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TPS Reports: Paint Presence, Perimeter Threats, and Super-Efficiency
Oct 3rd, 2009 by Jon Nichols

Last time I introduced my TPS (Talent Plus Style) system and a basic statistic using that system called Playmaker Score.  Today I’ll show a couple more statistics I’ve developed using TPS.

The first rating is something I called Paint Presence Rating.  Before I go any further, remember that all ratings are adjusted for position, so some point guards rate higher than centers, even though they are obviously not greater “paint presences.”  Paint Presence Rating is determined by a player’s Composite Score, Close Attempt Percentage, Close True Shot Percentage, free throws/field goal attempts, and Rebound Rating.  Composite Score reflects a player’s all-around ability while the other four are all affected by a player’s skills/tendencies around the basket.

The second rating is Perimeter Threat Rating.  This rating reflects a player’s tendency to shoot three-pointers and his ability to make them.  It consists of three components: Composite Score, Three-Point Attempt Percentage, and Three-Point True Shot Percentage.

The third and final rating I will release today is called Super-Efficient Rating (it sounds silly, I know).  It incorporates three elements: Offensive Rating, True Shot Percentage, and Turnover Rate.  Offensive Rating is a good catch-all for every efficient thing a player can do offensively, while the latter two measure a player’s ability to hit shots when he needs to and not turn the ball over.  Things such as assists and offensive rebounds are also part of offensive efficiency, but they are only partly incorporated, through the use of Offensive Rating.

To see all the numbers, go to: Link.

A New Method for Evaluating Players, Part II: Explanation of TPS
Sep 30th, 2009 by Jon Nichols

As I alluded to in my last post, something I’ve wanted to do for a long time was to make a player rating system that is totally customizable.  Every team has different needs at different times, so the one-number-fits-all style of player rating systems, which has been the norm, seems inappropriate in certain situations.  Today I would like to explain to you something I’ve created called the TPS (Talent Plus Style) player rating system (movie reference: when I produce TPS reports in the future, just know that I did see the memo and I won’t forget to include the new cover sheet).

Why TPS?  As I said in my last article:

Let’s say Shaquille O’Neal rates better than Rashard Lewis in Player Rating System X.  The Magic should try to swap Lewis for Shaq, then, right?  Obviously not.  Orlando needs a big man (calling Lewis “big” is a stretch, but go along with it for now) that can stretch the floor and give space for Dwight Howard down low.  Suddenly, we’re doing so much contextual research for Player Rating System X that the player rating itself isn’t that useful anymore.  Instead, we’re relying on shooting percentages, shooting tendencies, rebounding ability, defensive ability, etc.

Having the flexibility to specify what you are looking for in particular from a player makes things easier for talent evaluators and more fun for fans.  There are a couple of things about TPS that make it very useful:

  • Every variation of TPS ratings is adjusted for position.  A center who can shoot three-pointers at the league average is much more valuable than a shooting guard with the same efficiency.  Likewise, a point guard with a league average rebounding rate is probably pretty good in that respect.  Not only does adjusting for position level the playing field, but it also makes it easier to find players who are unconventionally good at things.
  • TPS can include my original Composite Score rating system if desired.  As you may or may not recall, Composite Score is a combination of the Offensive/Defensive Ratings developed by Dean Oliver, PER /counterpart PER, and offensive/defensive plus-minus.  Additionally, if you only like some of those components, you can pick and choose which ones to include.  Composite Score often serves as a base for many of the ratings I develop when I’m playing around with TPS.  It provides a nice “all-around” measure for players so that even when you want to focus on specific skills, you don’t ignore everything else that occurs on a basketball court.
  • There are literally an infinite number of possibilities for how you can rate players.  Up to 25 different variables can be included, and each can be assigned a different weight, depending on what’s important.
  • Every variable is adjusted either per-minute or per-shot-attempt.  Players who perform admirably despite limited playing time will still rate well.

Which variables can be included in TPS player ratings?  They can be broken down into three categories:

Composite Score Stats:

  • Composite Score
  • Offensive Composite Score
  • Defensive Composite Score
  • Offensive Rating
  • PER
  • Offensive Plus-Minus
  • Defensive Rating
  • Counterpart PER
  • Defensive Plus-Minus

Shooting Stats:

  • Close Attempt Percentage (=close attempts/total shot attempts)
  • Close True Shot Percentage
  • Midrange and Post Attempt Percentage (=midrange and post attempts/total shot attempts)
  • Midrange and Post True Shot Percentage
  • Three-Point Attempt Percentage (=three-point attempts/total shot attempts)
  • Three-Point True Shot Percentage
  • Fouled Attempt Percentage (=fouled shot attempts/total shot attempts)
  • Fouled True Shot Percentage
  • Assisted Rate (=assisted field goals/total made field goals)

Other Advanced Stats:

  • True Shot Percentage
  • Free Throws/Field Goal Attempts
  • Pure Point Rating
  • Assist Rate
  • Turnover Rate
  • Rebound Rate
  • Usage Rate

As you can see, I did not develop all of these statistics (for some I just adjusted them for position and use them as components in my ratings).  Offensive and Defensive Ratings were developed by Dean Oliver and can be found at Basketball-Reference.com.  PER and many of the other advanced stats were developed by John Hollinger.  I used Basketball-Reference and Knickerblogger.net to gather these.  For player names and teams, I used Dougstats.com.  For positions, plus-minus, and Counterpart PER, I used 82games.com.  Additionally, although I calculated the shooting stats myself, similar numbers can be found at 82games.  To calculate the shooting stats, I used the play-by-play data available at BasketballValue.com.

The ratings I have come up with so far are all based on a 0-100 scale, with 50 being average.  Remember that these ratings are adjusted for position, so a player with a 50 is average for his position.

