Category Archives: nba

Ray Allen, finals MVP?

He certainly seems to have found his stroke in this series, and has been arguably the most consistent of the Big Six… here are the individual contributions to last night’s game:

tm Player MP PTS MEV PVC PtC Credit G/B
bos Ray Allen 48.00 19 25.69 0.293 29.34 0.312 4.69
lal Lamar Odom 39.00 19 24.86 0.301 26.57 0.283 4.70
bos Paul Pierce 42.17 20 18.07 0.206 20.64 0.220 2.26
lal Kobe Bryant 43.35 17 19.01 0.230 20.31 0.216 2.08
bos Kevin Garnett 37.15 16 16.66 0.190 19.03 0.202 2.23
bos James Posey 25.47 18 12.84 0.146 14.66 0.156 3.07
lal Trevor Ariza 8.72 6 11.65 0.141 12.45 0.132 12.44
lal Pau Gasol 37.98 17 11.20 0.136 11.96 0.127 1.82
lal Derek Fisher 25.33 13 9.98 0.121 10.67 0.113 2.57
lal Vladimir Radmanovic 26.58 10 9.55 0.116 10.21 0.109 2.66
bos Eddie House 24.57 11 8.51 0.097 9.72 0.103 2.50
bos Rajon Rondo 17.02 5 4.90 0.056 5.60 0.060 2.73
bos P.J. Brown 14.53 3 2.07 0.024 2.36 0.025 1.51
bos Leon Powe 9.05 3 0.80 0.009 0.91 0.010 1.15
bos Kendrick Perkins 13.25 2 0.57 0.006 0.65 0.007 1.19
lal Jordan Farmar 21.42 3 0.57 0.007 0.61 0.006 1.11
bos Tony Allen 2.23 0 0.52 0.006 0.59 0.006 #DIV/0!
lal Luke Walton 3.78 3 -0.70 -0.008 -0.74 -0.008 0.81
lal Ronny Turiaf 10.02 0 -1.12 -0.014 -1.20 -0.013 0.57
lal Sasha Vujacic 23.82 3 -2.48 -0.030 -2.65 -0.028 0.76
bos Sam Cassell 6.57 0 -2.90 -0.033 -3.31 -0.035 0.00
Totals 480 188 170.25 2.000 188.38 2.004 2.24

What a game it was! I admit to assuming a Laker win and tuning out. I never expected such a comeback! Allen, Pierce and Garnett all showed up last night, and Bryant missed his usual umteen shots. Posey and Ariza both had pretty big games, but Vujacic fell off the map.

For games like these, I like putting together a graph of team points over time, which is something you can find elsewhere, but I add some useful information to mine, and calculate what I call “approximate domination,” (although I could probably come up with a better name). Essentially, you take the area under the winning team’s curve below, and subtract the area under the losing team’s curve. This is the average lead, compounded by second, over the course of the game. To me, it represents the extent of the closeness of a game better than final score.

As is hopefully evident, the Lakers dominated this game, but the Celtics drastically increased their slope right after LA took their biggest lead. The black trendline is Laker’s scoring, and green is Celtics. The sparklines at bottom represent individual scores, height-scaled in accordance with how many points were made–ftm, f2m, or f3m. Dotted lines indicate points at which the teams were tied, and solid vertical lines indicate the largest deficit and lead for the winning team. As you can see, despite winning by six, the Celtics trailed by an average of eleven points for the duration of the game. I think this is somewhat informative, although, unfortunately, somewhat time-consuming to calculate… what do you think?


The Grizzlies were good, once

And not too long ago, either. It may seem hard to believe today, but the Memphis team once featured actual good players and won more than half of their games. In 03-04, everybody on the team upped their production by about 50%, and James Posey came to the team, playing the most productive basketball of his career, by far. It’s always interesting to me to find players who are colored gray, indicating that their playing style is very close to the league average–that is, their propensity to score, play perimeter ball, and do interior things is very much in line with some theoretical “average player”–Battier in 02, Posey in 04, and Miller in 06 played in this vein and found success in the role. Also of note is the contrast between a player like Rudy Gay, who in 2007-08 was about as scoring-oriented a player as you will find, and one like the slate-blue versions of Battier and even Gasol, whose color pegs them as essentially opposite to a scoring-oriented player like Gay. Rudy may be good, and have lots of potential (quality younger players often start out with a focus on shooting), but I always have had a soft spot for those scorer’s-opposite types like Battier.

