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Archive for the 'Analysis' Category

Chris Bosh and the Most Offensively Detrimental Games in Our Database (*according to statistical +/-)

25th February 2011

During Chris Bosh's brickfest last night, all I could think of was, "Wow, this is a John Starks-ian performance." Turns out it was even worse, albeit in a much less critical situation than Game 7 of the Finals.

Using offensive statistical plus/minus (OSPM), I put together a list of the most detrimental offensive games in our box score database (this spans 1987-2011 for the regular season, and 1991-2010 for the playoffs). For every game, I calculated the player's OSPM, the team's offensive rating, and what the team's offensive rating would have been had the player turned in a league-average performance. The most detrimental performances were the ones that sucked the most points from a team's offensive rating. I also added one requirement to qualify for the list: the player's offense must have cost his team a win -- i.e., with an average offensive performance from a player in his minutes, they would have outscored the opponent, but instead lost the game.

Let's use Bosh as an example. Last night, Bosh had an OSPM of -15.18, which means for every 100 possessions he was on the floor, he drained more than 15 points away from Miami's offensive rating relative to a league-average performance. Miami's actual offensive rating was 95.3, but if Bosh had just been average, Miami's rating would have been 108.5 -- meaning he cost them 13.16 points of offensive rating over the course of the entire game. Worse yet, Chicago's offensive rating was 99.6, so if Bosh had been average (or even merely below-average), Miami would have won the game. That's why Bosh qualifies for the list, because his poor offense cost his team a win.

Anyway, here are the most detrimental offensive performances in our database (mouse over column headers for descriptions):

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Posted in Analysis, Data Dump, Statgeekery, Statistical +/-, Trivia | 26 Comments »

Percentage of Team Shot Attempts “Created” While On the Floor

23rd February 2011

With noted shot-creator Carmelo Anthony on the move, I was wondering which players have a hand in "creating" the highest percentage of their team's shot attempts when on the floor.

If we're just looking at a player's own shooting attempts, this is pretty easy. You can look at the percentage of team FGA a player takes when on the court (all leaders minimum 1,366 minutes):

Player Pos Tm G Min FGA FTA %FGA
Kobe Bryant SG LAL 58 1959 1121 415 33.6%
Carmelo Anthony SF DEN 50 1774 967 417 32.7%
Derrick Rose PG CHI 53 2012 1068 328 31.8%
Kevin Durant SF OKC 51 2011 1037 457 31.3%
LeBron James SF MIA 55 2100 1034 479 30.7%
Dwyane Wade SG MIA 53 1964 957 467 30.4%
Amare Stoudemire C/PF NYK 53 1949 1028 422 30.3%
Andrea Bargnani PF/C TOR 51 1828 935 254 29.7%
Michael Beasley SF/PF MIN 48 1566 828 196 29.7%
Russell Westbrook PG OKC 55 1953 932 446 29.0%
Monta Ellis SG GSW 56 2298 1156 336 28.6%
Joe Johnson SG/SF ATL 47 1688 788 182 28.5%
Dirk Nowitzki PF DAL 47 1611 737 274 28.1%
Antawn Jamison PF/SF CLE 53 1737 822 214 28.0%
Kevin Martin SG HOU 56 1745 848 476 27.8%
Eric Gordon SG LAC 41 1550 712 296 27.6%
Brook Lopez C NJN 57 1959 870 351 27.4%
Stephen Jackson SG/SF CHA 55 2025 884 260 27.3%
Luis Scola PF HOU 58 1939 920 251 27.2%
Blake Griffin PF LAC 57 2156 971 492 27.1%

You could also take it a step further and factor in free throws as well, calculating the percentage of each team's True Shooting Attempts (FGA + .44 * FTA) each player takes while on the floor:

Player Pos Tm G Min FGA FTA TSA %TSA
Kobe Bryant SG LAL 58 1959 1121 415 1303.6 34.5%
Carmelo Anthony SF DEN 50 1774 967 417 1150.5 33.3%
Kevin Durant SF OKC 51 2011 1037 457 1238.1 32.1%
Derrick Rose PG CHI 53 2012 1068 328 1212.3 31.9%
LeBron James SF MIA 55 2100 1034 479 1244.8 31.9%
Dwyane Wade SG MIA 53 1964 957 467 1162.5 31.8%
Amare Stoudemire C/PF NYK 53 1949 1028 422 1213.7 31.7%
Kevin Martin SG HOU 56 1745 848 476 1057.4 30.6%
Russell Westbrook PG OKC 55 1953 932 446 1128.2 30.1%
Andrea Bargnani PF/C TOR 51 1828 935 254 1046.8 29.6%
Monta Ellis SG GSW 56 2298 1156 336 1303.8 29.1%
Michael Beasley PF MIN 48 1566 828 196 914.2 29.1%
Dirk Nowitzki PF DAL 47 1611 737 274 857.6 29.1%
Blake Griffin PF LAC 57 2156 971 492 1187.5 28.8%
Brook Lopez C NJN 57 1959 870 351 1024.4 28.5%
Eric Gordon SG LAC 41 1550 712 296 842.2 28.4%
Joe Johnson SG/SF ATL 47 1688 788 182 868.1 28.0%
Antawn Jamison PF/SF CLE 53 1737 822 214 916.2 27.5%
LaMarcus Aldridge PF/C POR 56 2206 989 332 1135.1 27.3%
DeMarcus Cousins C SAC 53 1443 662 248 771.1 27.2%

But I think you need to take assists into account as well.

