rc3.org Rafe Colburn on software development (and other topics)
Your 2009-2010 NBA Preview
The Wages of Wins blog has some bad news for most NBA fans:
Here is an interesting factoid about the NBA Finals. Since 1978 (the first year we can calculate Wins Produced) no team has won an NBA title without one regular player (minimum 41 games played, 24.0 minutes per game) posting at least a 0.200 WP48 [Wins Produced per 48 minutes]. Only one team – the 1978-79 Seattle Super Sonics [led by Gus Williams with a 0.208 WP48] – managed to win a title without a regular player crossing the 0.250 threshold. And only four other champions didn’t have at least one player surpass the 0.300 mark. This tells us – and hopefully this is not a surprise – that to be an elite team you must have at least one elite player.
Okay, now let’s connect this factoid to the draft. Since 1995, no player who posted a below average college PAWS40 [Position Adjusted Win Score per 40 minutes] his last year in college managed to post a career WP48 above the 0.200 mark (after five seasons, minimum 5,000 minutes played). So although college numbers are not a crystal ball (and really, college numbers are not perfect predictors of what a player will do in the NBA), it does seem like players who don’t play relatively well in college are not likely to become superstars in the NBA.
In short, if your favorite team doesn’t already have a truly great player, they’re highly unlikely to win a championship. And the odds are that they won’t find the great player they need in the draft.
This article also makes an important point about synthetic stats. PAWS40 is a stat that the Wages of Wins people made up. Its value is solely in its correlation with more tangible measures of success. Many people who are suspicious of quantitative analysis hate stats like these, but the proof is in the pudding. When you have a derived statistic that correlates this closely with something useful to measure (like championships or wins), that statistic carries more value than any of the more organic stats, like rebounds per game, or shooting percentage.
Links from May 20
Long delayed roundup of links:
- Dan Benjamin: Top 10 Programming Fonts. I’m currently giving Inconsolata a whirl.
- Jasmin Blanchette: The Little Manual of API Design. A very interesting looking PDF that I intend to read.
- John Quiggin: Austrian Business Cycle Theory. A very well written critique.
- Advanced NFL Stats: Draft Success by Team. Not enough attention is paid to the long term results of the draft.
- James Carr: TDD Anti-Patterns. I’m a sucker for lists like this.
- Firediff. A diff plugin for Firebug.
- Continuing Intermittent Incoherency: Ending The ga.js Wait.Using Dojo to address some of the problems with ga.js, the JavaScript file used by Google Analytics.
- Eliot Spitzer: If Judge Posner believes this, the world really has changed – One of the most prominent free market intellectuals thinks the market is incapable of setting CEO pay. Judge Posner has gone on to say many even more provocative things lately. This week he’s guest blogging for Andrew Sullivan.
- AisleOne: 8 Simple Ways to Improve Typography In Your Design. Very good article on improving your use of type.
- James Duncan Davidson: Dear Speakers. Tips for conference speakers.
- Ajaxian: FirePHP: Tying together Firebug and PHP. A means of packaging debug information for Firebug to consume with AJAX responses.
- LearnHub: How to Compare Hosted DNS Providers (with Data!). DNS performance is an underrated piece of the overall site performance picture.
- Seed Magazine: Getting Past the Pie Chart. On the state of data visualization.
- USA Today: Announcing baseball’s all-stars in the broadcast booth. Ranking the baseball broadcasters.
- A.V. Club: Turn off the shuffle: 25 great albums that work best when listened to from start to finish.
- Findings from the A LIST APART Survey, 2008. The results are interesting, but what I really like is the CSS used to create the charts.
- Web Style Guide 3. Filing this away for later.
- Chad Fowler: 20 Rails Development No-No’s. Compiled from responses to a request for feedback on Twitter.
- Last.fm Blog: Mapreduce Bash Script. Very elegant hack.
- Migrating from svn to a distributed VCS. This is specific to the Python code base, but it is a great general resource.
