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Praise for The Basketball Distribution:

"...confusing." - CBS
"...quite the pun master." - ESPN

Step Two of the Two-Step Process

The best way to predict point margin is to first predict a team's four factors, then convert the four factors into point margin via linear regression.

The linear regression is the 2nd step, and here are the results (with an R^2 value of about .99)

(Numbers derived from

Step one is a bit harder in some-ways, and should probably be done on a team-by-team basis. We'll cover that soon.


  1. Wouldn't it be better to regress the four factors onto efficiency margin, then adjust that for pace? Possessions (and the intercept) shouldn't have a non-0 value, or else the predicted MOV will change depending on which team you label as the offense.

    I did a regression using only 2009 numbers, and got the following coefficients:

    Intercept 0
    Oefg 1.321490754
    Oto -1.21443408
    Oor 0.632136795
    Oftr 0.104561921
    Defg -1.321490754
    Dto 1.21443408
    Dor -0.632136795
    Dftr -0.104561921

    Those are all exactly the same as yours, but multiplied by a constant (1.350315943). My R^2 is only 0.97.

    How did you end up with a negative intercept anyway? Were the losers always the offense?

  2. I forgot I had auto-calculations turned of in Excel. Those obviously aren't all multiplied by the same constant.


  3. Good point about the possessions - that was pretty stupid of me! Part of the problem is that I was using this on team stats, not game stats.

    I suppose I should zero the intercept! I just find it interesting that I have such a high R^2 value! Definitely inflated it with the possessions coefficient.



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