20th April 2010

As if everyone isn't already tired of this debate (one which will never be satisfactorily settled, I'm sure), here's a final note on who contributed the most to the 1995 Rockets' offense during the playoffs, Hakeem Olajuwon (mega-high usage, average efficiency) or Clyde Drexler (mid-to-high usage, mega-high efficiency)...
My last post attempted to create a simple model of team offensive efficiency using Dean Oliver's Offensive Rating, Possession %, and what Dean called "Skill Curves", or the relationship between changes in individual usage and efficiency rates. In general, both Oliver and Eli Witus found a quantifiable inverse relationship between increases in usage and predicted offensive efficiency -- in other words, there's diminishing returns to increasing your usage, and as you add more usage you become less and less efficient (which only makes sense to anyone who's ever played basketball).
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Posted in Analysis, History, Statgeekery, Statistical +/- | 51 Comments »
19th April 2010

Over in the comments of an earlier post about the 1990s Knicks, a discussion is raging about who the best player on the 1995 Houston Rockets was -- Hakeem Olajuwon, or his old college teammate Clyde Drexler? At the core of the back-and-forth is whether Drexler's 120.1 offensive rating (using 23.8% of Houston's possessions when on the court) was more vital to the offense than Hakeem's 109.8 ORtg (using 34.1% of possessions when in the game)... In other words, the old usage-efficiency debate. On one side, Drexler clearly contributed more points per possession to the Rockets' effort than Olajuwon -- but on the other side, Hakeem had to create offense on a significantly higher % of the Rockets' possessions than Clyde, and if you subscribe to "skill curve" theory, this means Clyde's ORtg was artificially enhanced by the extra defensive attention Hakeem drew -- as well as the fact that his shot selection didn't have to include the offense's toughest shots, which were presumably going to Hakeem (at least in a larger proportion), in turn dragging down Hakeem's ORtg.
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Posted in Analysis, History, Statgeekery | 17 Comments »
16th April 2010
Playoffs Home ▪ 2010 Playoff Previews
On the eve of the 2010 Playoffs, I thought it'd be cool to run down the current list of winningest NBA "people" -- players and coaches. We know which coaches coached which games, so we can give them accurate credit for W-L records, but if you recall for players, we have to estimate the team's W-L record for games in which they appeared. Fortunately, this is pretty easy and a pretty decent kludge: take the team's winning percentage in all games (in this case, all playoff games in a season) and multiply by the player's games played for wins, then subtract that from his games for losses. This isn't perfect, but in the absence of pre-1991 playoff gamelogs, it's the best we can do (and it's pretty darned accurate for such a simple solution). With the explanation out of the way, here are the winningest playoff "people" of all time:
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Posted in Data Dump, History, Playoffs, Statgeekery | 5 Comments »
6th April 2010
The other day I decided to check out the Most Improved Player (MIP) list on ESPN.com's NBA Awards Watch. Before visiting the page I figured that Kevin Durant would be at the top of the list, as Durant has made a stratospheric leap this season, going from at best an average player to one of the top five players in the NBA. Imagine my surprise when I saw Durant in the second spot on this list, behind Aaron Brooks of the Houston Rockets. In my mind I knew that this had to be wrong, that Durant's improvement was the most improbable performance of the season, but I needed a way to quantify it. The question is: How? Let's go to the data...
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Posted in Awards, Statgeekery | 31 Comments »
6th April 2010
Note: This post was originally published at College Basketball Reference, S-R's brand-new College Hoops site, so when you're done reading, go over and check it out!
Prior to the 2010 tournament, many media pundits felt that Duke had the easiest bracket of any #1 seed, despite Kansas actually being the top overall seed in the field. If no upsets happened, Duke would have to go through AP #9 Villanova to reach the Final Four; by comparison, Kansas would have to go through #5 Ohio State, Syracuse would have to go through #7 K-State, and Kentucky would have to go through #6 West Virginia.
