Today is the trade deadline. So the obvious topic of choice is a discussion of a specific trade (or trades). Unfortunately, most of the trades were really not that interesting (at least to me). The one possible exception was the Jermaine O’Neal for Shawn Marion trade. But in thinking about this transaction it occurred to me that I have already noted – as the following posts indicate– that Jermaine O’Neal is not quite as good as people think (a conclusion I think Toronto now understands).
So in an effort to avoid repeating myself (too much), I am going to start the discussion by focusing on a Raptor who might benefit from O’Neal’s departure. As the last post in this list indicates, O’Neal was the Most Overpaid Player in 2007-08. The second player on that list is Andrea Bargnani. And in thinking about the O’Neal-Marion trade, I found my thoughts turning to the idea that Bargnani is now going to be permanently thrust into Toronto’s starting line-up.
Bargnani has actually been starting for the Toronto since December 31. But I think that’s because of injuries to O’Neal and Chris Bosh. With O’Neal permanently out of the picture, Bargnani is now going to be the starting the center on this team.
Bargnani was the first player taken in the 2006 draft. And generally, when we think of the top choice in a draft, we think of a star. At the minimum, we think of a starter. But thus far Bargnani has only started 92 times in the first 199 NBA games he has played. Relative to other number one selections — like Shaq, The Admiral, LeBron, Yao – it’s clear that Bargnani has not quite lived up to the standards of the number one pick. But how bad has he been?
There have been a few “busts” at the top of the draft. Certainly Kwame Brown and Michael Olowokandi didn’t live up to expectations. But if we look at the numbers, Bargnani still has a way to go to even reach the lofty standards of Kwame and the Kandi-Man.
Table One reports the performance of each number one pick – in the lottery era (since 1985) — after three seasons in the NBA. Bargnani’s WP48 [Wins Produced per 48 minutes] this season is -0.059. Such a mark puts him on pace to produce -3.1 wins this season. When we add this production to what Bargnani did his first two years in the league, we see that the number one pick of the 2006 draft could finish his third campaign with -8.1 Wins Produced. Such a mark easily is the lowest level of output of any number one pick taken since 1985. Yes, even Brown and Olowokandi surpassed the production of Bargnani.
One should emphasize that this is not the story if we focus on scoring. Both Kwame and the Kandi Man were below average scorers. In contrast, Bargnani produces points at an above average rate. Unfortunately – as Table Two indicates – he is well below average on the boards (and with respect to steals). Consequently, Bargnani – like Eddy Curry (another scoring center who is not very productive) – doesn’t help his team win.
Despite this lack of production, though, Bargnani is going to start at center for the Raptors. So although the acquisition of Marion helps (yes, Marion does more than O’Neal), the loss of Jamario Moon – and the potential increase in Bargnani’s minutes – is going to hurt. Consequently, it’s possible that the O’Neal-Marion could be one of those rare trades that hurts everyone involved.
More on the Trade
To see how much this trade helps or hurts, though, we should look at a few more numbers. Here is what each player in the trade has done this season (at the All-Star Break):
Shawn Marion: 0.219 WP48
Marcus Banks: 0.006 WP48
Jermaine O’Neal: 0.034 WP48
Jamario Moon: 0.208 WP48
Given these numbers, here are some quick thoughts on the trade:
Miami Heat: O’Neal – as noted before – is not quite the player he was a few years ago. So adding him doesn’t help the Heat this season (O’Neal’s contract does come off the books in 2010, so Miami remains a player in the 2010 free agent market). Moon’s WP48 of 0.208 is only eclipsed on the Heat by Dwyane Wade. So if the Heat gave some minutes to Moon, the loss of Marion could be somewhat offset. Unfortunately for Heat fans, Moon got less than five minutes of playing time in his first game with Miami. If this first game is indicative of how much Moon will play, then it’s likely this trade doesn’t help Miami in 2008-09 (although, the team does get a first round pick sometime in the future, so that might help sometime in the future).
Toronto Raptors: Marion is a small upgrade over Moon on a per-minute basis. Plus, Marion will get more minutes. So that clearly helps. Moon and O’Neal, though, averaged 55 minutes per game. This means that someone on this team is about to get more playing time. As noted, if that’s Bargnani, the Raptors are not helped. The same story would be told if that someone is Jason Kapano. At this point it’s not entirely clear how minutes will be allocated (especially since Bosh is out). Still, looking over the numbers it doesn’t look to me that this trade is enough to get the Raptors in the playoffs this season. And if that doesn’t happen, then the Raptors just traded a future first round pick – and a very productive player in Moon – for the right to stop paying Jermaine O’Neal (a player they shouldn’t have volunteered to pay in the first place).
In sum, this trade clearly doesn’t help the Heat (at least, not this season). And it may not help the Raptors. It might, though, help Bargnani. With his ability to score, this trade might give him enough additional playing time to boost his scoring totals. Given how salaries are determined in the NBA, it’s entirely possible that this trade will increase the chances of Bargnani cashing in on a significant pay raise in the future. So although both fans of the Heat and Raptors might not be happier, Bargnani – a player who is currently the least productive number one pick in the lottery era – may someday look back at this trade as something that led to much future happiness.
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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.