Subscribe!
Follow me on twitter

The good stuff


At other venues...
  • ESPN.com ($)
  • Deadspin
  • Slate

  • Strategy
  • Whether to foul up 3 late
  • The value of 2-for-1’s

  • Philosophy
  • All points are not created equal
  • Brady Heslip’s non-slump
  • The magic of negative motivation
  • A treatise on plus-minus
  • The preseason AP poll is great
  • The magic of negative motivation
  • The lack of information in close-game performance
  • Why I don’t believe in clutchness*

  • Fun stuff
  • The missing 1-point games
  • Which two teams last lost longest ago?
  • How many first-round picks will Kentucky have?
  • Prepare for the Kobe invasion
  • Predicting John Henson's free throw percentage
  • Can Derrick Williams set the three-point accuracy record?
  • Play-by-play Theater: earliest disqualification
  • Monthly Archives

  • July 2014
  • May 2014
  • April 2014
  • March 2014
  • February 2014
  • January 2014
  • December 2013
  • November 2013
  • October 2013
  • September 2013
  • August 2013
  • July 2013
  • June 2013
  • May 2013
  • April 2013
  • March 2013
  • February 2013
  • January 2013
  • December 2012
  • November 2012
  • October 2012
  • September 2012
  • August 2012
  • July 2012
  • June 2012
  • May 2012
  • April 2012
  • March 2012
  • February 2012
  • January 2012
  • December 2011
  • November 2011
  • October 2011
  • September 2011
  • August 2011
  • July 2011
  • June 2011
  • April 2011
  • March 2011
  • February 2011
  • January 2011
  • December 2010
  • November 2010
  • October 2010
  • August 2010
  • July 2010
  • June 2010
  • May 2010
  • April 2010
  • March 2010
  • February 2010
  • January 2010
  • December 2009
  • November 2009
  • October 2009
  • July 2009
  • February 2009
  • January 2009
  • December 2008
  • November 2008
  • October 2007
  • September 2007
  • July 2007
  • June 2007
  • May 2007
  • April 2007
  • March 2007
  • February 2007
  • January 2007
  • December 2006
  • November 2006
  • October 2006
  • September 2006
  • August 2006
  • July 2006
  • June 2006
  • May 2006
  • April 2006
  • March 2006
  • February 2006
  • January 2006
  • December 2005
  • November 2005
  • October 2005
  • September 2005
  • August 2005
  • July 2005
  • June 2005
  • May 2005
  • April 2005
  • March 2005
  • February 2005
  • January 2005
  • December 2004
  • November 2004
  • October 2004
  • September 2004
  • August 2004
  • July 2004
  • June 2004
  • May 2004
  • April 2004
  • March 2004
  • February 2004
  • January 2004
  • December 2003
  • November 2003

  • RSS feed

    New Digs

    by Ken Pomeroy on Tuesday, August 30, 2005


    Welcome to kenpom.com v2.0! I’ve given this place a little bit of a makeover, including the following:

    - Additional sortable stats for each team, and 2004 stats have been added as well.

    - I hired a highly-respected marketing firm to come up with a new name for the blog, and it paid off big-time.

    - RPI data has been added for 1999. Relive the spectacle that was New Mexico getting an at-large bid while ranked 74th in the RPI.

    - Pomeroy Ratings pages have been standardized back to 1999.

    - More background on what the various tempo-free stats mean, and how they can make your life better. Also, I’m introducing a new free throw multiplier of .475! If you don’t know what that means, don’t worry.

    - The blog is a little “cleaner” and it should be more readable, especially with respect to tables and lists.

    Regular posting…

    Read more...

    Powe-Wow

    by Ken Pomeroy on Wednesday, August 17, 2005


    For those who missed it, the preseason top 50 for the Wooden Award was announced last week. The list isn't binding in any way - someone not on the list can ultimately win the award in March as the nation's best player. It's strictly a publicity stunt, but it's one I welcome at this time of year. It's a great way to get reacquainted with the top talent in the game. Click here for the complete list.

