Consistency: The One Thing The Nets Are Good At? Part 1 of a Series.

By David Roher

A Model of Consistency.

Consistency is funny. We usually consider it a good thing to have, and we remember prolonged, steady excellence for a long time. Joe DiMaggio’s 56-game hit streak. Cal Ripken’s 2,632 consecutive games. Oscar Robertson’s 1962-season-average triple-double. Takeru Kobayashi’s winning the Nathan’s Hot Dog Eating Contest for six years in a row.

But there’s nothing about consistency that is inherently good. It just means that there’s a continued production of results that are all similar to each other, which says absolutely nothing about the quality of those results. There are plenty of things that are consistently terrible, like three-week-old sushi and the Los Angeles Clippers. On the blog, we’ve been pretty consistently ignoring anything about basketball. That’s another bad thing, and something I’ve decided to change with this series. Where better to start than the New Jersey Nets?

The motivation for the series was the fantastically dreadful manner in which the Nets opened their 2009-10 season, losing their first eighteen games. As they proved in game #19, however, they’re not a bad enough team to lose every single time they step on the floor. In fact, according to John Hollinger’s current Power Rankings, they’re not even the worst team in the league. Even during their 18 Games That Shook the World, the Nets’ points scored and allowed dictated that they should have won 2 or 3 (through their Pythagorean Expectation, a method of estimating record based on runs/points/goals).

Luck, or lack thereof, was probably the greatest cause of their streak. But it got me thinking: was there something about the Nets, other than simply their inability to play quality basketball, that enabled them to provide us with such a shining beacon of ineptitude? Perhaps, I thought, it had to do with their consistency.

Let’s say a team scores 80 and allows 130 points per game, which would likely make them the worst team in history, worse than the Nets could ever dream of being. Their Pythagorean winning percentage would be just .001. But couldn’t the way in which they achieved those averages give them a drastically different result? For example, this team never scores less than 75 or more than 85. However, it allows 70 or 190 points per game, depending on whether it was home or away (this team really loves its fans), which means they win every single home game, giving them a winning percentage of .500. Nothing in this example would ever happen to that degree in real life, but hopefully through the exaggeration you can see the possibility of it happening in reality to a lesser effect.

Maybe the Nets, by staying close to their atrocious averages, were more likely to go on a winless streak. To address that question properly, however, we’ll have to dig a lot deeper into the consistency question. I’ve compiled, through the use of our own Dan Yamins’ aggregated game-by-game results, a consistency index for every team since the start of the NBA in 1950. It’s simply a measure of the standard deviation of each team’s game-by-game point totals. The analysis of the data will come in the next installments (including adjustments for differences in average point totals, games per season, etc.) but just to give you a sneak peek, here are some of the results:

Most Consistent Offenses since 1950 (Team, SD of Points Scored per Game)

1999 Miami Heat, 6.74 (Lockout year)
1986 Detroit Pistons, 8.09
1954 Milwaukee Hawks, 8.40 (Shorter season)
1975 Philadelphia 76ers, 8.40
1994 Minnesota Timberwolves, 8.62

Least Consistent Offenses

1950 Sheboygan Red Skins, 15.75 (Shorter season)
1951 Fort Wayne Pistons, 14.99 (Ditto)
1984 Denver Nuggets, 14.78
2007 Washington Wizards, 14.72
1991 Houston Rockets, 14.58

Most Consistent Defenses

1999 Sacramento Kings 7.69 (Lockout year)
2001 Miami Heat, 8.68
2002 Miami Heat, 8.79
1964 St. Louis Hawks, 8.81
2007 Atlanta Hawks, 8.83

Least Consistent Defenses

2008 Toronto Raptors, 15.53
1984 Denver Nuggers, 15.52
1993 Philadelphia 76ers, 15.50
1950 Denver Nuggets, 15.42 (Shorter season)
1951 Fort Wayne Pistons, 14.97

Over the next few posts, I’ll be looking at these numbers further, determining both their causes and possible effects. Stay tuned.

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7 Responses to Consistency: The One Thing The Nets Are Good At? Part 1 of a Series.

  1. dadler3 says:

    I’m excited to see what you have on tap next.

    I presume you’re familiar with the work on standard deviation of runs and Pythagorean expectation in baseball. I remember reading a terrific article about it this summer, but I can’t find it right now. From what I recall, it talked about how scoring consistently can lead to fewer “wasted” runs.

    If you have an average of 6 runs per game, but score 12 50% of the time and 0 50% of the time, that would be much worse than scoring 6 all the time…scoring 12 is not much better than scoring 6 (usually a win in both cases) while scoring 6 is a ton better than scoring 0 (usually a win vs. a sure loss). I don’t totally recall the article, but by that definition, I would imagine that being consistent in runs scored and inconsistent in runs allowed, you could outperform your Pythagorean expectation.

    This article touches on some of the issues:

    http://www.hardballtimes.com/main/article/outsmarting-pythagoras/

    Looking forward to seeing how things look in basketball (and hoping someone can find that article I’m talking about).

    • David Roher says:

      Given the work that’s been done on the subject I had figured someone had done something similar, but I hadn’t found anything. I’d be very interested in reading that article as it’ll probably shape where I go from here.

    • E says:

      dadler- I agree with what you state regarding your example, but I don’t think that your conclusion (that [by] being consistent in runs scored and inconsistent in runs allowed, you could outperform your Pythagorean expectation) holds up. (Admittedly, I haven’t read the article.)

      The team in your example is an excellent offensive team, scoring 6 runs per game. In that case, consistency would be beneficial. But consider a team that averages only 2 runs per game … if they score 4 50% of the time and 0 50% of the time, that would be much BETTER than scoring 2 all the time…scoring 2 is not much better than scoring 0 (usually a loss in both cases) while scoring 4 is a lot better than scoring 2 (more likely a win vs. a very likely loss).

      I think the better hypothesis would be that if a team is above average in scoring, it is better to be consistent, but if it below average in scoring, it is better to be inconsistent. The same would hold true for points/runs allowed.

  2. tgt says:

    Are you planning on factoring in pace to your calculations? A 95-90 game on 100 posessions is essentially the same as a 142 – 135 game on 150 possessions, but they would have very different effects on your measure of offensive and defensive consistency.

    Deviation of pace itself might also need to be factored in.

    • David Roher says:

      Yeah, I was. The problem is that all I have is points scored on a game-by-game level, not number of possessions. So I couldn’t do deviation of pace right now, although that’d be very interesting in itself.

  3. Kevin Pelton says:

    Dean Oliver has done some great work on consistency in basketball, both in Basketball on Paper and online here:

    http://www.rawbw.com/~deano/articles/BellCurve.html

    (The ancient Java applets cut off the text, but you can read what is below the second set by viewing the page source.)

    • David Roher says:

      Thanks for coming over here, Kevin. Big fan of the work you guys do.

      I had come across the Basketball on Paper chapters as I was writing the article – on the one hand I was disappointed to see that there was already some ground on the issue, but the work he’s done is pretty amazing. An old article he wrote about Princeton’s strategy also ties into this.

      Right now I have to deal with a couple finals, but I’m going to get cracking on the data by Tuesday at the latest. There’s still a lot of interesting stuff to be done with it.

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