- Digg the Blog: Introducing Digg’s IDDB Infrastructure. Something I need to digest.
- Patrick Peak and Paul Barry: Presentation on BrowserCMS. It’s an up and coming CMS built using Ruby on Rails.
- Rogers Cadenhead: Bit.ly Builds Business on Libya Domain. On the risks of relying on the technical governance of an authoritarian dictatorship.
- dotfiles.org: .zshrc. A collection of zsh init scripts.
- UXmatters: Refining Data Tables. Tips on creating usable reports.
- Z-Shell Frequently-Asked Questions. From my recent zsh obsession.
- Fried CPU: zsh: The last shell you’ll ever need!. zsh advocacy.
- 2009 Rubyist’s guide to a Mac OS X development environment. This is where I got the idea to try zsh in the first place.
- Time: Detroit’s Beautiful, Horrible Decline . An amazing set of photos.
- James Dumay: Mac OS X Tip: Preventing accidently launching FrontRow when cycling windows. This happens to me all the time.
- Ms. Glaze: Make It Nice or Make it Twice. Very much applicable to software development.
- Michael Ruhlman: Duck Confit: It’s What’s For Lunch. Who doesn’t want to confit their own duck?
Are great programmers hired or made?
As sports fans know, the NFL draft is this weekend. In many ways, it’s the most exciting event of the year for football fans. Every team gets to participate, and fans have the chance to believe that their favorite team has improved itself, at least until games are played and reality sets in. Mike Tanier has written the best article I’ve read analyzing the meaning of the NFL draft — Made, not Born. I don’t want to talk about it in terms of football, though, but rather in terms of hiring software developers.
Years after the draft, players are called a “bust” or a “steal” based on how they perform, but Tanier’s inarguably true argument is that how players develop once they reach the NFL is more important than their qualities when they were drafted. Incredible athletes who are drafted into a bad situation often have short, unimpressive careers. Lesser athletes who are drafted into good situations wind up in the Hall of Fame. People obsess too much over draft analysis and not enough over how well teams develop players. (Indeed, many teams that are considered great at picking players in the draft are more likely great at developing the players they pick.)
What does this have to do with software development? Obviously hiring developers is different than drafting football players. What I think is similar, however, is that what you do to enable programmers to succeed once they start work is just as important is hiring the right people in the first place. There are all kinds of situations a talented programmer can be placed in that will lead to their writing poor quality code and developing bad habits that are hard to break. A lesser programmer on a good team with solid processes and better mentors can produce great software.
This is one of the things I wonder about when I read articles about Google’s hiring practices. Does Google produce the software that they do because they hire incredibly talented people, or do they create an environment for developers that enables them to make the most of their talent? I expect that they’re good on both counts, but people seem to obsess more over the former than the latter.
Pick up basketball etiquette
Jan Chipchase mentioned the specific etiquette of a skateboard park he visited in San Diego, and it made me think of a conversation I was having recently about the rules of etiquette at basketball courts.
I learned basketball court etiquette when I was in college, playing with people from the dorms and the neighborhood around the school on an outdoor court on campus.
The first and most basic rule is that winners stay. I can’t remember how many points we played to, although I think it was 11, but regardless, the winning team stayed on the court to be challenged by the next group of people who were waiting. You get dibs on leading the team to challenge the winner by saying, “I got next” before anybody else did. The person who “has next” recruits the challengers from the group of people who are also waiting — taking someone from the losing team if there are more than enough people waiting is bad manners. That’s how basketball courts are run everywhere.
In half court games, the additional rule is “make it take it”. In real basketball, the ball changes possession after a team scores, but in pickup half court games, when you score you get the ball back. That keeps games moving quickly so that more players can rotate in.
When there aren’t enough people to play a game, people tend to shoot around while they wait for more people to show up. There’s etiquette for that, too. First of all, it doesn’t matter if you brought a ball, in a shoot around situation everybody gets to play. Getting a rebound entitles you to take a shot. If you make your shot, the person who fields the ball passes it to you. That’s called “change”. If someone else tries to keep the ball after you make a basket, you say, “Gimme my change,” and they are supposed to pass the ball back to you so you can shoot again.