As the tournament progressed, the only upset that happened along Duke's path was #3 Baylor reaching the Regional Final instead of Villanova, who had been picked off by Saint Mary's (CA). This meant that instead of #9 'Nova, Duke actually only had to go through the 19th-ranked Bears to reach Indy. Once they reached the Final Four, they found #6 West Virginia waiting for them, and in the Championship Game the Blue Devils had to beat #11 Butler, whom they only topped by 2 when a pair of shots by Gordon Hayward each missed by mere inches. So you can see why some are reacting to Duke's crown today with criticism that they faced one of the easiest roads to a championship in NCAA history. But is this true? Was Duke's path to glory really devoid of potholes along the way? And if so, how does 2010 Duke compare to other past champions who had more grueling roads?
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Posted in NCAA, Statgeekery | 2 Comments »
31st March 2010
Note: This post was originally published at College Basketball Reference, S-R's brand-new College Hoops site, so when you're done reading, go over and check it out!
In a variation on a running theme (one that's especially pertinent given the early departures of Syracuse, Kansas, & Kentucky from this year's tourney), I wanted to know how often the "best" (i.e., most talented, most dominant over the entire season, etc.) team wins the NCAA Tournament. We know that the NFL's best team wins the Super Bowl about 24% of the time, that the best team in baseball wins the World Series about 29% of the team (or at least, they did back in the 1980s when Bill James studied the issue), and that the NBA's best team wins the Finals almost half of the time... So what's your guess for college basketball?
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Posted in NCAA, SRS, Statgeekery | 5 Comments »
30th March 2010
Note: This post was originally published at College Basketball Reference, S-R's brand-new College Hoops site, so when you're done reading, go over and check it out!
With Baylor and Tennessee in contention for a pair of Final Four slots on Sunday, we had the possibility of a Butler-West Virginia-Baylor-Tennessee group emerging from the regional finals, which would have been perhaps the least storied Final Four in recent history. Alas, Michigan State and Duke, two of the more successful schools of all time, crashed the Final Four party -- but they also left us with an eclectic 4-team group that will provide ample storylines over the coming week. How does this year's crop compare to past Final Fours in terms of the talent of the teams involved? Let's take a look:
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Posted in NCAA, SRS, Statgeekery | 1 Comment »
21st March 2010
This is basically a big data dump, but I thought I'd share the thought process & methodology involved. The premise is to find players whose teams won more postseason games than they were "supposed to" based on their regular season winning %'s and those of their playoff opponents (if this sounds familiar, you may have seen this Doug Drinen post, which Google found for me about halfway through the creation of this post)...
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Posted in Data Dump, History, Playoffs, Statgeekery | 13 Comments »
10th March 2010
This is another stab at something I've worked on for years -- the idea is to take the performance for each team in the Four Factors, and find teams with similar profiles in the past to determine how teams of that ilk eventually do in the playoffs. Here's the methodology:
- Calculate the Four Factors for each team on offense and defense (technically, I guess that would make it Eight Factors, but whatever).
- Calculate the Z-score for each team's factors by subtracting the league average and dividing by the league's standard deviation.
- Compute the difference between the two teams' z-scores and square it... Do this for all 8 factors.
- Add the squared differences together, weighted by the following: Offensive & defensive eFG% --> 0.2 each; offensive & defensive TOV% --> 0.125 each; offensive & defensive ORB% --> 0.1 each; offensive & defensive FT rate --> 0.075 each.
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Posted in Data Dump, Statgeekery | 14 Comments »
9th March 2010
Note: This post was originally published at College Basketball Reference, S-R's brand-new College Hoops site. All of the data used here can be found at S-R/CBB, so when you're done reading, go over and check it out!
In the media, you often hear about certain players or coaches "changing the culture" of a program, ostensibly meaning they fostered a new atmosphere in the locker room, installed a new playing style, or gave their players newfound confidence in themselves. But has anyone measured which coaches "changed the culture" of a school's hoops program the most?
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Posted in NCAA, Statgeekery | 5 Comments »