Here's a great analysis from Ben Blatt of the Harvard Sports Analysis Collective. He looked at three well-known sports writers -- Bill Simmons, Rick Reilly and Jason Whitlock -- and performed a lexical analysis to create a statistical representation of their writing styles.

What can you do with that analysis? Well, you can see what descriptive words are most frequently used by each author:

• Simmons: Biggest, Excited, Eventually, Almost, Low
• Whitlock: Spoiled, Several, Allegedly, Particular, Important
• Reilly: Tiny, Large, Very, Nice, Dumbest

Or, perhaps more interestingly, you can attribute unknown works to any of the the authors. On six different papers -- the first and last from the period under consideration, which were left out of the training data -- Ben's model went 6 for 6 in choosing the correct writer. More impressively, there was no doubt - the model was 100% certain of its choices. Ben writes that he was surprised at the accuracy.

This method is more frequently seen in attributing historical works, like Shakespeare or the Federalist Papers. However, Ben's success shows how powerful a statistical analysis can be. There weren't any complex algorithms at work here -- all he did was a (relatively) simple Bayesian analysis. Great and entertaining work.

Apologies for the slow posts... but the NYT explains:

Wall Street trading is often described as a blood sport. But inside the great investment houses, the sport of the moment is, of all things, curling — that oddball of the Olympics that is sort of like shuffleboard on ice.

This slow-poke game, which originated in 16th-century Scotland, has captivated the Type-A world of Wall Street almost by accident. CNBC, whose market chatter is the background music on trading floors, switches to curling from Vancouver shortly after the closing bell.

I thought I was the only one going curling-crazy, but it turns out all of Wall Street has spent the last couple weeks learning a new vocabulary (just call me "Skip") and shouting at the TV. Whether or not everyone else has been honing their skills by playing shuffleboard, I don't know... but my plan to open an NYC curling house/alley/place (?) just got a major boost.

The WSJ asks, "Is It Time to Retire the Football Helmet?" With the debate about football head injuries and CTE swirling, some are wondering if wearing helmets is actually exposing players to greater danger than if their heads were exposed. Though seemingly counter-intuitive, the argument follows well-established moral hazard reasoning that some have perceived in, for example, government bailouts for large financial institutions.

Moral hazard arises when an insured party takes greater risk because they know they are protected. In the NFL, that translates players making and taking more violent hits because wearing a helmet makes them feel invulnerable. The reality, however, is that the helmet protects only from direct trauma to the skull; the brain remains very much at risk.

Taking helmets away would certainly change the sport. Though it's hard to disagree that all things equal, players with helmets will play more aggressively than those without, not everything would stay equal with that rule change. I suspect the game would evolve to resemble rugby - a sport not without its share of head injuries.

For a data-driven perspective on the head injury debate, please see Jer Thorp and Jeff Clark's independent analyses comparing two CTE narratives.

Apologies in advance for the absolutely terrible/fantastic title.

The winner of the 2009 contest for the Best Visual Illusion of 2009 is particularly appropriate tonight as the Yankees strive to hand the Phillies their second championship in as many years. The prize was won by a team that has identified the core difficulty in hitting a curveball: it's not where you think it is.

The illusion arises because the seams on the ball spin sideways when a curveball is thrown. When the ball is seen in the batter's peripheral vision, the brain infers from the sideways motion of the seams that the ball itself is traveling sideways, even if it is not. Conversely, when the ball is seen by the batter's central vision system, the sideways visual cue is ignored, presumably because the image of the ball itself on the retina is more a more convincing indicator of it's position.

Critically, not only does the ball appear to drift when viewed by the peripheral system, but when it transitions from central to peripheral vision it appears to jump from one position to another! So the combined effect is: the ball is physically curving through space AND when it reaches the peripheral vision system it is perceived to jump from one position to another AND while in the peripheral system it appears to drift sideways in addition to its actual curve.

The authors argue that this explains the phenomenon of curveballs "breaking" suddenly. A curveball which hangs - that is, one that doesn't break - likely isn't spinning at the right speed to set off the illusion.

But don't take my word for it: try the illusion out for yourself.