Grizzlies franchise history

What do you think? Was Posey the catalyst for the Grizzlies’ success? Did Battier’s and Jones’ departure spell the end? Does the order of the players within each season appear right? Is Abdur-Rahim one of the best players in Vancouver/Memphis history? Please let me know your expert opinions in the comments.

Making Pierce a liability

… is what the Lakers managed to do last night. Garnett, had he not rebounded well, would have also been a huge negative, although he had three offensive and nine defensive boards, which is the same as Pau Gasol, who people incessantly call “soft.” Bryant really tried to take this game over, and managed to win it for his team, I admit that I was skeptical that such an approach would work (he had only one assist), but it seems to have in this case.

tm Player MP PTS MEV PVC PtC Credit G/B
lal Kobe Bryant 45.25 36 28.07 0.370 33.39 0.397 2.62
bos Ray Allen 41.42 25 25.54 0.370 28.91 0.344 4.06
lal Sasha Vujacic 27.60 20 20.08 0.265 23.88 0.284 5.93
bos Kendrick Perkins 28.45 8 16.05 0.232 18.17 0.216 5.10
bos James Posey 24.60 9 12.25 0.177 13.86 0.165 5.94
lal Jordan Farmar 20.05 5 11.55 0.152 13.74 0.164 6.67
bos Kevin Garnett 41.98 13 10.17 0.147 11.52 0.137 1.49
bos Rajon Rondo 21.87 8 7.62 0.110 8.622 0.103 1.97
lal Pau Gasol 39.47 9 4.97 0.065 5.906 0.07 1.36
lal Trevor Ariza 8.82 4 4.61 0.061 5.483 0.065 5.53
bos Eddie House 19.80 6 4.82 0.070 5.461 0.065 1.74
lal Derek Fisher 28.07 6 4.02 0.053 4.778 0.057 1.60
lal Luke Walton 11.23 0 1.97 0.026 2.342 0.028 1.60
bos Sam Cassell 6.85 2 0.95 0.014 1.07 0.013 1.29
lal Lamar Odom 27.97 4 0.75 0.010 0.89 0.011 1.05
lal Ronny Turiaf 18.87 0 0.26 0.003 0.31 0.004 1.16
lal Vladimir Radmanovic 12.68 3 -0.42 -0.006 -0.5 -0.01 0.89
bos Leon Powe 5.98 1 -2.25 -0.033 -2.55 -0.03 0.57
bos P.J. Brown 17.48 3 -2.39 -0.035 -2.7 -0.03 0.68
bos Paul Pierce 31.57 6 -3.67 -0.053 -4.16 -0.05 0.80
Totals 480 168 144.93 2.000 168 2.01 1.94

It is difficult to identify what to take away from this game: PP had a game last night like Kobe has been having all season against the Celtics–last night, some folks were saying that the Celts should take heart because their two best players played terribly, and they still made it a close game on the road. However, to the extent that LA caused their terrible play with good defense, this is not a reason to rejoice, unless they can come up with a better plan for the next game.

Just how bad was the free throw discrepancy in Game 2?

An inquisitive reader asked me to examine just how bad was the home/away free throw attempt discrepancy in game 2. Using regular season data from 1986-2008, I calculated home fta – away fta, finding a maximum of 41 (on 02/06/93 DEN v DAL) and a minimum of -41 (on 11/19/03 NYK v LAL). The mean discrepancy in favor of the home team is 1.364, and the standard deviation is 10.254. Below is a plot of the empirical density, with Game 2 indicated with a red line:

Game 2’s difference, 38-10=28, is 2.598 standard deviations above the mean. If my counting is correct, this puts the game in the 0.994 percentile of games in terms of pro-home free throw attempt discrepancy. What I cannot tell you, unfortunately, is whether it was the officiating, or the play, that lead to the difference.

