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Pythagoras: Solid Fundamentals, Good Upside, Can’t Go Left

I came across this bit of analysis at The Basketball Jones by Scott Carefoot and it caught my interest.

Why the Miami Heat are Better Than You Think

In the analysis, the author uses a regression analysis using a team’s points scored and points allowed as a predictive measure to see whether that team so far is “lucky” or “unlucky” this year in their win total.  The formula is derived from baseball stat legend Bill James‘ approach to evaluating baseball talent.

The argument caught my eye because Carefoot argues, not only that are the Heat the unluckiest team in the league thus far, but our Thunder are THE luckiest.

Here is his chart:

Source: The Basketball Jones

Do you want to see the formula that he applies? (of course you do!)

Statistics are a powerful tool in evaluating teams with the hope that they might have some predictive measure.  The caution in presenting them though is that commonly, the analyst will either put too much weight on it or not enough (if any).  Ultimately, the data stands on its own; you can either put some merit into it, or dismiss it.  So what I thought I would do is apply the formula to the last two seasons and see how useful it was in telling us about the overall success of teams.

(Champ is highlighted, playoff teams in bold)

All game stats provided by NBAstuffer.com

So those are the numbers; what can we glean from them?  What would these stats have told us about the last two years’ success stories, if we did not know how the season ended?

  1. As a predictive measure, last year’s season was a bit of an anomaly, while 2008-09 appeared to be more tighter in conforming to the statistical prediction based on point differential.  Orlando had the highest point differential, yet underperformed in the win column.
  2. Last year, nine out of the 16 playoff seeds actually underperformed, or were “unlucky,” not meeting their expected win total.  San Antonio was the worst at a -5, and Boston, the Eastern Conference representative, was a -1.
  3. Last year, six out of the top 10 “luckiest” did not make the playoffs.  Does that mean that the pluckiest of the bunch outperformed their meager expectations? Could it be that they won games at the end of the season when certain other teams were not actually trying to win?
  4. OKC actually underperformed last year, if we use this metric, and yet their point differential was higher than it is now.
  5. This element of “luck” actually was huge in the Western Conference.  OKC, Portland, and San Antonio all finished with 50 wins, and all of them came up short of their prediction. Meanwhile, Dallas actually jumped all of them by the fortune of their season-tops 6 “lucky” wins.

At the end of the day, I feel like the Double Rainbow guy.  I have no idea what this all means.  I’m not sure this really tells us much of anything due to the organic nature of the way the NBA season works.  What I will say difinitively though is that if a team like the Thunder get those three “lucky” wins, even early on in the season, and play the rest of the way on par for their course, the ramifications of the season’s outcome can be huge.  It could mean the difference between a 4-seed and an 8-seed.  Lucky?  Good?  As refined men such as Cal Hockley might say, a real man makes his own luck.


One response to “Pythagoras: Solid Fundamentals, Good Upside, Can’t Go Left

  1. M December 9, 2010 at 3:32 pm

    There is the actual record, the general degree of over or under-performance on point differential and then there is also the degree of game to game volatility. Using the latter as well can explain individual team stories better than with just the first two.

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