In Part 1 this morning, we looked at the most prominent players in the history of our NBA Tuesday series on MVPs, and now in Part 2, we are going to look at the most “overrated” players in the league’s past. This does not mean these players are not “great”—it just means they’re not as great as they have been perceived to be in terms of value.
Using the sabermetric measurement of MVP Award Shares, we can see which players have been overvalued by voters in comparison to our evaluations based on Win Shares and Player Efficient Rating. This is our list of the most overrated MVP candidates/winners in NBA history:
- Magic Johnson
- Bill Russell
- Tim Duncan
- Kobe Bryant
- James Harden
- Julius Erving
- Kevin Durant
First reaction might be … WHAT?! How can these players be overrated?
Well, they got a lot of MVP votes at the time, but none of them ultimately won multiple MVP awards from us. For example, Magic may be the best Los Angeles Lakers player ever, but due to circumstances beyond his control, we didn’t give him an MVP nod ever. In fact, the three years Magic won the MVP vote, we re-assigned the hardware to Michael Jordan. That’s just bad luck.
Magic earned the fifth-most MVP vote shares in history, so clearly he was an epic player, but again, sometimes circumstances beyond a player’s control determine his historical destiny/legacy. Likewise for Russell: He won five MVP votes, but we took them all away based on sabermetrics. That doesn’t make him any less “great” overall, but it does put his career into better context.
Duncan won two MVP awards; we only confirmed one of them. Erving is a special case, though, as we took away his one NBA MVP and gave it to Kareem Abdul-Jabbar, but Doctor J did win three ABA MVP awards—and we confirmed all of those. That has nothing to do with the NBA MVP vote shares above, though.
Harden and Durant have a chance to win more hardware, of course, so the case is not closed on them. However, as single-time winners in our book, you can see they’ve gotten a lot of MVP votes over the years with relatively little to show for it.
This is not an exact science, of course, and we are okay with others interpreting data differently than we have. But this has been our show for the last 17 months, and now it draws to a close with some intriguing conclusions and notions. We hope you enjoyed the ride … and come back next week for the next series of retrospective analysis.