More NBA spatial data

Adrian the Canadian — my designated Deadspin trawler — sent me an interesting graphic by Kirk Goldsberry and Matt Adams showing the highest percentage shooters from various regions of the court. You might recall that Goldsberry presented similar work at the Sloan Sports Analytics Conference in March (runner up for the research award). My take on this work is that, while interesting and impressive in terms of data, much of the spatial variation in shooting could be explained by factors other than location-specific shooting ability (this will sound familiar if you read my post yesterday on player tracking data).

First, random chance is an issue, especially when trying to identify the best shooters at each location. I think Goldsberry requires a certain number of shots for inclusion at each spot, but he doesn’t do the statistical analysis to determine whether the differences he presents are statistically significant (i.e., large enough such that they are probably not due to chance variation). His big surprise — Rondo leading the league in one mid-range zone — is likely based on a fairly small sample of shots.

Second, defensive position is missing from the analysis. A big red flag for this one is that Durant, at only 40% shooting, leads in the three point zone just to the shooter’s right at the top of the key. Every other three point zone has a guy over 50%. Unless there’s something challenging for right handers about that spot, I’m guessing this is due to differences in shot quality. For example, that may be a common launching pad for right handed guards in the pick and roll, which will often be a contested three. Adrian suggested that shooting guards often end up in that area, especially at the end of the shot clock, and heave up tough, well-guarded shots (Kobe . . .). For some reason, it’s probably uncommon for a well-spaced team to put a guy there for an easy three off a kick out or swing pass.

When and how a player gets the ball might make a difference too (under pressure at the end of the shot clock, off the dribble or from a pass, off a practiced set play or a broken play, etc.). The point is, the differences in field goal percentage that Goldsberry presents could be due to many things, and the strategy implications differ depending on the explanation. I don’t think anyone would tell you to let Ray Allen shoot wide open threes, even though Goldsberry shows he has a very cold area in his paper. And, even after accounting for those factors, remaining differences could just be random chance. We need some error bars on those numbers!

Player tracking in basketball: not a silver bullet

For anyone who follows quantitative sports analysis, player tracking cameras are not news. Along with the NBA, soccer teams use them (even in the MLS) and rugby teams use them. They give x-y-z coordinates for each player at a high frame rate, which can be processed into a variety of statistics. Many think that this approach will revolutionize sports analysis. I stumbled across an article at ESPN today spreading this view to the masses.

Tracking data can help with many things, but it won’t save analysts from themselves. Here’s a point-counterpoint from the article linked above.

Point: “Paul Pierce averaged 4.5 assists this season, which is pretty good for a scoring wing. But that number doesn’t tell the whole story. According to SportVU, Pierce’s teammates shot a higher percentage after his passes than any other player in the NBA. This shows Pierce is passing at the right time — he’s giving his teammates mostly layups and open shots.”

Counterpoint: Pierce might be making great passes, but it’s just as likely that Pierce plays with better than average shooters or better than average cutters/floor spacers, or that Pierce commands a strong defender

Scrabble riddle responses

Last week, I posted a Scrabble riddle posed by my buddy Tony. Here’s the riddle again:

Specify a word that cannot be played under any circumstances in a Scrabble game.

If you still want to take a stab at the riddle, follow the link above to see the complete rules. Now, SPOILER ALERT – answers are below!

Scrabble riddle

This comes from my buddy Tony:

Specify a word that cannot be played under any circumstances in a Scrabble game.

Feel free to look up Scrabble rules if you need a refresher (or ask me). Googling “unplayable Scrabble words” is not allowed, of course. Send your answers to me privately and I’ll post them in a few days — there’s more than one right answer. Also, no words allowed that are clearly excluded by Scrabble rules (proper nouns, foreign words, etc.).

If you’d like to see some of the possible answers, check out the next post.

Why are the hockey playoffs so unpredictable?

The NHL playoffs have many more upsets than the NBA. Adrian the Canadian tells me that this is ruining their product, since the most exciting teams often get unlucky and bow out early. I can’t help but agree — I stopped watching this year after my favorite team (the Red Wings), my local team (the Bruins), and probably the best team (the Penguins) got bounced. The NHL wasn’t always so unpredictable — the Canadiens, Islanders, and Oilers won 13 of 15 cups between 1975-76 and 1989-90. Adrian’s theory is that the the rise of the butterfly goalie has increased save percentages, which makes outcomes more random.

It’s pretty easy to show that increased save percentages do indeed muddy up the result. I generated 1,000 simulated games for three sets of parameters. First, the 1980s (before the butterfly):

• Both teams: 89% save percentage
• Team A: 32 shots per game on average
• Team B: 28 shots per game on average

Then, for the late 90s/early 2000s (butterfly goalies, slightly fewer shots on average perhaps due to popularity of the neutral zone trap):

Time for shootouts to go?

Here’s a fun fact. NHL first round winners were 45-54 in shootouts in the regular season. First round losers were 63-43.  Here are the match ups (higher regular season point total first, shootout record in parentheses, winner in bold):

• Rangers (4-5)  vs. Ottawa (6-4)
• Bruins (9-3) vs. Capitals (4-4)
• Devils (12-4) vs. Panthers (6-11)
• Penguins (9-3) vs. Flyers (4-7)
• Canucks (8-7) vs. Kings (6-9)
• Blues (4-10) vs. Sharks (9-5)
• Blackhawks (7-7) vs. Coyotes (6-10)
• Predators (5-5) vs. Red Wings (9-3)

So, the team with the lower shootout win percentage won seven out of eight series. The team with the higher point total only won four out of eight (Rangers, Blues, and Predators), in part because good shootout records inflated some teams’ point totals. Why do we still have shootouts again?

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.