    The preseason list doesn't contain any freshmen and according to a press release, is based on the following criteria...

    The list is composed of 50 student athletes who, based on last year's individual performance and team records, are the early frontrunners for college basketball's most coveted trophy.

    But that statement isn't true for two of the players that made the list.

    One of those is Leon Powe of Cal, who missed all…

    Read more...

    Feeling Lucky?

    by Ken Pomeroy on Tuesday, August 9, 2005


    I did this last year, and looking back on it, it was revealing. You can read last year's editions of the luckiest and unluckiest teams from 2004 and judge for yourself. Just ignore my comments about Florida State.

    If you don't know what the Pythagorean method is, then you'll have to read the 2004 write-ups. All I am doing is subtracting a team's expected winning percentage from its actual conference winning percentage based on its points scored and allowed during conference play. I have decided to rank the teams by winning percentage difference, instead of by win difference. This is so the system is not biased towards conferences that play a lot of conference games.

    These are the teams whose actual conference regular-season record was exceeded by their expected record the most. You could say luck went against these teams the most. The numbers are winning…

    Read more...

    Points Distribution

    by Ken Pomeroy on Monday, August 1, 2005


    The points distribution page illustrates where a team’s (and their opponents’) offense in coming from. The numbers in each column indicate the percentage of points scored (or allowed) by each type of shot. Keep in mind that the numbers on this page do not say anything about the quality of a team’s offense or defense. The data provides another piece of the puzzle of how each team plays offense or defense.


    Read more...

    Four Factors

    The offensive and defensive summary pages are based on Dean Oliver’s four factors concept. You can read Dean’s more detailed explanation of the four factors here. Essentially, the four factors are the building blocks to the efficiency formula.

    Efficiency data gives you an idea of the quality of a team’s offense or defense, but the four factors tell you why a team is good or bad when they have or don’t have the ball. Here’s a breakdown of how each statistic on this page is calculated…

    Effective field goal percentage is like regular field goal percentage except that it gives 50% more credit for made three-pointers.

    eFG%  = (.5*3FGM + FGM) / FGA
    
    

    Turnover percentage is a pace-independent measure of ball security.

    TO% = TO / Possessions
    
    

    Offensive rebounding percentage is a measure of the possible rebounds that are gathered by the offense.

    OR% = OR / (OR + DRopp)
    
    

    Keep in mind that rebounding percentage is computed from box score data which does not contain team rebounds. Therefore, the figures shown here may differ slightly from calculations made on the rebounding totals provided by a school.

    Finally, free throw rate captures a team’s ability to get to the free throw line.

    FTRate = FTA / FGA
    
    

    In Dean’s piece, he mentions the relative importance of each factor. In the NBA, eFG% is easily the most important factor, followed by TO%, OR%, and FTRate. A “RoboScout”-type analysis of games from the 2005 season shows that the importance of each factor is similar in college, with free throw rate being slightly more important in the college game, but still taking a back seat to offensive rebounding. Each team is different though. For instance, Gonzaga’s free throw rate was the second most important contributor to their offensive success. For Michigan State, offensive rebounding ranked second.

     

    Read more...

    RPI Help

    The Ratings Percentage Index (RPI) is the formula used by the NCAA to rate men’s and women’s college basketball teams. The formula is described below.

    The RPI is calculated by adding three parts.

    Part I (25% of the formula): Team winning percentage. For the 2005 season, the NCAA added a bonus/penalty system, where each home win or road loss get multiplied by 0.6 in the winning percentage calculation. A home loss or road win is multiplied by 1.4. Neutral games count as 1.0. More on the effect of these changes can be found here.

    Part II (50%): Average opponents’ winning percentage. To calculate this, you must calculate each opponent’s winning percentage individually and average those figures. This is NOT calculated from the opponents’ combined record. Games involving the team for whom we are calculating the RPI are ignored.

    Part III (25%): Average opponents’ opponents’ winning percentage: Basically taking all…

    Read more...

