Last September I made the argument that Jason Kidd Really Did Help the Mavericks in 2007-08. My argument – summarized below — was based almost entirely on efficiency differential (offensive efficiency minus defensive efficiency).
What does efficiency differential tell us about the Kidd acquisition? At the time of the trade Dallas had a differential of 4.3. When the season ended, the team’s differential stood at 4.9. For a team to increase its differential from 4.3 to 4.9 in just 29 games, that team would have to post a mark of 6.0 in the final games of the campaign. In other words, the Mavericks clearly improved after Kidd came to town.
That was the story of 2007-08. At the midpoint of the 2008-09 season the Mavericks – with essentially the same cast that finished the 2007-08 season – have a differential of 1.50. In other words, Dallas has declined. And of course we wonder why?
An answer begins with Table One.
Table One reports two views of the Mavericks. The first reports how much this team could have expected to win given what these players did in 2007-08. The second reports what this team can expect given this team’s performance in 2008-09. As one can see, there’s a substantial difference in the two views.
When we look at the individual players we see a number of players who have declined relative to last year. Specifically, Dirk Nowitzki, Josh Howard, DeSagana Diop, Jason Kidd, Antoine Wright, Brandon Bass, and Jason Terry are offering a combined 21 fewer projected Wins Produced relative to last year.
Looking for an Explanation
For this many players to suddenly offer less begs for some sort of explanation. Here are some possibilities.
- Diminishing Returns: When Jason Kidd arrived it was suspected that his immense productivity would have a substantial negative impact on his teammate’s performance. Certainly diminishing returns exists in the NBA. But as we will (briefly) detail in the next book, the effect is not that large. Furthermore, there is reason to think it’s not a very big issue in this instance. Below the standard table reported above is another table that reports what the Mavericks could expect had these players maintained what they did in 2007-08 after Jason Kidd arrived. As one can see, with Kidd in 2007-08 these players were still quite good. The decline did not happen with the arrival of Kidd, but with the end of summer in 2008. In sum, diminishing returns – at least with respect to Kidd’s arrival– doesn’t look like a good explanation.
- Coaching: Last November Slate.com noted a study I co-authored examining coaching in the NBA. Essentially we found that most coaches don’t have a substantial impact on player performance (this study has been expanded greatly for the next book). Given this research we might expect that the move from Avery Johnson to Rick Carlisle might not make a difference. Of course, just because the typical result is that coaches don’t alter performance, it doesn’t mean that a specific coach or coaches can’t have an impact. So perhaps Carlisle is to blame (or Avery Johnson might feel vindicated).
- Age and Injury (and attitude): It’s also possible that we are seeing the impact of age and injury. Nowitzki, Kidd, and Terry have all celebrated their 30th birthday. So their decline might be due to age (although Dampier has not yet suffered from this problem). As for injury, Howard has missed a number of games. He also might have some attitude issues. Certainly Howard has transformed from a very productive player in 2006-07 to a below average player in 2007-08. Much of this decline is related to Howard focusing on taking more shots and capturing substantially fewer rebounds and steals. In sum, Howard is transforming from a great role player to a not-so-great scorer.
Looking at Players
One observation we made in The Wages of Wins is that looking at the players isn’t going to be good enough. You also have to look at the numbers and understand the story the numbers are telling.
Some – in an apparent effort to twist our words — have attempted to argue that we actually said you should never watch the players; all you should do is look at the numbers. In reality, we said watching has an important role. This is what we specifically said on page 125 (of the hard cover version):
One cannot end the analysis when one has measured the value of player performance. Knowing the value of each player is only the starting point of analysis. The next step is determining why the player is productive or unproductive. In our view, this is where coaching should begin. We think we can offer a reasonable measure of a player’s productivity. Although we have offered some insights into why players are productive, ultimately this question can only be answered by additional scrutiny into the construction of a team and the roles a player plays on the floor.
This advice might apply specifically to the Mavericks. We can see how productive these players were in 2007-08. And we can see how productive these players have been in 2008-09. What we cannot say with certainty is why the numbers are so different between each season. And that is where – as we note above – the coaches need to step up.
Clearly one place the coaches need to look is the play of Josh Howard. Kidd, Nowitzki, and Dampier are on pace to 41.8 wins this year. If Howard can return to what he did in 2006-07 – when he produced 10.9 wins – this team can at least gain some ground in the West. If not, then Dallas may be making its first trip to the lottery since 2000.
Let me close by noting that this trip to the lottery might be pre-ordained. Looking at the franchise index over at Basketball-Reference.com I noted an odd fact about the Mavericks. This team has never made the playoffs when a Democrat was President. With a Republican in the White House, though, they made the playoffs in fourteen out of twenty seasons. So if Obama manages to stay in office for eight years, fans of this team should expect a very long drought. That is, if we believe this last set of numbers.
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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.