Credit where credit is due

Last night’s game was awesome–I admit a pro-Celtics bias on account of a pro-Kevin Garnett bias, but also and anti-Kobe Bryant bias. When claiming objectivity, it’s always a good thing to clear potential biases up front, to let the reader know who they’re dealing with… That said, Garnett had a pretty good game last night, and Bryant had a pretty bad game… Garnett would have been even better without that cold streak–the only player who missed more shots was Kobe, who missed 17! Using the results of a huge, awesome linear regression the results of which have not yet been made public (although it’s very similar to the coefficients seen here), I derive the following from last nights box scores:

Player min pts MEV PVC PtC Credit
Kevin Garnett 40.65 24 22.33 0.250 25.94 0.279
Paul Pierce 31.07 22 18.49 0.207 21.48 0.231
Pau Gasol 41.47 15 19.39 0.246 20.52 0.221
Derek Fisher 40.82 15 18.98 0.241 20.09 0.216
Ray Allen 43.95 19 16.85 0.189 19.57 0.210
Rajon Rondo 35.03 15 14.92 0.167 17.34 0.186
Lamar Odom 39.02 14 12.90 0.163 13.65 0.147
Kobe Bryant 41.87 24 11.06 0.140 11.71 0.126
Vladimir Radmanovic 17.05 5 9.86 0.125 10.43 0.112
Leon Powe 9.32 4 6.85 0.077 7.96 0.086
Sam Cassell 12.97 8 5.40 0.061 6.28 0.067
P.J. Brown 21.20 2 5.08 0.057 5.90 0.063
Sasha Vujacic 26.52 8 4.17 0.053 4.41 0.047
Ronny Turiaf 12.38 5 1.74 0.022 1.84 0.020
Jordan Farmar 7.18 2 0.86 0.011 0.91 0.010
Kendrick Perkins 23.02 1 0.63 0.007 0.73 0.008
Luke Walton 13.70 0 -0.05 -0.001 -0.06 -0.001
James Posey 22.80 3 -1.39 -0.016 -1.61 -0.017
Totals 480 186 168.05 2.000 187.08 2.012

MEV is the term for model-estimated value or point difference created, using only the regression weights. PVC is percent of valuable contributions, which is each player’s part of total team MEV. PtC is points created, which scales MEV values according to actual team and opponent scoring, to roughly account for those factors unmeasured by the box score, and Credit is, essentially, the amount of a win each player should be credited for. MEV and PtC are intended to account for both offensive and defensive contributions, that is, the player’s contribution to his own team’s scoring, and his defense preventing his opponent’s scoring. Boston’s total team Credit was 1.114, and LA’s was 0.898, based on the number of points each scored. It appears as though Boston was able to do to Kobe what they did in the regular season. Note that Posey, despite a timely three, actually hurt his team some: his two turnovers and three personal fouls effectively cancelled out his two steals, while his two defensive rebounds and three points could not compensate sufficiently for four missed shots. However, this is only based on box scores… he may have had tremendous unmeasured defense which I cannot capture, since his plus/minus was +3. It’s interesting to compare my metrics with plus/minus figures: Kobe was -13 for the game…

Carrying the burden

There has been some discussion lately as to whether the Lakers are better when Bryant scores a lot versus when he facilitates others’ scoring. I thought I’d look at the game-by-game data to investigate: The correlation between Bryant’s percentage of team total field goals attempted and point differential is -.539; between Bryant’s percentage of team total assists and point differential is -.609. This is inconclusive, but it indicates that when Bryant does a lot of the scoring, or a lot of the passing (i.e. the team relies on him increasingly exclusively), the team does poorly. This is likely because Bryant’s statistical load-carrying results from his teammates playing poorly, and when they do so, they are more likely to lose. One other interesting finding is that the correlation between Bryant’s assists/field goal attempts and point differential is 0.312–implying that as Bryant’s game shifts more toward facilitating (ignoring his statistics relative to team totals), his team does better. For comparison, the same correlation for Derek Fisher is -0.032 (essentially insignificant), Gasol is 0.123, Odom is 0.198, Kevin Garnett is 0.302, Paul Pierce is 0.023, Ray Allen is 0.152, and Rajon Rondo is 0.127. To the extent that anything can be gleaned from such simple correlations, we might take away that Bryant’s facilitating is very important to Laker success.

