It applies to any similarly competitive school, too.

Sometimes Harvard Yard literally smells like bullshit. The grass takes a regular beating from the weather and the footsteps of mathematicians eager to find the shortest path to class. So, a few times a year, to spruce it up for the brochures and the visiting parents, the grounds crew gives it a fat coating of organic fertilizer. This is what it takes to be the best.

Harvard prides itself on having the most distinguished faculty, the smartest students, and the greatest resources in the world. But for the next few days, none of that will compare with having one of the the 30 best men's college basketball teams in the country. Last night, the Crimson pulled off an impossible upset against New Mexico. The victory itself was merely unlikely. The absurdity lies in the unlikelihood: UNM is a public school with about a hundreth of Harvard's endowment and a googolth of its cachet. It was like America beating Jamaica in the hundred meter.

The team's recent rise makes it an easy culprit in Harvard's cheating scandal: Both of its co-captains were forced to leave left campus after plagarizing a take-home exam. But athletic pressure was a small part of what caused the mess, just as the mess was a small part of the culture in which it took place.

The biggest problem on campus is bullshit. I say this as a graduate who still can't get the smell off. It's impossible to be the best at everything, no matter how hard the university and its students try. It's much easier to appear to be the best at everything, regardless of whether you actually are.

Freshmen arrive with their personal brands already cultivated. They've taken all the right classes, done all the right extracurriculars, won all the right Domestic Extemp competitions. What do you think happens when you put SIX THOUSAND OF THESE PEOPLE IN ONE PLACE? Every single act must correspond to a résumé bullet point. Nothing, including learning, can be done for its own sake. The social scene is a calculus of popularity that includes future net worth. Depression and alcoholism run rampant, but those are downers. Every single person faces pressure to appear better than he or she is.

In basketball, on the other hand, bullshit doesn't work. The student newspaper can slap "Veritas" on a dead tree and give its editorials a phony air of unearned superiority. But no brand is prestigious enough to shoot the ball as well as Laurent Rivard did last night. All Harvard students are measured as intensely as the ones on the court in Utah, yet few are measured as precisely on their merit.

Last weekend, I went to the sixth annual MIT Sloan Sports Analytics Conference. Attendance has gone up every year, and it gets harder and harder to get a feel for who actually goes to this thing: Why were they there? Were they still all sabermetrics geeks? High-powered businessmen? To find out, I did some analysis of my own, polling over 100 people over the two-day event.

I tried get a sample that represented the whole conference, asking students, executives, media, and panelists. There was about a 90 percent response rate. Nate Silver was the only respondent who gave an answer with a decimal point.

The weird "more/less/average nerdy" result is an example of the "Lake Wobegon Effect," named after Garrison Keillor's mythical hometown "where all the women are strong, all the men are good looking, and all the children are above average." Another possibility is that all of the nerdiness was concentrated in a few nerds, so that most of the attendees were below the mean nerdiness level.

For all of the times "geek" and "nerd" are referenced in the media about the conference, the people here weren't classically nerdy (I think you can trust me to make that distinction). This was a conference for business school nerds, the ones who wear suits to bed. Their dream job is to employ analysts, not do analysis. The word "nerd" is a brand now and that is horrifying.

Update: "Unable to name anyone" should be 16%, not 15%.

Graphics by Jim Cooke.

Twitter reports that the Super Bowl generated 24 million tweets last night. Most of them were terrible, so I just looked at the ones that said "fuck."

I plugged my program, "Fuck_Machine.rb," into Twitter's live stream, grabbing every tweet that contained both "fuck" and a term referencing either the Ravens or 49ers. Fuck_Machine dutifully recorded 226,309 tweets between 6:34 p.m. and 11 p.m. Eastern time, about one percent of Twitter's estimate of the total. The actual tweet number was a bit higher, because Fuck_Machine could only handle 50 tweets every second.

The Ravens won the game, but they won the fuck battle as well: Baltimore inspired 141,064 "fuck" tweets, compared with 108,715 for San Francisco (23,470 tweets contained references to both teams). The tweets ranged from the aggressively negative:

To the profanely exhortative:

Here's a graph of how it played out during the game (the vertical axis represents tweets per minute):

The letters represent important moments in the game. Here's a fuck-based Super Bowl recap, showing who gave a fuck and when.