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Posted in Analysis, Statgeekery | 30 Comments »

Layups: The ‘Black Hole Atlas’

15th February 2011

How in the cosmos did I miss this the first time around?

Two weeks ago, while I was busy with Super Bowl/Hall of Fame work at PFR, SBNation's Tom Ziller posted a story -- and an awesome graphic -- about the biggest "black holes" (players who never pass) in the NBA.

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Posted in Analysis, Just For Fun, Layups, Statgeekery | 21 Comments »

How Telling Is a Team’s Record vs. Elite Teams?

14th February 2011

Despite their high overall marks, apparently neither the Lakers nor the Heat can beat the league's other so-called "elite" teams. Miami is just 6-9 this season against teams in the top 10 in W-L%, and 0-6 against top-5 teams. The Lakers are barely better, going 6-7 vs. top-10 squads and 2-6 against the top 5. Here's a summary of the other teams in the top 10 by either W-L% or point differential:

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Posted in Analysis, History, Playoffs, Statgeekery | 41 Comments »

Mini-Mailbag: MVP Winners, Team Winning %, & SRS

11th February 2011

Alex Sonty, who writes ChicagoNow's Load O' Bull blog, has been paying close attention to Henry Abbott's TrueHoop posts about Derrick Rose -- specifically, this post about past MVP winners and their teams' rankings in wins. Henry found that team wins were highly correlated with MVP voting, to the point that 19 of the last 20 MVPs came from a team with a top-3 record. This of course is bad news for Rose, as the Bulls are 6th in winning % at the moment.

But Alex was wondering how past winners stack up in a schedule-adjusted margin-of-victory based metric like the Simple Rating System, where the Bulls are 5th. So here's the master list -- every MVP winner, with their team's rank in both WPct and SRS:

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Posted in Analysis, Awards, BBR Mailbag, History, SRS | 14 Comments »

Layups: Ken Pomeroy on Single-Game Plus-Minus

10th February 2011

Ken Pomeroy (of the outstanding college hoops stat site Kenpom.com) ran an interesting simulation last month with regard to the randomness inherent in single-game plus-minus scores:

A treatise on plus/minus - the kenpom.com blog

According to Ken's simulation, a player with precisely average "true +/- skill" can show up with wildly variant observed +/- values over the course of a game, or even 20 games.

Just for fun, I re-ran this experiment for ten thousand games, tracking the observed +/- impact of the player through various checkpoints. Here were the results:

#Sims On Off MOV per40
1 5.00 -17.00 -12.00 44.00
10 0.70 -2.60 -1.90 6.60
100 0.49 -0.85 -0.36 2.68
500 -0.39 -1.02 -1.41 1.26
1000 -0.16 -0.46 -0.61 0.60
5000 -0.06 0.10 0.04 -0.31
10000 -0.13 0.12 -0.01 -0.51

Even after 10,000 games, a massive sample that would never be possible to achieve in real life, our perfectly average "player" appears to be a half-point per 40 min worse than average by raw on/off-court plus minus. As Ken says, "respect randomness"!

Posted in Analysis, Layups, Statgeekery | 3 Comments »

2011 APBRmetric All-Stars

9th February 2011

Just as we did last season, let's take a look at which players would have made the All-Star teams if various advanced stats were the only criteria in the voting. To pick teams, I used the official positional designations from the 2011 ballot; each team must have 4 guards, 4 forwards, and 2 centers, with room for 2 wild cards from any position to fill out the roster. Players in bold are starters; "*" designates the player as a member of the real-life All-Star team.

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Posted in All-Star Game, Analysis, Statgeekery, Statistical +/-, Win Shares | 142 Comments »

“Too Much Kobe”? Try “Not Enough Defense”

31st January 2011

Just a brief rant about the media reaction to yesterday's Celtics win over LA...

After the game, especially on the SportsCenter coverage last night, I saw "Too Much Kobe" being held up as an explanation for the Lakers' struggles. Here's a sample:

"Bryant took 29 of the Lakers' 66 field goal attempts (43.9 percent) while he was on the floor. This was the 10th game this season that Bryant took more than 40 percent of the Lakers' shots while on the court. In those 10 games, the Lakers are 3-7. Los Angeles is much better when Bryant shoots a smaller percent of the team's shots while on the court. The Lakers are 23-5 when Bryant takes less than 35 percent of the team's shots when on the floor."

That's a familiar media theme when Kobe scores a ton of points but his team loses; we saw it a lot in 2006, for instance.