There are a lot of other rules, too, and judging from a street game I was watching the other day, the rules are pretty much the same as they’ve ever been.
What’s interesting to me is that every community or subculture has its own etiquette, whether it’s a message board for fans of a TV show, the regular crowd at a popular restaurant, or an IRC channel. I’m always a little surprised by people who don’t take the time to pick up these rules of etiquette before jumping into a new situation.
The limitations of blog coverage
The USS Mariner (a baseball blog) has as good a short explanation of where blogs trail newspapers and other outlets in terms of what they can provide. The topic in this case is sports, but it holds up for other topics as well:
I’m (obviously) a huge proponent of blog coverage, but there’s no way it fills the gap of a major paper. We don’t get press access. We can’t go talk to Wakamatsu or anyone on the team unless we know them personally. We don’t have the ability to spend eight hours interviewing people about a breaking issue and turning around something insightful for the next day. The research and analysis done here or on Lookout Landing or anywhere is done essentially for free (well, not Lookout Landing, obviously, as they get to bathe in a hot tub of Kos’ money every night). There’s a lot you can’t do as a writer when your budget is zero.
This disparity isn’t as large as it once was — Talking Points Memo alone has shown that “blogs” can break big news stories, but sites that do commentary are reliant on the professional, full time media to dig up the news that they comment on.
Links from January 23rd
I’m going back to packaging up my del.icio.us bookmarks daily and posting them here.
- The Black Triangle is an article from 2004 about game development found by Jason Kottke. It describes the disconnect between programmers and users, where users are unimpressed by seeing something relatively simple on the screen, and developers are thrilled at the huge amount of work that into getting that simple thing onto the screen. I’ve found it’s never a good idea to show customers the Black Triangle. It always comes later in the process than they’d think and often freaks them out.
- waferbaby: The Setup. Interviews with people about their computer setups. I can never read enough of these.
- New York Times: Gazan Doctor and Peace Advocate Loses 3 Daughters to Israeli Fire and Asks Why. The horrific cost of war.
- Dr. Saturday: Australian Rules’ blood’s worth bottling. A proposed playoff structure for college football. A more interesting approach
- Going.com: Newspapers Covering Obama’s Inauguration. A huge collection of newspaper front pages from President Obama’s inauguration. And yes, it still feels weird to type “President Obama.”
- CSS Newbie: The EqualHeights jQuery Plugin. I’m always looking for better ways to set columns to equal heights on a Web page.
- Glenn Greenwald: Mohammed Jawad and Obama’s efforts to suspend military commissions. When anyone questions whether the United States tortures people or tortures the wrong people, you can forward them the story of Mohammed Jawad, a teenager captured in Afghanistan who was coerced to confess to killing US soldiers with a grenade. The military prosecutor in his case petitioned that he should be released and ultimately resigned rather than prosecute him.
Getting ready for the BCS championship
First, ignore the fact that the BCS Championship can in no way be regarded as an actual national championship. Then go read Smart Football’s collection of posts related to the teams in the championship. If you want to understand football more deeply, it’s the best resource out there.
New York magazine interviews Nate Silver
New York magazine has an interview with Nate Silver of fivethirtyeight.com, this year’s go-to polling analysis site.
I’ve been reading Nate’s baseball analysis for years and was thrilled to see that he was applying his analytic approach to political polling this year. The results have not been disappointing. This paragraph describes my general reaction when I found out who was running fivethirtyeight.com:
Silver’s site now gets about 600,000 visits daily. And as more and more people started wondering who he was, in May, Silver decided to unmask himself. To most people, the fact that Poblano turned out to be a guy named Nate Silver meant nothing. But to anyone who follows baseball seriously, this was like finding out that a guy anonymously running a high-fashion Website turned out to be Howard Cosell. At his day job, Silver works for Baseball Prospectus, a loosely organized think tank that, in the last ten years, has revolutionized the interpretation of baseball stats. Furthermore, Silver himself invented a system called PECOTA, an algorithm for predicting future performance by baseball players and teams. (It stands for “player empirical comparison and optimization test algorithm,” but is named, with a wink, after the mediocre Kansas City Royals infielder Bill Pecota.) Baseball Prospectus has a reputation in sports-media circles for being unfailingly rigorous, occasionally arrogant, and almost always correct.
