Lots of credit here goes to David Hess (aka @AudacityOfHoops) for his work on a simple estimation of how turnover effect efficiency. Check out his pretty blog!
Given the limitations of that formula, I decided to take it a step further: how much does EACH four factor affect a team's offensive performance? Because every time I check out Ken Pomeroy's team four factors I want to better-quantify those green-or-red bits of data.
I've come up with a way to quantify how deviation of the league-mean by each team's four-factors affects their overall offensive efficiency.
The same can easily be done for defense, but for right now, I'm just going to focus on offense:
WARNING: BORING MATH
I took a regression (which myself and David have done before) of the four factors on offensive efficiency. For each team, I took their four factors, save for the one in question, and multiplied them by the regression estimates. I replaced the one in question with the league average. Finally, I took their raw offense and subtracted this number from it. This gives us an estimate of how a team's deviation from the mean affects their overall offense, in terms of the Four Factors.
Here's the great news:
1) I made an Excel spreadsheet so you can easily plug this in for any team without having to scour for them (just enter the team under "Team")
2) I used the same color scheme as Ken Pomeroy's numbers :)
2) I also made a PDF for those who don't want to use Excel.
Editable Excel File
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