(via Newsweek)

It's an extraordinarily sad state of affairs when you can come to this country at the age of 12 as a refugee, train as a gifted runner in San Diego junior high and high schools, attend UCLA as an incredible four-time All-American award winner, become a naturalized US citizen as you graduate college, compete in the Olympics and win a silver medal for the United States and finally become the first American to win the NYC Marathon since 1982... and still have people insist you're not an American?!

The Times has an article about the Mets Fan's Dilemma: who to root for in this year's World Series?

[T]he misery of this uninspired season has been unexpectedly heightened by the indignity of watching their most despised division rival face off against their despised crosstown rival in the World Series

For me, the question is simple: I've never rooted for the Yankees and I'm not about to start now. On the other hand, I can remember cheering on the Phillies when they were playing Atlanta (though it's funny how that has reversed). For all this talk of division rivalry, the Phillies are hardly the reason the Mets haven't been playing any meaningful baseball lately - the sad truth is that the Mets are their own worst division rival, three years running.

The goal of any automotive film is to convey the pure sensation of driving at speed - and few are as successful as Ferrari's latest promotion for the new 458 Italia, embedded here for your driving pleasure. The disclaimer in the beginning notes that no special effects are used and the implied message is that the cars do all their own stunts. Nonetheless, the film is obviously heavily scripted and post-processed. Not that I mind in the slightest:

Click here to view the embedded video.

(Interestingly, watching in full screen - which you should of course do - removes the vertical letterboxing exhibited in the small player.)

I read this morning about the drama at last night's MTV video awards (does anyone actually watch this stuff?), but the episode was overshadowed in my mind by a quirky accident of rankings: if Taylor Swift beat Beyonce for the "Best Female Video", how can Beyonce go on to win "Video of the Year"? Presumably, video of the year should encompasses the gender-defined category!

In fact, Taylor Swift wasn't even among the video of the year nominees - which seems like an implicit statement of quality right from the start. From that perspective, she shouldn't have even had a chance at best female video. I'm not sure how the nomination process for this whole event works but it appears inherently flawed. My suspicion is that the nominators and voters must be drawn from different populations, for how else could they elect someone for best female video that they did not even consider for video of the year??

Fortunately, college football and its infallible ranking system have returned. Stay tuned.

Wikipedia is an incredible resource, but every now and then it gives me pause. Consider the first two sentences about the seventh-inning stretch:

The seventh-inning stretch is a tradition in baseball that takes place between the halves of the seventh inning of any game. Fans generally stand up and stretch out their arms, legs, necks, backs, calves, fingers, elbows, and other muscles and sometimes walk around.

Is the whole list really necessary?

The Mets just can't catch a break:

On a day when Mets starter Oliver Perez allowed six runs in the first inning, the Mets were in a position to win in the ninth with one swing of the bat, only to be thwarted by one of the rarest plays in baseball.

Eric Bruntlett pulled off an unassisted triple play in the ninth inning, the 15th in major league history and just the second to end a game.

Unfortunately, despite having one of the most advanced online presences among professional sports leagues, MLB's media lockdown (no rebroadcasting without "expressed written consent") means I have to send you here to see the play in action.

The WSJ has printed one of the best "fooled by randomness" pieces I've seen in quite a while, titled "The Triumph of the Random." This one uses streaks in sports as a central metaphor, with DiMaggio's 56-game hitting streak as exhibit A. It presents an immediate disclaimer:

Recent academic studies have questioned whether DiMaggio’s streak is unambiguous evidence of a spurt of ability that exceeded his everyday talent, rather than an anomaly to be expected from some highly talented player, in some year, by chance, something like the occasional 150-yard drive in golf that culminates in a hole in one. No one is saying that talent doesn’t matter. They are just asking whether a similar streak would have happened sometime in the history of baseball even if each player hit with the unheroic and unmiraculous—but steady—ability of an emotionless robot.

The lengthy article then deals with the mathematics of streaks, demonstrating that they are far more probable than we would otherwise think:

A few years ago Bill Miller of the Legg Mason Value Trust Fund was the most celebrated fund manager on Wall Street because his fund outperformed the broad market for 15 years straight. It was a feat compared regularly to DiMaggio’s, but if all the comparable fund managers over the past 40 years had been doing nothing but flipping coins, the chances are 75% that one of them would have matched or exceeded Mr. Miller’s streak.