There are two things that I find interesting about this. The first is that I’ve been reading quantitative analysis of sports for years and wondering how the lessons drawn from that analysis can be applied to other fields. Silver’s work is illustrating just how applicable those lessons are, and I wasn’t surprised to read that he is being invited to speak before business audiences on his work.
The second is that it shows yet again how the secret to being a successful blogger is producing excellent content. Anyone who’s thinking about starting a blog should look at the success Silver has had. He started the year with a diary on the Daily Kos and now he runs a political blog that gets millions of views. Do great things, and the audience will be there.
The lesson for long-time bloggers with small (but wonderful) audiences is self-evident, sadly.
Sports statistics analysts take over the world
Somehow, Nate Silver’s political Web site escaped my notice until today. Silver is using the same techniques he and other used in building improved baseball statistics to analyze the performance of pollsters in 2008 elections, and to aggregate multiple polls into an accurate prediction of voter behavior.
The site provides a lot of interesting numbers, including the odds of various scenarios occurring, like “Obama wins all Kerry states” and “McCain loses OH/MI, wins election.” The site also provides return on investment rankings for the states, and the individual chance of the candidates winning each state.
The reason this post has the subject it does, though, is that it’s fun to watch sports analysis go mainstream. Sports analysis is a perfect training ground for statistical analysis because of the discrete raw statistics that can be used, and the fact that predictions can very easily be compared to actual results.
Most sports analysis comes down to a simple question, “Which things help teams win?” So if I’m a football analyst, I may argue that average time of possession better predicts winning than average margin of victory. I can then process the historical data for as many seasons of football as I like and test that argument. It doesn’t matter how beautiful my theory is, the data will quickly show whether I’m right or wrong.
It’s not surprising to me to see people who have cut their teeth in the world of sports analysis start applying their methods to other areas. The numbers may be different, but the discipline is the same. Silver is doing with polling numbers and election results what he did before with batting averages and baseball games.
If nothing else, it makes me feel like all of the time I’ve spent reading about quantitative analysis of sports hasn’t been a total waste.
If you’re into this sort of analysis, there’s also the Princeton Election Consortium, which posted a mild critique of Silver’s methodology. And for a more naive analysis that just looks at the latest poll result for each state, see electoral-vote.com.
Winning process
Paul DePodesta is a baseball guy who was made famous in Michael Lewis’ book Moneyball. At the time of the writing he was the assistant to A’s general manager Billy Beane, and then went on to serve as general manager of the Los Angeles Dodgers. Now he works in the front office for the San Diego Padres. On his blog, he writes about the basics of building a successful team. The key is to focus on process rather than outcome:
We all want to be in the upper left box – deserved success resulting from a good process. This is generally where the casino lives. I’d like to think that this is where the Oakland A’s and San Diego Padres have been during the regular seasons. The box in the upper right, however, is the tough reality we all face in industries that are dominated by uncertainty. A good process can lead to a bad outcome in the real world. In fact, it happens all the time. This is what happened to the casino when a player hit on 17 and won. I’d like to think this is what happened to the A’s and Padres during the post-seasons.
As tough as a good process/bad outcome combination is, nothing compares to the bottom left: bad process/good outcome. This is the wolf in sheep’s clothing that allows for one-time success but almost always cripples any chance of sustained success – the player hitting on 17 and getting a four. Here’s the rub: it’s incredibly difficult to look in the mirror after a victory, any victory, and admit that you were lucky.
The whole article is well worth reading.
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