Posts tagged as:

football

Data wars

January 11, 2010 in Data

The NYT writes about the military’s data problem:

Air Force drones collected nearly three times as much video over Afghanistan and Iraq last year as in 2007 — about 24 years’ worth if watched continuously. That volume is expected to multiply in the coming years as drones are added to the fleet and as some start using multiple cameras to shoot in many directions.

A very interesting read for the dataheads among us. The comparison to football broadcasts also caught my eye – televised sports are so frequently compared to battles and war, and here we see the army coming to the athletes for advice:

But while the biggest timesaver would be to automatically scan the video for trucks and armed men, that software is not yet reliable. And the military has run into the same problem that the broadcast industry has in trying to pick out football players swarming on a tackle.

So Cmdr. Joseph A. Smith, a Navy officer assigned to the National Geospatial-Intelligence Agency, which sets standards for video intelligence, said he and other officials had climbed into broadcast trucks outside football stadiums to learn how the networks tagged and retrieved highlight film.

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Moral hazard and the NFL

November 11, 2009 in Data, Sports

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.

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Questionable rankings

September 14, 2009 in Data, Sports

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.

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I recently stumbled on a strange cyclical pattern for the word “spread”, as you can see here:

Spread Trend

Why would there be such a pattern?  I believe the reason has to do with the football season, which begins in September and ends in early February.  Football is the most bet on sport, and the most common bet in football is against the spread. Therefore, the football season and spread bets are the fundamental drivers of this cyclical pattern. what do you think?

(By the way, that atypical spike at the far right of the “spread” graph is due to people searching for information on the spread of swine flu.)

Because the search volume for “football” is so much larger than that for “spread”, it is difficult to graph them both using Google Trends (even when limiting results to the United States). Instead, I have exported and rescaled the data to create my own version of the graph:

Spread vs FootballFinally, using the newfound Google Insights tool, I can compare the relative growth of US-based searches for “football” and “spread”, only within pages Google classifies as gaming-related. The blue is spread and the red is football:

Relative Growth of "Football" and "Spread"

Convinced yet?

-R & J

Click here for a live view of this trend; and here for a live view on Insights.

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I apologize for being late with this:

YouTube Preview Image

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