Power in Numbers: San Francisco Magazine, December 2010

What do you do if the fitness club you’re obsessed with is about to go out of business? If you’re Max Levchin, the multimillionaire cofounder of PayPal, you get your similarly fanatical gym buddies to go in with you to buy the club yourselves. Levchin had been working out for about a year at an elite cycling studio in San Francisco, and he felt he just couldn’t live without its particular claim to fame. At the club, now named VeloSF, you can ride while wearing a gas mask, so you can calculate your gas-exchange ratios; then you can get your ear pricked to find out how much lactic acid you’re producing. “These things endlessly feed my obsession for math,” says Levchin.

Indeed, the data appeals to many Bay Area tech geeks, says Ian Charles, another VeloSF co-owner, who heads mergers and acquisitions for digital-media company RMG Networks. “They like having the numbers to tell them if their work out is effective and if they’re doing better this week than last,” he says. As it turns out, fitness isn’t the only aspect of tech folks’ lives that they like to negotiate with math. Below, three geeks reveal the algorithms that help them maximize their time—and their adrenaline.

Faster parking
Most people think that when they’re waiting for a space in a full parking lot, they should tailgate the car in front of them, since that puts them second in line for any spots that open up. But one day, Bob Goodson, founder and CEO of Quid, which collects and markets data on private tech firms, was stuck in a line of cars and calculated his way to the opposite conclusion. The lot had about 120 spaces, each with a one-hour limit. By tailing the car in front, he realized, he would have access to only two new spaces that came open—the one on the left and the one on the right—and 60 minutes divided by those two spaces put the potential wait at half an hour. However, by hanging way back, he would gain access to about 20 more spaces, putting the wait time at three minutes. “I set my stopwatch, and a spot came up at the 2:45 point,” he says. “I thought, ‘Holy crap!’”

A more exciting game
A lifelong Chicago Bears fan, Warren Packard—no relation to the legendary David Packard—came up with a way to rate the excitement level of real-time sports events. His company, Thuuz.com (short for enthusiast), pulls in the digital feeds of games and applies a set of algorithms to the play-by-play to measure the pace of the game, how close it is, and the number of dramatic individual moments. “If it passes a certain threshold,” Packard explains, “we send out an immediate alert to tell people, ‘Hey, this game’s worth watching.’” For this year’s NCAA basketball tournament, for example (games are still viewable online), Thuuz advises that you leave Kentucky–West Virginia alone but tune in to the Sweet Sixteen Tennessee–Ohio State match when the game has five minutes to go.

A quicker commute

Most weekdays, Alan Malloy walks 10 blocks east and 2 blocks south from his apartment in the Tenderloin to his job at HubPages, a social-content site. A typical person uses what Malloy calls “the greedy algorithm,” crossing in whichever direction has the green light. But by using a bit of probability-theory logic, Malloy found that he could shave valuable seconds off his travel time by waiting at the red. Here’s how: As he walks east, he encounters a red light that won’t change for another three seconds, which theoretically means it would be faster to cross to the south now at the brief green, then go east the rest of the way. But Malloy noticed that on a 10-block walk, he’d likely encounter at least one red light that would force him to wait for 10 seconds. Therefore, he opts to wait those three seconds up front and cross to the south later, when the potential wait is longer and the reward is greater. “The goal,” he says, “is to minimize the time spent not walking.”

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