Kottke and Freakonomics were kind enough to link over here, which has brought more queries about salaryper. Rather than piling onto the original web page, I’ll add updates to this section of the site.
I didn’t include the project’s back story with the 2008 version of the piece, so here goes:
Some background for people who don’t watch/follow/care about baseball:
When I first created this piece in 2005, the Yankees had a particularly bad year, with a team full of aging all-stars and owner George Steinbrenner hoping that a World Series trophy could be purchased for $208 million. The World Champion Red Sox did an ample job of defending their title, but as the second highest paid team in baseball, they’re not exactly young upstarts. The Chicago White Sox had an excellent year with just one third the salary of the Yankees, while the Cardinals are performing roughly on par with what they’re paid. Interestingly, the White Sox went on to win the World Series. The performance of Oakland, which previous years has far exceeded their overall salary, was a story, largely about their General Manager Billy Beane, told in the book Moneyball.
Some background for people who do watch/follow/care about baseball:
I neglected to include a caveat on the original page that this is a really simplistic view of salary vs. performance. I created this piece because the World Series victory of my beloved Red Sox was somewhat bittersweet in the sense that the second highest paid team in baseball finally managed to win a championship. This fact made me curious about how that works across the league, with raw salaries and the general performance of the individual teams.
There are lots of proportional things that can be done too—the salaries especially exist across a wide range (the Yankees waaaay out in front, followed the another pack of big market teams, then everyone else).
There are far more complex things about how contracts work over multiple years, how the farm system works, and scoring methods for individual players that could be taken into consideration.
This piece was thrown together while watching a game, so it’s perhaps dangerously un-advanced, given the amount of time and energy that’s put into the analysis (and argument) of sports statistics.
That last point is really important… This is fun! I encourage people to try out their own methods of playing with the data. For those who need a guide on building such a beast, the book has all the explanation and all the code (which isn’t much). And if you adapt the code, drop me a line so I can link to your example.
I have a handful of things I’d like to try (such as a proper method for doing proportional spacing at the sides without overdoing it), though the whole point of the project is to strip away as much as possible, and make a straightforward statement about salaries, so I haven’t bothered coming back to it since it succeeds in that original intent.