I thought I would also take a look at how different players’ contributions affected team outcomes. To do this I used PVC (percent of valuable contributions) for each game for six different players, and plotted that against team scoring differential (the colors of the dots are what type of game they played):

Gasol gives us a fairly small sample size, but it would appear that he mostly contributes about 15% of his team’s valuable contributions, and their success changes little when he does more.

Odom appears to have a “sweet spot” in the middle of his PVC range–if he has a poor game or plays low minutes, or if he has to carry the burden, the team falters.

It appears that as Bryant carries and increasing amount of the load for the Lakers, they do poorly. This might mean that if Bryant makes it all about himself, his teammates play badly, or it might mean that in games in which the Lakers are faring poorly, Bryant attempts to take over–the causal arrow in this, and all of the other graphs, is very cloudy.

Allen’s PVC appears to have little to do with team success.

The trend is somewhat ambiguous, but it appears that Pierce has bigger games when the Celtics play well.

LikeĀ  Bryant’s, this is another fairly obvious downward trend. My intepretation is that the high PVC games are those in which Garnett’s teammates fail to show up, and thus he carries the load. With little or no help, he cannot win the game on his own.

Let me know if these graphs hold any more insight for you, or if I’m reading them wrong, or if they mesh with your subjective notions. If I can get the data, I might look at Michael Jordan’s numbers, to see whether or not he really could take over games and lead his team to victory.

Edit: Here’s Jordan’s Chicago years, regular season post-1986-87 (my data only goes back that far). He shows a similar pattern, although his PVC goes substantially higher–he had some big games. The sparseness of the data on the high end makes it tough to make firm conclusions. Note also that one problem with interpreting all of these is that in huge blowouts (either for or against), the starters are often taken out early, leading to a diminished PVC. This could be fairly heavily influencing the trends here.

Double edit: You might be interested in seeing the results of the first game, in terms of individual contribtions, which I’ve tabulated here.

Triple edit: Since it’s apparently been lost on one of our commentors, I should mention that the fit lines are loess smoothers, and were not, in fact, drawn in MS Paint.

The Road to the NBA Finals

Using a modification of the BoxScores formula, and applying it to single games, I’ve developed an estimate of Points Created (which accounts for both points scored by the player’s team (positive), and points scored by their opponent (negative)) for each player on both NBA finalists for each game through the end of the Conference Finals. The result is a very accurate estimate of player contributions to victory in each game–the big stars often rise to the top, but in an 82-game season, followed by a 15- or 20-game playoff run, role players often make the difference. Bryant, Gasol and Odom often lead their team’s production, but even Walton and Radmanovic have lead the Lakers to victory. The Celtics appear even more balanced in this sense–while Garnett, Pierce, and Allen often top the Points Created table, Rondo and Perkins often play huge roles–even leading their team to victory in the fifth game of the Conference Finals against Detroit.

Points Created by Game: Boston

Points Created by Game: LA

One of the more interesting things about this representation is the different types of games each player has–indicated here by coloration. Games in which a player primarily contributes with scoring are redder, those in which he does “interior” things–blocks and rebounds–are bluer, and those with mainly perimeter contributions–assists and steals–are greener. Most games fail to fall easily into a single category, and so color combinations identify the degree to which each player’s performance can be characterized in each of these three ways. Thus, a purple box indicates a scoring performance by an interior player, a yellow box shows scoring/perimeter, etc. It is interesting to note that these colors often reflect commonly held notions about playing style–Bryant is often relatively red, leading his team offensively, and occassionally green, when he passes out assists or locks down on defense. Garnett is every possible color in the graphic, revealing his multifaceted ability to do whatever his team needs.

Below is a crudely compiled comparison of the teams’ head to head matchups during the regular season (click through to get a top-to-bottom matchup of both teams’ entire seasons). Boston won both meetings decisively, though the Lakers had not yet gained Pau Gasol (though they did have Bynum, who will not play in the finals). Garnett and Pierce had huge second games, creating 37.9 and 34.5 points, respectively. Bryant’s performance in the first was below his average, and in the second was dismal–focusing mainly on scoring (orange/pink coloration), and failing to create much difference between the teams. I would be interested to hear any comments you might have, or things you notice in the graphics. There is a ton of information to glean here, and I haven’t begun yet to absorb much of it.

Both Teams’ Seasons