I don't want to simply summarize the book or give chapter by chapter run down. Instead I'll list a few key points and also extrapolate a bit.
Scoring in the NBA is over valued with respect to paychecks and wins. High volume shooters who score hurt there team by using up so many shots and converting at a low percentage. Rebounding, defense, and assists are undervalue with respect to winning and pay.
This I already knew from his blogging. There is a heavy emphasis on regression analysis and multiple season data collection to come to conclusions. This makes sense. The more data, the more accurate the conclusions can be.
It also got me thinking about the proper place of anecdotal evidence. When I think of teams losing a lineman in football, especially a star lineman, and then losing, is there a way to properly study this? What about occurrences that are rare and so are essentially anecdotal? What about so-called black swans? This data do not necessarily lend themselves to the type of analysis that David Berri does. I noticed a difference between the types of analysis done; while I don't have the knowledge, database, or computing power to do the analysis he does, this blog can be more focused on anecdotal analysis and trying to distill low-frequency data analysis from the mountain of sports data being collected.
I don't have the means to do what David Berri does; but anyone can do what Nicolas Nassim Taleb does.