Feb 4 2009

Ranking Net Efficiency Ratings

I’ve been lucky enough to take part in an independent study with my advisor this semester, where I study various methods for ranking things, like sports teams. Our specific area of application is the NCAA tournament, but these methods can be used for much more.

My main interest is in how to apply ranking methods to various NBA statistics at the team, unit, and player level. I am initially focusing on ranking various team statistics such as efficiency, rebounding%, shooting% from various spots on the court, TOs per possession, etc. Over time I will make the daily ratings available in a stats section on this website, but for now I’ll just post the results as I get the rankings together.

My first application is to net efficiency ratings, where a team’s net efficiency rating is their offensive points per 100 possessions – defensive points per 100 possessions.

To rank and rate the team’s net efficiency ratings, I have used Kenneth Massey’s linear regression method outlined in his paper Statistical Models Applied to the Rating of Sports Teams.

The implementation I used adjusts for the team’s strength of schedule and measures home court advantage. As of this writing, the home court advantage was measured to be worth 3.20 points per 100 possessions.

The Ratings

The chart below shows each team’s adjusted net efficiency rating next to their actual net efficiency rating (unadjusted). The usefulness of this is debatable, as the differences between the adjusted and unadjusted ratings is fairly small. There are some switches in rank here and there (such as ORL over LAL), but the conclusions you draw about the teams based on their adjusted versus unadjusted ratings aren’t likely to change much.

Rank Team





Rank Team





1 CLE 10.91 11.56 16 MIL 0.43 0.37
2 BOS 10.07 10.77 17 DET -0.79 -0.10
3 ORL 7.69 8.16 18 IND -1.09 -2.12
4 LAL 7.58 8.81 19 TOR -1.87 -2.46
5 POR 4.19 4.14 20 CHA -2.28 -2.77
6 NOH 3.62 3.60 21 NYK -2.52 -2.50
7 DEN 3.58 3.83 22 CHI -2.59 -2.85
8 HOU 2.95 3.21 23 MIN -3.13 -2.98
9 SAS 2.51 3.59 24 GSW -4.36 -4.56
10 PHX 1.87 2.21 25 NJN -4.80 -3.80
11 UTA 1.78 2.88 26 OKC -7.03 -6.27
12 ATL 1.47 1.80 27 WAS -7.40 -8.34
13 PHI 0.99 0.77 28 MEM -7.94 -7.07
14 DAL 0.84 1.21 29 LAC -8.70 -8.91
15 MIA 0.45 1.08 30 SAC -9.62 -10.22

Making Predictions

This method assumes each possession deserves equal weight. If we assume that this is a fair way to rate a team’s net efficiency for future predictions, then we can make predictions with the following formula:

margin = home team rating + home court advantage – away team rating

Where margin is the net number of points we expect the home team to win by per 100 possessions played. So if Cleveland is hosting the Celtics, we expect Cleveland’s margin to be 10.91 + 3.20 – 10.07 = 4.07 points per 100 possessions. If Boston is instead hosting the Cavs, then we expect Boston’s margin to be 10.07 + 3.20 – 10.91 = 2.36 points per 100 possessions.


These ratings give us a better sense of a team’s actual net effeciency rating with respect to the entire league, but as you can see from the chart the differences are, in most cases, not that large and have only a small impact on the actual rank of each team.

4 Comments on this post


  1. Predicting Team Rebounding Rates wrote:

    […] we saw in my post on ranking net efficiency ratings, we don’t gain a lot of information by ranking NBA efficiency ratings at the team level. In […]

    February 10th, 2009 at 1:16 pm

  1. Gabe said:

    Unless I missed it, can you explain how you do your adjustment? In other words, what is making the difference between the adjusted and unadjusted?

    February 4th, 2009 at 1:12 pm
  2. Ryan said:

    You can see Massey’s paper for the details (linked above), but it’s his least squares method that measures the ratings based on who the team has played and holds for home court advantage with the constraint that the ratings sum to 0.

    So to answer the question “what is making the difference between the adjusted and unadjusted”: it is the fitting of the equations that incorporate the team vs. team matchups with the addition of the home court advantage.

    Let me know if that doesn’t answer your question.

    February 4th, 2009 at 1:30 pm
  3. Tony said:

    I was actually wondering how the Home court advantage for each team is calculated. What does the formula to calculate home court advantage include?

    March 20th, 2010 at 6:37 pm

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