Next, it moves to psychology and describes the way in which humans seek patterns in randomness as a grounding mechanism with a nice segway by way of my favorites, Kahneman and Tversky, who authored a seminal paper on hot hands in basketball:

If a person tossing a coin weighted to land on heads 80% of the time produces a streak of 10 heads in a row, few people would see that as a sign of increased skill. Yet when an 80% free throw shooter in the NBA has that level of success people have a hard time accepting that it isn’t. The Cognitive Psychology paper, and the many that followed, showed that despite appearances, the “hot hand” is a mirage. Such hot and cold streaks are identical to those you would obtain from a properly weighted coin.

Finally, it deals with the perception of random events:

Why do people have a hard time accepting the slings and arrows of outrageous fortune? One reason is that we expect the outcomes of a process to reflect the underlying qualities of the process itself. For example, if an initiative has a 60% chance of success, we expect that six out of every 10 times such an initiative is undertaken, it will succeed. That, however, is false.

A critical conclusion is laid out:

We find false meaning in the patterns of randomness for good reason: we are animals built to do just that... Many studies illustrate how this basic aspect of human nature translates to a misperception of chance.

Truly an excellent read and I can't recommend it more.

Somehow I never noticed this before, but the marks on the walls of the Harvard Club squash courts form excellent copula scatterplots.

Here is a picture of the court, courtesy HCNY's new website:

And here is a quick simulation I just ran of 10,000 points drawn from a Clayton copula with theta = 1.25:

It's not perfect, but it's pretty close. To fully match the pictured relationship, we'd need to assume the correct marginal distributions as well. Of course one could also make the argument that theres a more complex dependence structure at work here, given the strong diagonal band in the wall markings. Dare I plug the Fourier copula as a more  appropriate tool?

Vanity Fair on Harvard's Vanishing Squash Courts:

Artist James Powers, Harvard ’08, proved to be an invaluable source on two fronts. He knew about the four unused squash courts in Adams House because he had painted in them, seen movies inside them, and, like the other students, stored junk in them over the summer. Had he ever seen them used for squash? “Not in my time,” he reports.

So long, Adams squash courts. We hardly knew you.

This hilarious spot for Nike aired last night - the simple premise (established in the slightly-less-funny "Chalk" ad) is that Kobe and LeBron are inexplicably roommates.

Also, they are muppets.

Click here to view the embedded video.

Seven years ago, the Mets were among the first teams in MLB to adopt a tiered pricing system in which it costs more to see a game against a good opponent than a bad one. At the time, it was the most sophisticated such plan in baseball. Others included simple methods like charging more for weekend games or prime summer games.

The act was a major step toward recognizing that while the supply of tickets was more or less constant for every game, demand could vary wildly. Nonetheless, ticket prices were still set for every game before the season started, and were locked in no matter how attrative (or otherwise) the game ultimately appeared. Rain, cold, chances to see historial achievements, unexpected opponent records (good or bad) - all of these affect demand in ways which can not be anticipated in March.

Now, the Giants have announced a new initiative which will adjust ticket prices up until the first pitch. A software program will estimate demand based on dynamic variables and adjust ticket prices according. The factors include both teams' records, the stats of individual players (including the starting pitchers), the weather, the number of seats left to sell, proximity to gametime, promotional nights, and other similar metrics. Fans showing up on a rainy weekday night just before the game might be able to snag tickets for $5 that were $30 the week before.

It is likely that the model is not nearly as complex as one might think - in fact I imagine this is a perfect example of a time when a simple model can account for a surprising amount of variance. Not that this approach is revolutionary outside MLB - airlines and hotels have been doing something similar for years - but I think its an exciting and approrpriate use of data and would not be surprised if next season the metric is rolled out in a more expansive manner.

To think it was just a decade ago that the concept of statisticians on the field was inconceivable (but taken for granted today) - and now we have teams employing econometric methods to estimate demand. Quelle journee!