May 31st, 2009 by Jon Nichols

Below are links to some of the statistics I’ve created:

2008-09 Composite Score, PAC, and Value Rating

2003-08 Composite Score


Explanation of Composite Score
May 30th, 2009 by Jon Nichols

The Composite Score rating system consists of two components, Offensive Composite Score (OCS) and Defensive Composite Score (DCS).  Each is made up of a combination of three advanced statistical metrics and then adjusted based on a player’s position and playing time.  The rating system is always under construction, so the system used today may not be as good as one you could see in a few weeks.

First, let me explain OCS.  It is a combination of three statistics: the Offensive rating system developed by Dean Oliver (which can be found at basketball-reference.com), PER production (found on the team pages at 82games.com), and offensive plus-minus, found at basketballvalue.com. I then adjust offensive rating and PER production for position. Next, I add up the three z-scores for the three stats for each player and multiply them by 10. After adjusting for playing time (whether or not most of it is against starters or benchwarmers), Offensive Composite Score is complete.

Offensive ratings are an incredible measure of efficiency. PER also measures efficiency but takes into account players with higher usage rates. +/- is a great indicator of how well a player is fitting into his team and helping them offensively.

The average score is set at 0.

  • -40 and below: Terrible
  • -40 to -20: Very bad
  • -20 to 0: Below average
  • 0 to 20: Above average
  • 20 to 40: Very good
  • 40+: Elite

Player rank percentiles were also included to get a relative value of each player.

Next is an explanation of DCS.  DCS uses the mirror statistics of the three used for OCS.  Instead of Offensive rating, it uses a very similar Defensive rating.  Instead of PER, it uses counterpart PER, which is basically the PER accumulated by a player’s defensive matchups.  Finally, instead of offensive plus-minus, I use defensive plus-minus.  The scores are on the same scale as OCS.

Composite Score (CS) is a combination of OCS and DCS.

Counterpart PER, and PER were found at 82games.com. PER, or Player Efficiency Rating, was developed by John Hollinger.  Offensive and defensive ratings, which were developed by Dean Oliver, were obtained from basketball-reference.com. Plus-minus can be found at basketballvalue.com and 82games.com.  Player names and positions were obtained from dougstats.com. I used an adjustment for starters based on the formula developed at the APBRmetrics message board (http://sonicscentral.com/apbrmetrics/index.php).

Glossary of terms on stats pages:

OCS – Offensive Composite Score
OCS Rank – How a player ranks offensively among all the players in the league that qualify (at least 500 minutes played)
DCS – Defensive Composite Score
DCS Rank – How a player ranks defensively among all the players in the league that qualify
CS – Composite Score (OCS + DCS)
CS Rank – How a player ranks overall among all the players in the league that qualify

Tips for Interpreting Composite Score Rankings

  • Take everything with a grain of salt. It may be weird hearing that coming from me, but it’s true. If a player is ranked too high or too low in your opinion, try to think about why that is. Does he play on a really good team that inflates his numbers? Does he constantly draw the toughest defensive assignment, making his defense look bad? Instead of dismissing the numbers, try to think of why they are the way they are.
  • Look at a player’s general range of ranks, not the specific number. If a player is ranked 10th, for example, I may not think he’s actually the 10th best player in the league. However, I do think he’s better than a guy ranked 50th. As always, think of the numbers as guidelines, and not as absolute fact.
  • Don’t try to compare players based on their rankings. This is related to the last point. Because these numbers are an inexact science, and because the difference between two players is often extremely small, don’t think that a player ranked 7th is automatically better than a player ranked 8th. It may be fun to discuss it that way, but it’s not the best way to look at Composite Score.
  • Use supporting evidence. Look at my numbers, but also look at other advanced stats as well. Looking at all the numbers will give you a better overall picture of what stats say about a certain player.
Explanation of PAC
May 29th, 2009 by Jon Nichols

As you look through my Position-Adjusted Classification system, you may have some questions.  How does it all work?  What numbers do you use?  How is the classification calculated?  How dare you call my favorite player that?  This guide is here to help.

First of all, let’s explain what PAC is.  It is a player classification system that uses four advanced statistics to divide players into 48 different categories.  The statistics I use are: Pure Point Rating (explanation here:Link), jump shot percentage, free throw attempts divided by field goal attempts, and Rebound Rate.  Pure Point Rating basically compares a player’s assists to turnovers, but in a more accurate and complex way than you’re probably used to.  Jump shot percentage is the amount of shots a player takes that are taken from the perimeter (not necessarily three-pointers).  Rebound Rate is the percentage of rebounds a player gathers while he is on the floor.

Once I have those numbers for every player, I adjust them for position.  Then, using a formula I have developed, I determine if a player is especially strong or weak in each of those categories.  Each combination gets a different classification, for a total of 16 combinations.  The names of the combinations are:

Perimeter Scorer
Perimeter Player Who Can Rebound
Ball-Handler with Range
Skilled and Strong
Inside Scoring Ball-Handler
Rebounder With Skill
Scorer Who Can Rebound
Rebounder With Range
Outside Shooter
Inside Scorer

I won’t get into explaining which combination leads to each category, but I’ve tried to make them as self-explanatory as possible.  When in doubt, check other players that qualify for that same category to get a list of similar players (if you’re wondering, there’s only one All-Around player and that’s Kobe Bryant).

The 16 categories turn into 48 when I add Usage Rate, a number that measures how many of a team’s possessions that a player uses.  Each player can have a high, medium, or low usage rate.

Player names, positions, and free throw rates were obtained from DougStats.com.  I obtained the Pure Point Rating, Rebound Rate, and Usage Rate data from the KnickerBlogger.net stats page.  Jump shot percentages were obtained from 82games.com.


  • PAC is based on position.  Chris Paul may not seem that strong, but for a point guard he is.
  • The numbers are based on this current season.  Therefore it’s not a full 82 games worth of a sample size, so things could change as the season progresses.
  • PAC reflects a player’s style, not quality, of play.  Just because two players fit under the same category doesn’t mean they’re of equal ability.  In fact, the two usually have nothing to do with each other.
  • This is still a work in progress.  It’s my first go at this, so there may be some minor flaws.  If you have any suggestions, e-mail me at [email protected].
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