In the sky airplanes are otherworldly—in part because we see them from afar, graceful specks arcing across the sky. Jessica Ambats sees them differently: up close, in daring air-to-air pictures shot from the open door of another plane. Earlier this year in an interview with the photography website The SmugMug, Ambats explained her method: She looks for striking backdrops like the Las Vegas strip or the Bay Area, prefers to begin shoots just before sunset, and gets all her camera equipment set before takeoff. Once airborne, she radios precise instructions to the subject planes. The final images are dramatic and capture layers of human ingenuity: We can build a city, build an airplane to fly above it, and then engineer a way to photograph it all.
A power grid Marx could love
Electric cars are considered an important part of a more eco-friendly future, but they come with at least one big problem: If all cars go electric, we won’t be making enough electricity to power them all. A new study out of Sichuan University in China, and reported last month in the MIT Technology Review, explains that the problem is particularly acute because we’re all going to need that electricity at the same time—overnight, so our cars are charged in time for our morning commutes.
The paper runs through different systems for allocating scarce electricity: first-come-first-served, or a round-robin scheme in which each car gets a certain number of charging minutes per hour. These systems wouldn’t guarantee, however, that everyone ends up with enough power in their cars to get to work. A better approach, the researchers contend, is to use feedback from cars and allocate power based on how much juice you currently have in your battery, how long your commute is, and when you need to leave for work. It’s a Marxian form of electricity justice: each according to his needs.
It’s a fun solution conceptually, and satisfyingly efficient in some ways. It’s also, of course, completely antithetical to American car culture, where the ability to “get in your car and go” is an important part of how we think about personal freedom.
Is this the best NBA stat yet?
The world of sports is full of new statistics, each claiming to be a better, smarter way to judge a player’s value: In baseball alone, sports wonks now think about not just RBIs but WHIP, VORP, and EqA, just to name a few.
In a very fluid sport like basketball, value can be a little trickier to measure once you get past points and rebounds. A team of Harvard statisticians has recently devised a new way of getting at what they believe is the true on-court value of a professional basketball player—using a kind of information that only recently became available.
Their stat, called Expected Possession Value, or EPV, aims to measure how each small decision a basketball player makes affects his team’s likelihood of scoring on that possession. It was presented last weekend at the MIT Sloan Sports Analytics Conference and has been getting attention on big sports websites like Deadspin and Grantland. The secret is cameras: During the 2012-2013 season, the NBA installed a system of motion-tracking cameras called SportVU in 13 arenas that recorded the position of the ball and all 10 players on the court 25 times per second. The result was a whole new kind of data about the game.
The cameras let the Harvard statisticians consider the different options available to a player when he had the ball, and then evaluate which players were best at choosing the option that maximized their teams’ chances of scoring. Each decision raises or lowers the “expected value” of the possession—the likelihood it will lead to points. When you take the average of all the decisions a player makes, you get a seasonlong statistic the researchers call EPV-Added (or EPVA) that can be used to compare players.
Of course, any statistic has to pass the reality test—how closely does a player’s EPVA correspond to his value to a team?—and here, EPV has some work to do.
The researchers ranked the 10 best and worst NBA players by EPVA for the 2012-2013 season. (There are no Celtics on the list because Boston is one of a small number of teams that doesn’t release its SportVU data to researchers.) Number one was Los Angeles Clippers All-Star guard Chris Paul, a choice that definitely passes the sniff test. The player with the second worst EPV, however, was more questionable: center Kevin Love of the Minnesota Timberwolves, who’s a leading contender to win the MVP award this year.
I mentioned to the researchers that the Kevin Love ranking seemed off. They noted his wrist injury last year, but also admitted that the statistic tends to be biased against “high-usage” players—generally stars—who log a lot of minutes and find themselves in a wide range of situations throughout the game, not all of which are optimally suited to their abilities. Role players who come into games in specific situations that fit their skills tend to rate better. “It’s difficult to separate the quality of a player’s decision-making from the actual set of situations in which a player has to make a decision,” researcher Alex D’Amour wrote to me. “That’s the real weakness of constructing an all-in-one metric for ranking all players.”