Category Archives: Research Papers

The Tank Watch (4/27/2012, final edition)

Earlier this spring, my coauthor Chris and I discovered that NBA teams tank a lot, especially teams in the first or second lottery position. This season, I’ve been tracking team performance before and after playoff-eliminated teams locked in to their lottery position. Once teams clinch their spot, there’s no incentive to tank anymore. We found that teams play much better after clinching. Here’s what things look like this year:

The Tank Watch

As I thought a couple weeks ago, the lockout bunched everyone up this year. There just weren’t enough games for teams to separate at the bottom. Only the Bobcats, Wizards, Timberwolves, Trail Blazers, and Bucks clinched their spots before the season ended. This doesn’t mean that teams weren’t tanking (see my post on the Cavs yesterday), but I can’t really test for tanking in a foolproof way. And, comparing pre/post clinch winning percentage doesn’t identify all tankers, since some teams may make personnel decisions that are irreversible (Exhibit A: the Warriors) and others just get so used to losing or are so terrible that motivation fades (Exhibit B: the Bobcats).

The one team that looks like a tank show for sure is the Wizards, who essentially clinched the second lottery spot a week ago, and rattled off five wins to finish the season. While the Wiz were playing all their stars down the stretch (since they had no reason left to lose), their buddies at the bottom (Cavs, Timberwolves, Warriors) were sitting everyone down or trading them. The big outlier of course is the Hornets, who, due to their league ownership, kept Eric Gordon alive and played GREAT down the stretch. At least it only cost them one spot in the end (they finished tied for third), and Hornets fans can be optimistic about next year with Gordon.

Now that we’re done with all that tanking, let’s get on to the NBA’s second season, where all the best players get to play, all the stadiums are full, and all the teams are above average.

Cavaliers, what have you done?

Yesterday, based on my past research with my buddy Chris, I predicted that the Wizards would take it to the Cavaliers last night. The Wizards were already locked into the 2nd lottery position, while the Cavs could still move up or down. Well, I was right. The Cavs looked good to start the game and then slowly faded away.

Our research shows that teams who haven’t clinched play worse than teams that have. In other words, they tank. However, we haven’t determined how they do it. Are players actually trying to lose, or is it all personnel decisions? Last night’s game gave us some evidence for the latter: Continue reading

The Tank Watch (4/17/2012)

‘Tis the season for tanking! Last week, there were six teams eliminated from the playoffs. The Bobcats and Wizards had lost quite a lot already since then, though the Hornets looked surprisingly good. The Hornets continue to look good, but everyone else is bad bad bad, and the ranks of the eliminated have grown. The Bobcats locked in the worst record last night, but it’s hard to imagine them winning any games the rest of the way, so I’m not sure they can be accused of tanking. They are just a terrible team.

The Tank Watch

The Hornets 6-3 record since playoff elimination is largely due to the return of Eric Gordon (they are 4-1 in recent games when he has played). However, would any team other than the LEAGUE OWNED Hornets bring back Eric Gordon Continue reading

Who tanks in the NBA?

Tanking: intentionally losing in order to improve draft position.

After my PhD buddy Chris and I circulated our findings that NBA teams tank a lot, we’ve been asked a few times, “Which teams are tanking?” Today I offer a quick look at teams that have likely tanked.

First, a refresher: we measure tanking by comparing performance before and after playoff-eliminated teams “clinch” their lottery spot. In the last couple games of the season, many teams lock in their spot, so they no longer have an incentive to lose. Those games act as our control. The problem with doing it this way is that some tankers may keep trying to lose even after they clinch their spot. This could happen because teams shut down star players because of “injury” or just because teams develop a habit of losing.

So, the big caveat with the results below (and the results in our paper) is that we are almost certainly missing some tankers. Some teams Continue reading

Optimal drafting

There’s a new paper out this month by Casey Ichniowski and Anne Preston concerning the NCAA tournament and the NBA draft (thanks to my PhD buddies Chris and Felipe for passing it along). Their argument is that unexpectedly strong tournament performance (especially team performance) causes players to be selected earlier in the NBA draft. This isn’t a bad thing though — in fact, they suggest that these strong tournament players tend to outperform their draft position in the NBA.

I believe their results saying that tournament performance affects draft position (this has also been shown by Chaz Thomas in an undergraduate thesis, and by David Berri, Stacey Brook, and Aju Fenn), and I mostly believe their results that strong tourney performers should be drafted even earlier, though their set up is a little odd for this second issue.

