Archive for the 'General' Category

ESPN's Outside the Lines (for my money, probably the best program on the network) showed a very thought-provoking piece today about former NBA guard Cuttino Mobley, who was forced to retire this year shortly after an early-season trade sent him from the Clippers to the Knicks for salary-cap purposes. In the trade physical, it was supposedly discovered that Mobley had a life-threatening heart condition, but new reports have surfaced indicating that Mobley's condition was known to teams as far back as his Houston days (for instance, each of his 4 teams had a clause written into his contract absolving them of liability in the event of on-court death). The report raises questions about the commodification of players as "walking contracts" under the current CBA, an unsettling circumstance particularly heightened by the battle for who gets the cap and/or luxury tax benefits out of Mobley's very serious health condition.

When the league announced the All-NBA Teams this week, there were relatively few surprises. For those who haven't seen them already, the selections looked like this:

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For all of our readers out there who are interested in some X's and O's, the site Jes-Basketball.com has a large library of java-animated play diagrams on file, ranging from basic offensive and defensive sets to some rather obscure plays.

Over the past few decades, "parity" has been the major watchword in professional sports, as frustrated owners feeling statistically eliminated from postseason contention on Opening Day lobbied for changes like salary caps and wild-card playoff spots to even the playing field. And it seems to have worked: at one point the NFL was seeing surprise teams (St. Louis 1999, Baltimore 2000, New England 2001) win the Super Bowl every year, and MLB hasn't seen a repeat champion since the Yankees in 2000.

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This past week, ESPN.com's John Hollinger rolled out a new stat that compares a player's PER (Player Efficiency Rating) to that of a "replacement-level" player, in an effort to incorporate minutes played into an evaluation of the player's worth. Said JH:

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SLAM Online has a great interview with 82games.com head honcho Roland Beech about the past, present, and future of statistical analysis in basketball. And I can say I don't find a single thing to disagree with in Roland's responses.

As I'm sure many of you already know from Justin's post last Monday, my father passed away suddenly from complications of pneumonia last Saturday at the age of 59. First of all, I'd like to thank everyone for their love and support during this difficult time for me and my family. It means a lot to have people thinking of and praying for us right now, while we try to sort this tragedy out. As you can imagine, it's difficult to focus on the minutiae of turnover rates and true shooting percentages when life's big things place themselves squarely in front of your face. At the same time, though, I thought I would share a little bit today about my dad and what the game of basketball meant to our relationship. After all, I wouldn't be here writing for you guys if it weren't for him introducing me to the game many years ago.

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So, did anybody catch that game last night?

In preparation for it, yesterday morning I wrote a rather effusive hosanna about LeBron James' high caliber of play this season, breaking down how LBJ's performance so far had not only surpassed Kobe Bryant's best years, but was also challenging the greatest campaigns of legends like Michael Jordan and Wilt Chamberlain.

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That's right, it's all expectations all the time here. To refresh everyone's memories, on Friday we looked at a very simple way to set up preseason expectations for each team using a linear regression model with the previous season's SRS. Then, yesterday we took that same dataset and added team minute-weighted age as a variable, which helped to (marginally) improve the model's fit.

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On Friday, in an effort to establish preseason "expectations" for each team, we built a very simple model for projecting future performance at the team level. We included both W-L records and SRS scores from the 5 previous seasons in a linear regression, and we discovered that in both cases the only past season that's significant at the 5% level is the year directly before the one we're trying to predict (year "Y-1"). We also found that past SRS scores (which are essentially average scoring margins, but adjusted for strength of schedule) better predict future W-L than past W-L do -- which just confirms what people like John Hollinger have been saying for a long time. Finally, using our regression model, we ranked the biggest positive ('08 Celtics) and negative ('99 Bulls) surprises in NBA history, and showed what the model predicted for the current season as well.

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