Mandatory Credit: Tom Szczerbowski-USA TODAY Sports
Thursday the Boston Celtics traded Rajon Rondo to the Dallas Mavericks for Brandan Wright, Jae Crowder, Jameer Nelson, a second round pick and a complicated protected first round pick that most likely will be conveyed in the 2016 draft. The way things work in the NBA is that the trade gets remembered as the trade for the guy that was the biggest star, which can either be measured in All Star appearances, salary, or simply by the ratio of players and assets given up to get him. So, by any sane conventional sense this will be known as the ‘Rondo Trade.’
Advanced Math: .76 > .42
If, however, we take a less sane perspective and look at who as been the most productive player this year, we see that Wright has been the most productive player included in the trade by a number of metrics, in which case this would be known as the ‘Brandan Wright Trade.’ To my mind the best practice is neither to ignore nor rely completely on one number player metrics, but to use them as a starting point, as a sort of Bayesian prior when looking at players or trades.
Pretty clearly every metric rates Wright as the most productive player so far this year, or last year for that matter[1. Via Basketball Reference]:
The Player Tracking Plus Minus (PT-PM) beta model I created agrees too. Below is a chart with the elements that make up the metric and each player’s overall score.[2. Each element is weighted by the coefficients in the model. Scoring weights points minus field goal and free throw attempts and catch and shoot ratio, Passing weights points created by assist and passing efficiency, Offensive Possessions weights contested and uncontested offensive rebounds and turnovers, Rim Protection weights opponents FG% at the rim, number of attempts defended and fouls, and Team Defense weights the defense efficiency rating when the player is on the floor].
Here is where I think things get interesting, along with the more granular breakdowns from the table via Basketball Reference. In the chart one can actually see why Rondo (second bar from the right) is such a polarizing player. He has performed as the best passer in the league by far, but is well below average in retaining offensive possessions, scoring, rim protection and team defense effect.
Wright on the other hand is credited with his incredibly efficient scoring (albeit in low volume), ability to extend offensive possessions ,end defensive possessions and protect the basket. On the other hand his passing numbers and team defense effect on a below average Dallas defense are rated below average.
That, however, isn’t the whole story.
For example, a number of studies, including a couple I have done, as well as common sense [3. Using the assumption that coaches are neither irrational nor without basketball knowledge] indicate that minutes played by NBA players conveys some information about players abilities not captured by box score data. In that case, we need to take note of the fact that Wright has never been a starter or averaged over 19 minutes a game. That is his approximate average with Dallas this year, so, it is worth noting that numbers like total Win Shares and Value Over Replacement Player (VORP), indicate the difference between Rondo’s production this year and Wright’s is less than the per 48 minutes figures. However, my own study indicated that the informational value of time on the court may be log linear rather linear, in other words there is more information increasing a player’s time from a total of 100 minutes over a season to 600, than from 1,100 to 1,600.
There are also interesting questions about whether the basically linear player models can capture the net impact of some one as singularly talented at one aspect of the game as Rondo is at passing. Though the on/off numbers in terms of offensive efficiency for the Celtics teams do not indicate any significant boost with Rondo on the court beyond what the player metrics.
There Will Be Regression
Simple statistical knowledge tells us to expect regression toward the mean for such significant outliers such as Rondo and Wright in terms of scoring efficiency, one of the less stable (though very important!) statistics in basketball. This is by far Rondo’s least efficient scoring performance to date in his career, though, admittedly, the trend has been down for a few years. It is also Wright’s most efficient scoring season so far, another ‘regression’ flag.
Further, my own studies doing win projection models, as well as other studies, have shown that correlation between a player’s box score statistics and efficiency is lower when they change teams; an indication that fit matters. My own projection system apples a small increase in mean regression for players that changed teams in the off season. It should also be noted that Dallas and the San Antonio Spurs are two of the teams that seem to best utilize fit, as well as that player’s who are less efficient and play less are more likely to change teams as well, stars get longer contracts and get traded less.
Discontinuity, Salary, Time Horizon, and Fit
As usual, Zach Lowe does a very good job of laying out the pros and cons in terms of roster fit with Rondo on the Mavericks, which is suggested reading, so I won’t recover that ground.
With Wright there are reasons to adjust our expectations for value added as well. The first of which is that Wright has a similar time horizon mismatch with the Celtics that Rondo did in that he will be a free agent at the end of the year, in which the Celtics do not figure to be anywhere near contenders. For that reason, even if Wright plays as productively as he did in Dallas he may have more value to the Celtics in a trade than as a player likely to walk away at the end of the season. It is really not sane to think of a trade as being about player that stayed with a team for sixty days.
In terms of fit Wright instantly becomes the best rim protector on the team[3. Not a high bar]. His ability to finish the pick-and-roll would have worked nicely with Rondo, but will still be useful especially alongside the Celtic’s stretchy young bigs Kelly Olynyk and Jared Sullinger. On the other hand Wright’s lack of scoring versatility and range, as shown in the shot chart below, will limit Wright’s cumulative effect on the Celtic’s offense and the ability to pair him with similar non-shooting bigs as it did in Dallas.
On the Mavs’ side of the ledger the time horizon is roughly now, or at least while Dirk Nowitski remains a productive player. There are reports that the possibility of an ‘extension’ with Rondo was broached, which is important given that the Mavs are unlikely to have significant cap space this off season, but each side has an out if either fit or Rondo’s play don’t work out.
Ultimately, I think, the degree of discontinuity between Rondo’s peak performance and his post knee surgery will determine the success of the trade for the Mavericks. And only an unforeseen alignment of time horizon and fit with Wright in Boston could genuinely make this the ‘Brandan Wright’ trade even if he has been the more productive player in the last two years.