalized as the sports themselves. Enormous companies like SAP, which recently partnered with the NHL to provide analytics on its website, are after the vast sums of money being directed toward Big Data in pro sports and they have resources well beyond the many one- and two-man start-ups on hand.
Someone like Marc Appleby, who uses a unique optical camera tracking setup for hockey with his Ottawa-based company PowerScout, and has one NHL team as his primary client, is in tough in that environment – especially when there are league-level partnerships trying to crowd out the little guys.
"The innovation [at Sloan] is really impressive," Appleby said. "It keeps you honest. … If you blink, things will change, and you have to keep up."
At least on the NHL side, the good news is that hockey remains in a developmental stage. Some of the concepts from basketball – another arena sport with teams moving back and forth from end to end – and soccer – where goalies are a factor and wearable technology is making in-roads – can carry over, and marrying video with data is a popular new frontier.
The key, as it was with Beane, is trying to find inefficiencies: undervalued assets or aspects of play that can be better quantified and used to improve.
That's far easier to do these days in hockey (and tennis, golf and others that are gaining growing representation at Sloan) than the other big three – baseball, basketball and football – simply because this pursuit remains relatively new.
But the competition is growing.
"If I look broadly at where I saw the most growth this year in analytics, hockey was unbelievable," Sloan co-founder Jessica Gelman said.
"Baseball's gone through 10, 11, 12 exploitations of inefficiencies," Toronto Maple Leafs assistant GM Kyle Dubas explained, rattling off a list of stats that began with on-base percentage back in the Moneyball-era. "Hockey, we're at one or two."
The curious thing about Sloan is that what would be the most interesting innovations are typically left untold. What teams are doing that's truly different and pushing the boundaries of analytics is proprietary info, which means many of the panels offer only general hints of what's going on.
Dubas, for example, goes so far as to say his analytics team is working on things that are far from the public domain, but he won't offer a hint as to what exactly those innovations are.
Finding what's next and doing it first, at Sloan or elsewhere, remains paramount.
"You have to," Dubas said. "If you only go up to the line where something's publicly accepted, everyone is going to be at that same line. You have to try to advance it."