Last year Andrew Bogut led the Milwaukee Bucks with 8.9 Wins Produced (WP). If the universe of NBA players only consisted of Milwaukee Bucks, Bogut would deserve to be very well paid. And in such a universe, it may not be surprising to see Bogut receive $72.5 million over five years.
In the world we actually live in, though, there are other NBA big men who do not play for the Bucks. When we consider those players, Bogut’s contract appears quite puzzling. After all, Bogut’s WP48 [Wins Produced per 48 minutes] was only 0.157 last season. Yes, this mark bests the mark of an average player (average is 0.100). But relative to other big men, Bogut’s productivity doesn’t seem to justify his pay.
Or to put it another way, if Bogut’s salary is the new standard in the NBA, a number of big men should be seeing much bigger salaries. Assuming Bogut does not improve (and that may or may not be a great assumption), Bogut is going to be paid $1.62 million per win over the length of his contract. If this is the cost of each win, here are the five-year salaries for all the power forwards and centers that were more productive than Bogut last season (assuming their productivity also remains unchanged).
Dwight Howard [24.6 WP, 0.382 WP48], $200.1 million
Marcus Camby [21.0 WP, 0.365 WP48], $170.7 million
Tim Duncan [18.1 WP, 0.328 WP48], $147.5 million
Kevin Garnett [17.9 WP, 0.370 WP48], $146.0 million
Tyson Chandler [16.3 WP, 0.281 WP48], $132.6 million
Amare Stoudemire [16.3 WP, 0.291 WP48], $132.2 million
Lamar Odom [15.4 WP, 0.253 WP48], $125.0 million
Carlos Boozer [14.8 WP, 0.251 WP48], $120.5 million
Andris Biedrins [14.5 WP, 0.334 WP48], $117.6 million
Shawn Marion [13.6 WP, 0.281 WP48], $110.3 million
Dirk Nowitzki [13.3 WP, 0.231 WP48], $108.2 million
Al Jefferson [13.2 WP, 0.217 WP48], $107.4 million
David Lee [12.7 WP, 0.259 WP48], $103.3 million
Emeka Okafor [11.8 WP, 0.208 WP48], $96.0 million
Jeff Foster [11.6 WP, 0.296 WP48] $94.6 million
Antawn Jamison [11.5 WP, 0.180 WP48], $93.4 million
Samuel Dalembert [11.2 WP, 0.197 WP48], $90.8 million
Brad Miller [10.3 WP, 0.197 WP48], $83.7 million
Chris Kaman [10.1 WP, 0.233 WP48], $82.3 million
Chris Bosh [9.9 WP, 0.197 WP48], $80.9 million
Yao Ming [9.9 WP, 0.232 WP48], $80.4 million
Pau Gasol [9.8 WP, 0.200 WP48], $79.5 million
Joe Przybilla [9.0 WP, 0.239 WP48], $73.6 million
Al Horford [9.0 WP, 0.170 WP48], $73.1 million
If these 24 players were paid at the Bogut-rate over the next five seasons, they would collect $2.65 billion. Yes, that’s billion.
Of course, the Bucks are hoping Bogut will improve. After all, he is only 23 years old. So perhaps Bogut’s future numbers will justify this contract.
Before one goes too far down that road, though, we need to consider Bogut’s WP48 in his first three seasons:
Year One: 0.140
Year Two: 0.145
Year Three: 0.157
Yes, he is improving. But his first three years do not suggest that Bogut is going to post Al Jefferson numbers anytime soon.
Year One: 0.118
Year Two: 0.113
Year Three: 0.252
Year Four: 0.217
Or Emeka Okafor numbers either:
Year One: 0.137
Year Two: 0.103 (only played 26 games due to injury)
Year Three: 0.290
Year Four: 0.208
Each of these players posted a significant leap in year three. Such a leap didn’t happen for Bogut. And now that he has been given $72.5 million, his incentive to make such a jump just got reduced a bit.
Of course, all this is good news for Bogut. But if you are a Bucks fan, you have to wonder what kind of team you are going to see when so much of the team payroll is dedicated to a player that is “good”, but not likely to be “great.”
Update: Okay, maybe I should read what I said in the past before I post more stuff. A few weeks ago – in a post on the NBA’s Overpaid – I argued that a win in the NBA is worth $1.67 million. When we see this figure, Bogut’s salary doesn’t seem so strange (and this post doesn’t seem too “great” or even “good”).
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Our research on the NBA was summarized HERE.
Wins Produced, Win Score, and PAWSmin are also discussed in the following posts:
Finally, A Guide to Evaluating Models contains useful hints on how to interpret and evaluate statistical models.