For all your fancy-pants statistical needs.

Praise for The Basketball Distribution:

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


Statistically, we can try to estimate a team's overall win% against an average team, and say that's their adjusted Win% (similar to Ken Pomeroy's Pythagorean win%). But this is only part of the picture.

Here I have used my consistency and adjusted ratings to predict home and away win probabilities for every NBA matchup. Instead up predicting how a team would fare against an average team, I predict how they fare on average against every team.

Here are the results (the home teams are the rows, the away teams are the columns).

I plug in the following into the NormDist function.

standard deviation=sqrt(team1consistency^2+team2consistency^2)
(^this estimates overall standard deviation of the two teams' performance, assuming a covariance of zero.)

Speaking of which: Some of you may have thought in the past, "This guy doesn't plug stuff into the NormDist function correctly!" And you would be correct. Technically, I should plug in a value of zero and a mean of an estimated point margin. But in order to find that team's win probability, I would do 1-Normdist(0,est. margin). But this requires more typing, so I use the equivalent, Normdist(est. margin,0).

No comments:

Post a Comment


About Me

I wish my heart were as often large as my hands.