The clearest way to show that teams make mistakes in the draft Continue reading

Sloan Sports research rundown

Following on my general analysis of the Sloan Sports Analytics Conference, here’s a look at the research presentations (you’ll note: nothing on the sports side of football or soccer! I submitted one of each but they were rejected . . . ):

An Expected Goals Model for Evaluating NHL Teams and Players (Brian MacDonald)

This paper tries to predict future performance better by incorporating more measurable statistics than past models (goals, shots, blocked shots, missed shots, hits, faceoff %, etc.). His prediction tests show that he makes improvements, and at the team level, I think these results have some value. However, moving to the individual level in a sport like hockey (or basketball, football, soccer, or rugby) is hard because of complementarities between players. For example, trying to measure one player’s contribution to team wins or goal differential based on the number of shots they take is hopelessly confused with the actions of other players on the ice that affect the quality and number of these shots.

Another issue in the paper is that MacDonald controls for team level statistics (such as faceoff win percentage) in the individual level regressions, when in fact much of player value may be driven by these statistics. For example, one of Red Wing Pavel Datsyuk’s strengths is faceoff win percentage, while one of his weaknesses is hitting. The value that individuals bring through these variables is caught up in MacDonald’s team level control variables. Still, the team-level analysis is a reasonable way to improve what’s out there.

Big 2’s and Big 3’s: Analyzing How a Team’s Best Players Complement Each Other (Robert Ayer)

This paper categorizes the top three players on each team Continue reading

Sloan Sports Conference publicity

I spent most of Friday and Saturday at the MIT Sloan Sports Analytics Conference in Boston, checking out other research and discussing my work (with my buddy Chris) on the NBA draft and tanking. Peter Dizikes wrote a nice article for MIT News discussing our project and some of the other work by MIT affiliates. I was also interviewed by a fellow named David Staples from the Edmonton Journal about our project.

David mentions another project on tanking presented at the conference. Adam Gold, who’s a PhD student at the University of Missouri, presented his “solution” for tanking. The proposal: total team wins after playoff elimination should determine draft order. My problem with this: teams that are eliminated sooner have more time to accumulate wins post-elimination, so, rather than race for the overall worst record, teams would race to be eliminated first. I think this would make the problem worse, since teams with low expectations  might give up early in the season, even if these expectations were wrong.

Adam’s response was that no teams will tank early, since they all try to make the playoffs first and foremost. I wish that were true, Continue reading

To tank or not to tank

Last week, I mentioned that my paper with my PhD cohort Chris was accepted for the poster session at the MIT Sloan Sports Analytics Conference. I’ll give the summary and some pictures today (you can find the full paper on my academic website). The project looks at the age old subject of tanking for position in the NBA draft lottery. We answer two questions:

  1. Should teams tank for a better draft position?
  2. How much do teams actually tank?

For the first question, we head right to the lottery. We are interested in the causal effect of obtaining the top pick in the draft. If the first pick is truly valuable, then teams should be willing to lose intentionally to get it. LeBron James, Tim Duncan, and Shaquille O’Neal were all first picks, but so were Greg Oden and Michael Olowokandi. We want the average value of all the first picks since the draft lottery took its current form in 1990.

Since there is some randomness in who wins the lottery, Continue reading

Since the dawn of Linsanity

Since it all began for Jeremy Lin on Saturday, February 4th against the Nets, Jeremy Lin has shot 42-73 from the field (58%!) over four games. Lin’s shooting percentage his senior year at Harvard? 52%. His first four games as the starter for the Knicks are even more anomalous considering that he is only 3-14 from three point range. He shot 60% on two pointers his senior year, compared with 66% over the last four games.

You probably know what’s coming. That’s right, Lin has had a great start to his career, but also a lucky start. Although his performance has transformed the Knicks’ demeanor, don’t expect the insane shooting to continue. Teams will also start backing off on pick and rolls to see if he can reliably make NBA threes. If you still want to jump on the bandwagon, Brother Conor can tell you what to expect.

I also have great news today! One of my submissions to the Sloan Sports Analytics Conference was accepted for the poster session. The paper (available at my academic website, written with Christopher Walters) estimates the causal impact of NBA draft incentives on tanking as well as the causal impact of winning the NBA draft lottery. In short, we find that teams tank a lot — teams that can improve their draft position by losing have lower winning percentages than teams that can’t by about 15 percentage points. There’s good reason for all this tanking. After adjusting for team quality, winning the draft lottery provides a four year attendance boost (though only a small increase in winning percentage). I’ll explain the details in a future post.

Maximizing offensive efficiency

During Kobe’s “hot streak,” I’ve been writing that he’s actually inefficient compared to Andrau Gasnum, the Lakers’ superb tw0-man post presence. I’ve said that he should give up some shots until his efficiency equalizes with Gasnum’s. Adrian the Canadian was quick to send me a Sloan Sports Analytics Conference paper arguing that teams  might equalize offensive efficiency too much already. The author (Brian Skinner) uses some network theory for unknown reasons (it’s not related to his point), but the paper boils down to Continue reading