As far as I can tell, "Too Much Kobe" is exclusively an offensive criticism. Trouble is, L.A.'s offense was fine yesterday. Against the 3rd-best defense in the league, against whom an average team would expect to score about 104 pts/100 poss. at home, the Lakers scored 110.1. The offense is not why L.A. lost, and therefore "Too Much Kobe" can't be why they lost.

They lost because they allowed the 11th-best offense in the NBA to score a staggering 125.0 points per 100 possessions against them on the road. This may or may not be Kobe's fault -- aside from personal fouls, he wasn't overly active on D, and despite his scoring feats the Lakers were -9 when he was on the court.

But it can't possibly be because Kobe had zero assists.

Posted in Analysis, Boxscore Breakdown, Rants & Ramblings | 143 Comments »

SRS Standard Errors, the Probability of Being the Best Team, and a Layup

20th January 2011

I finally got around to calculating the standard errors for our team Simple Ratings today:

Team Estimate Std. Error
SAS 7.97 2.62
MIA 6.90 2.60
BOS 6.67 2.63
LAL 5.78 2.59
CHI 4.81 2.61
ORL 4.61 2.61
DEN 3.48 2.63
DAL 3.30 2.62
NOH 2.40 2.60
OKC 2.05 2.61
ATL 1.75 2.60
UTA 1.73 2.61
HOU 0.86 2.60
POR 0.52 2.60
MEM 0.49 2.61
NYK 0.09 2.62
MIL -0.57 2.65
PHI -0.79 2.63
IND -0.87 2.65
LAC -1.51 2.63
PHO -1.91 2.64
GSW -2.92 2.62
CHA -3.74 2.64
DET -3.94 2.61
TOR -4.23 2.62
MIN -5.33 2.60
WAS -5.82 2.64
SAC -6.12 2.64
NJN -6.22 2.61
CLE -10.88 2.62

Then I set up a little Monte Carlo sim to estimate what is the probability of each team being the NBA's best (aka the team with the greatest "true" SRS skill). After 10,000 simulations using the estimates and standard errors above, here were the results:

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Posted in Analysis, Layups, SRS, Statgeekery | 8 Comments »

Franchise Peaks and Valleys

20th January 2011

What was the best run ever for your favorite team? What was the worst stretch of seasons? Let's take a look at the raw numbers in terms of NBA winning percentage over an x-year span (including our regressed 2011 WPcts):

Best & Worst 2 Years

Team Best 2 Years Worst 2 Years
Atlanta Hawks 1986/1987 (.652) 2005/2006 (.238)
Boston Celtics 1985/1986 (.793) 1996/1997 (.293)
Charlotte Bobcats 2009/2010 (.482) 2005/2006 (.268)
Chicago Bulls 1996/1997 (.860) 2000/2001 (.195)
Cleveland Cavaliers 2009/2010 (.774) 1982/1983 (.232)
Dallas Mavericks 2006/2007 (.774) 1993/1994 (.146)
Denver Nuggets 2009/2010 (.652) 1998/1999 (.189)
Detroit Pistons 1989/1990 (.744) 1980/1981 (.226)
Golden State Warriors 1975/1976 (.652) 2000/2001 (.220)
Houston Rockets 1993/1994 (.689) 1983/1984 (.262)
Indiana Pacers 1998/1999 (.689) 1983/1984 (.280)
Los Angeles Clippers 1975/1976 (.579) 1987/1988 (.177)
Los Angeles Lakers 1972/1973 (.787) 1958/1959 (.361)
Memphis Grizzlies 2004/2005 (.579) 1996/1997 (.177)
Miami Heat 1997/1998 (.707) 1989/1990 (.201)
Team Best 2 Years Worst 2 Years
Milwaukee Bucks 1971/1972 (.787) 1993/1994 (.293)
Minnesota Timberwolves 2003/2004 (.665) 1992/1993 (.207)
New Jersey Nets 2002/2003 (.616) 2010/2011 (.216)
New Orleans Hornets 1997/1998 (.640) 1989/1990 (.238)
New York Knicks 1993/1994 (.713) 1963/1964 (.269)
Oklahoma City Thunder 1995/1996 (.738) 2008/2009 (.262)
Orlando Magic 2009/2010 (.720) 1990/1991 (.299)
Philadelphia 76ers 1967/1968 (.798) 1973/1974 (.207)
Phoenix Suns 1993/1994 (.720) 1969/1970 (.335)
Portland Trail Blazers 1990/1991 (.744) 1972/1973 (.238)
Sacramento Kings 2002/2003 (.732) 2009/2010 (.256)
San Antonio Spurs 2005/2006 (.744) 1988/1989 (.317)
Toronto Raptors 2000/2001 (.561) 1997/1998 (.280)
Utah Jazz 1997/1998 (.768) 1979/1980 (.305)
Washington Wizards 1975/1976 (.659) 1962/1963 (.269)

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Posted in Analysis, History, Statgeekery, Trivia | 10 Comments »