• A: The Ravens score a touchdown, putting them up 7-0. 2,543 fucks are given at 6:41.
• B: The 49ers connect on a field goal, 7-3. 635 fucks are given at 6:54.
• C: Anquan Boldin makes a great catch. 706 fucks are given at 7:04.
• D: San Francisco fumbles. 712 fucks are given at 7:13.
• E: Touchdown Baltimore, 14-3. 2,254 fucks are given at 7:22.
• F: Colin Kaepernick throws an interception and a fight breaks out. Fuck volume stays at over 1,000 from 7:29 to 7:33.
• G: The Ravens attempt a fake field goal. 967 very confused fucks are given at 7:36.
• H: Joe Flacco connects with Jacoby Jones on a 56-yard touchdown, 21-3. Fuck_Machine breaks for the first time at 7:49, with over 3,000 tweets registered during that minute. Overall fuck volume remains over 1,000 until 7:54.
• I: David Akers kicks a field goal to close out the half, 21-6. Very few football-related fucks are given during halftime.
• J: The second half starts with an 108-yard kickoff return by the Ravens. Fuck_Machine breaks at 8:33, and over 2,000 fucks per minute are given between 8:32 and 8:35.
• K: The power goes out at 8:38. Very few people give a fuck about football for the next 45 minutes.
• L: The power returns at 9:10. Fuck volume is a paltry 345.
• M: The 49ers score their first touchdown, 28-13. 1,119 fucks are given at 9:25.
• N: The 49ers quickly score again, 28-20. Fuck volume reaches 2,974 at 9:33. People are starting to give a fuck again.
• O: Ray Rice fumbles. 2,856 fucks are given at 9:41.
• P: The Niners pick up another field goal, 28-23. Fuck volume reaches 1,876 at 9:45.
• Q: Justin Tucker and the Ravens respond, 31-23. 511 fucks are given at 9:58. No one really seems to give a fuck about field goals.
• R: San Francisco scores another touchdown but fails to convert the two-point attempt, 31-29. 2,544 fucks are given at 10:04.
• S: Baltimore kicks another field goal, 34-29. Fuck volume is 529 at 10:22 and sinks to 348 at 10:26.
• T: The 49ers come within ten yards of the goal line. 1,261 fucks given at 10:28.
• U: San Francisco turns it over on downs. 2,427 fucks are given at 10:35, and fuck volume stays over 1400 for the remainder.
• V: The Ravens take a safety, 34-31. 1,934 fucks are given.
• W: Time expires and the Ravens win the game, 34-31. Fuck_Machine breaks, with over 3,000 fucks per minute given between 10:45 and 10:50.

Join us next year, when we'll try to figure out whether anyone gave a shit.

My god.

During halftime of last night's Clippers-Suns game, the Inside the NBA crew had some fun at the expense of Charles Barkley, who mentioned during the second quarter that he gets his eyebrows waxed. The segment began with a mocking Shaquille O'Neal getting the same treatment, and it quickly devolved into transparent gay-baiting. Chris Webber put on lip gloss and Kenny Smith dangled his newly manicured fingernails off of his limp wrist. Then came the multiple slow-motion replays of the bit, because men being effeminate is even funnier at half speed!

Sir Charles, to his credit, didn't give a shit. When they cut back to Phoenix to get his reaction, he called out his colleagues for being insecure with their sexuality. He's also one of the few players who has publicly supported gay athletes. If NBA locker rooms are anything like TNT's halftime show, there's still a lot of work to do.

Hall of fame ballots follow their own own internal logic. For instance, regardless of how they feel about steroids, almost all voters agree with both or neither of the following statements:

• Barry Bonds should be in the Hall of Fame.
• Roger Clemens should be in the Hall of Fame.

Bonds and Clemens aren't similar players, but the essential question about their candidacy is the same: "Should an all-time-great player be elected even if he took steroids?" Voting for both is like saying yes, voting for neither says no, and voting for one and not the other is akin to making a bunch of fart noises.