To give an example of what TPS can do, I have created a rating called Playmaker Score.  This number rates players on all of their abilities, but especially their ability to create shots for others.  It considers a player’s Composite Score, Assisted Rate, Pure Point Rating, and Assist Rate (remember that Assisted Rate measures how many of a player’s shots were assisted by others while Assist Rate estimates how many of teammates’ field goals an individual player assists on).  To see the numbers, go to:

Link

This is just one rating that I threw together pretty quickly.  Still, it gives some interesting results and shows what TPS is capable of doing.  Over the next few weeks, I will come out with some similar player ratings using TPS.  If you have any questions or suggestions, feel free to comment below.

P.S. If you’re wondering what movie I referenced earlier, check out: Link to video

A New Method for Evaluating Players, Part I: Rating Shooting Abilities
Sep 25th, 2009 by Jon Nichols

One concern that many people have is that player rating systems are often too general.  I’ll be the first to tell you my Composite Score rating system needs a bunch of contextual information to truly be useful.  It’s simply too hard to sum up all of a player’s abilities with a single number.  One major problem is all the things that go unmeasured, although that’s outside the scope of our abilities until we start tracking new things.

A second major problem, one that I’m trying to find a solution for, is that different teams have different needs for different situations.  Let’s say Shaquille O’Neal rates better than Rashard Lewis in Player Rating System X.  The Magic should try to swap Lewis for Shaq, then, right?  Obviously not.  Orlando needs a big man (calling Lewis “big” is a stretch, but go along with it for now) that can stretch the floor and give space for Dwight Howard down low.  Suddenly, we’re doing so much contextual research for Player Rating System X that the player rating itself isn’t that useful anymore.  Instead, we’re relying on shooting percentages, shooting tendencies, rebounding ability, defensive ability, etc.

It still would be nice to have one number when we’re trying to evaluate players, if for no other reason than to save time.  But we’ve already proven that one number is useless without context.  What can we do?

Create multiple sets of player ratings.  Better yet, create an organic player rating system that adjusts based on whatever is important to us at the moment.  The Magic need a power forward that can shoot three-pointers efficiently and create his own shot from time to time?  Ok, let’s rate power forwards based on that.

The next step is to calculate all of those little components and adjust them by position.  Why adjust for position?  If we made a player rating system based on three-point shooting ability and shot-creation alone, without adjusting for position, our numbers would tell us the Magic should acquire someone like Roger Mason and put him at power forward.  That doesn’t seem like a wise suggestion.

Once we have all the position-adjusted components, we can then decide which are important based on our needs.  Today is the first step.  Similar to how I broke down individual players by quarter, each player in the league will be rated based on how he performs from four shooting locations: close (dunks and layups), midrange (including post shots), three-pointers, and getting to the free throw line.  Each rating is adjusted for position, so a center with a 90 rating on three-pointers is still very likely worse overall than a shooting guard with an 80.

The ratings will combine both frequency and efficiency.  In other words, if a player rarely shoots from midrange but is efficient at it, he won’t rate that well.  Similarly, if he shoots from midrange all the time but is highly inefficient, he also won’t rate well.  Ratings are on a scale of 1 to 100, with 50 being average for that position.

Frequency is measured by the player’s attempts from that shot location divided by his total attempts.  Efficiency is measured by his makes divided by his total attempts from that location.  The only situation that is included in this efficiency measure is when a shot actually goes up, so things like turnovers are ignored.

Before I release the numbers, I should say that these shooting tendencies and efficiencies are nothing new.  82games.com has had this data available for a while now.  My methods for extracting these tendencies and efficiencies from the play-by-play data are slightly different, but they are similar.  The new step I am taking is adjusting these numbers by position and creating a rating system off of these adjustments.  The numbers are available through Google Docs below:

http://spreadsheets.google.com/ccc?key=0AvNKNGJ_AHijdE5RWnZVcG9vS1VaQ1B5VFdBZG5tMHc&hl=en

If you’re angry because a certain player does not rate the way you’d expect, allow me to explain.  First, remember these ratings account for efficiency.  Superstars may be excellent shot producers (a skill I will rate in the near future), but they are not always the most efficient.  Second, these ratings also account for a player’s tendencies.  If a player is extremely likely to take a certain shot, his rating will be high for that.  However, if he balances his shot attempts, he will not rate extremely high in any of them.

A simple way to look at it is that these ratings are attempting to describe players as much as they are attempting to evaluate them.  LeBron James may only get an 80 in close shots (which is still quite high), but that’s because he mixes up his attempts.  He clearly is one of the most frightening players in the world when he’s near the basket.

These ratings do evaluate to an extent, but the bulk of evaluation for my new rating system will come from other components.  Shooting ratings will be a big part of the context I mentioned at the beginning of this article.

This is just a first run, so changes will inevitably be made.  If you have any suggestions, feel free to comment below.

Banks, Hooks, and Fades Article Fixed
Aug 6th, 2009 by Jon Nichols

Just a quick note: some of you may have had trouble viewing the tables on the Banks, Hooks, and Fades article.  The article is fixed now.  My apologies.

-Jon Nichols

Welcome to the New Basketball-Statistics.com!
Jul 28th, 2009 by Jon Nichols

Hello, and welcome to the new Basketball-Statistics.com.  It’s a new, cleaner, simpler look.  Everything on the old Basketball-Statistics.com is still available to be viewed.  For the archives of every major article I’ve written since 2006, click on All Articles.  To see my Composite Score, PAC, and Value Rating statistics, click on Stats.  My newest research is also available by clicking on one of the categories to the left.

I hope you enjoy the new layout.  If you find any bugs or can’t find an article you’re looking for, feel free to comment in this post or send an e-mail to jonnichols@basketball-statistics.com.

-Jon Nichols

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