    College Basketball Data

    The college basketball game file posted on my site is freely available for anyone to use with three requests on my part. (1) Give me some sort of acknowledgment on your site. (2) Let me know you are using the data and why you are using it. I am always curious. (3) While I do not expect you to actively quality control the data, if you do find errors or somebody reports an error to you, please pass it along to me.

    Now a little bit about the format. The home team is listed last. Games not played on a home court are denoted by a letter after the last team’s score. A capital ‘N’ indicates a game played on a neutral court. For a game where the listed home team is not playing on its home court, yet still getting a home court advantage, a lower case ‘n’ is…

    Read more...

    Pomeroy Ratings FAQ

    - Schedule Strength is computed by averaging the rating of each opponent, factoring in home court advantage as appropriate. For schedule strength purposes only, unrated opponents are given a rating of the worst rated team.

    - Data in the ‘LAST 5 GAMES’ column reflects a team’s performance in its last 5 games against rated teams, based on its opponents current ratings, using the same weighting principles that are used to calculate the season ratings.

    What is the purpose of your ratings system?
    This system is designed to be predictive. One can get a prediction by simply taking the difference in the ratings of two teams and make appropriate adjustments for home site advantage. You can probably save some work by looking at individual team pages. There you can find predictions for future games, along with the chances of winning the game outright. Check out this site to monitor…

    Read more...

    Stats Explained

    Let’s start with the most basic stats to measure the ability of a team’s offense and defense.

    Offensive efficiency
    Points scored per 100 offensive possessions.

    Defensive efficiency
    Points allowed per 100 defensive possessions.

    In order to compute efficiency, we need to know how to compute possessions.

    Possessions
    We can estimate possessions very well from box score stats by using this formula.

    FGA-OR+TO+0.475xFTA

    For each team, possessions are counted for the team and their opponents, and then averaged.

    Efficiency gives us broad view of how well the offense or defense functions, but we can break efficiency into what Dean Oliver dubbed the Four Factors. Shooting, rebounding, turnovers, and free throws provide the basic components of efficiency.

    Effective field goal percentage (eFG%)
    (FGM + 0.5*3PM) / FGA

    Shooting is measured by effective field goal percentage, which differs from conventional field goal percentage by taking into account the extra value of a made 3-pointer.

    Offensive rebounding percentage
    OR / (OR + DR)

    Defensive rebounding percentage can also be computed, using defensive rebounds in the numerator.

    Turnover percentage
    TO / Possessions

    Free throw rate
    This can either be FTM/FGA or FTA/FGA. Typically, for team offense FTM/FGA is used, while on defense FTA/FGA is used. This is FTA/FGA for both offense and defense.

    There are other team stats that are less important than the Four Factors, with the common approach of converting the standard per-game stats to per-opportunity.

    Assist Rate
    A / FGM

    Block Rate
    Blocked shots / Opp. 2PA

    Steal Rate
    Steals / Defensive possessions

    All of the above stats can apply to individuals in some form, also. There are two other stats that are applied to individuals that aren’t applied to teams. These stats were developed by Dean Oliver, and the formulas are far too complicated to list here. His book, Basketball on Paper, is worth buying if you are interested in how the calculations are performed.

    Offensive Rating
    This is the personal version of team offensive efficiency.

    Usage (% of possessions used)
    This describes a player’s role in the offense, by explaining how many of his team’s possessions a player is personally responsible for ending while he is on the floor.

    A simpler version of personal efficiency is this one

    True shooting percentage (TS%)

    Points scored / ( 2* (FGA + 0.475*FTA) )

    Read more...

    Basketball Shrink

    The Basketball Shrink finds teams most similar to the team you selected, based on the stats on the page you are looking at. On the summary page, teams are compared by adjusted tempo, adjusted offensive efficiency, and adjusted defensive efficiency. On the other stats pages teams are compared by all the stats listed on the page. The algorithm takes the sum of the percentage difference of each stat and ranks the teams accordingly.

    I call this the Basketball Shrink because it’s designed to give the user an idea of the personality of a team by producing a list of teams that play a similar style. For more information, here is my original post on the Shrink from the 2005 season: Basketball Shrink Debuts.


    Read more...