Thanks to some new data, we can quantify not just the players' performance, but also the relationships among the arguments about their performance. Leokitty assembled a spreadsheet of Hall of Fame ballots publicly released by BBWAA voters over the last five years, allowing us to see who voted for whom instead of just the raw vote totals.

Using that information, I found the relationships between a vote for one player on the ballot on a vote for every other player. You can view the results here.

The values refer to the correlation between the two players: for instance, in 2013, there was a .97 percent correlation between voting for Bonds and Clemens, by far the highest correlation on the list. Larry Walker and Jack Morris, at the other end of the spectrum, had a correlation of negative .24. Voters who thought Jack Morris was a Hall of Famer had completely different standards from the voters who thought Larry Walker was one. Other inimical pairings: Don Mattingly and Mike Piazza, and Don Mattingly and Roger Clemens.

I also correlated each player's votes with the total number of players, out of a possible 10, that each voter had chosen. Voting for Alan Trammell strongly correlated with voting for a higher number of players overall—suggesting that Trammell's supporters are the voters who believe in a more inclusive Hall. Update: Here's a heat map of the 2013 data, courtesy of reader MaltedLaurelBridge:

The correlations in bold are statistically significant at a 95 percent confidence level. Here are some more observations I made; feel free to add in the discussion below:

• Anti-steroids voters also seem more likely to vote for older candidates. The age of the voters themselves might be the common denominator.
• Craig Biggio and Mike Piazza had a strong correlation, which might imply that they were on the wrong side of the "Should I vote for a deserving player on his first ballot?" razor.
• Larry Walker's candidacy distills the sabermetric argument. In 2013, he was strongly aligned with votes for Tim Raines, Edgar Martinez, Jeff Bagwell, and Trammell, all beloved by nerds, and was aligned against Morris, the foil for the last few years against more statistically deserving candidates.
• Fred McGriff was negatively correlated with almost every possible steroid user in this year's balloting. Perhaps some voters are trying to find a clean, statistically similar alternative to Mark McGwire, Sammy Sosa, and Rafael Palmeiro. Frank Thomas will presumably have a similar pattern next year.
• McGwire, Sosa, and Palmeiro have high correlations with each other, but it's likely that there are cases of voters choosing one at the expense of the others.
• Bert Blyleven is the classic example of sabermetrics influencing Hall of Fame voters, but the data suggests that other forces are at work. He was strongly correlated with Andre Dawson and Morris, players disdained by the stats crowd, in 2010. This type of coalition might be what eventually gets Tim Raines to 75 percent.
• Don Mattingly voters have no logic, internal or otherwise. Candidates who have little chance of being elected yet stay on the ballot like Mattingly, Tommy John, Dale Murphy, and Dave Parker tend to be correlated with each other and against easy choices like Rickey Henderson and Roberto Alomar. You'd think those voters would advocate for a larger Hall, too, but their vote-total correlations are among the lowest on the board.
• Lee Smith remains a fairly popular choice, but he's had no significant correlation with any other player since 2012. This doesn't (necessarily) mean that a vote for Smith makes no sense. It may be that the argument about saves and relief pitching doesn't match up with other Hall of Fame arguments.
• The next couple of years of balloting will introduce Greg Maddux, Randy Johnson, Pedro Martinez, Tom Glavine, Mike Mussina, and John Smoltz. The last few years have been hitter-heavy, and it will be interesting to see how voters choose to balance their ballots between offense and defense, not to mention how they choose to balance a ballot that has around twenty deserving candidates.

• [Google Docs]

The Information by James Gleick. It's about the cultural and scientific history of information and information theory. He gets into the nuts and bolts a bit, but it's a good read even if you skim those parts.

http://www.amazon.com/The-Information-History-Theory-Flood/dp/1400096235/ref=cm_cr_pr_product_top

Collect all 150 Pokemon strategy guides.

http://www.valorebooks.com/textbooks/pokemon-blue-elizabeth-m-hollinger-paperback/9780761522829?utm_medium=referral&utm_campaign=Froogle&utm_source=Froogle&date=11/21/12&buy=3