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Dumpy's Statistical Analysis: Boston 112, Nets 101

Originally, I had an entire intro planned for this report. It was witty, it was clever—you know, all the good things. But then the Nets were pummeled, and, because my prologue was premised on the Nets not only winning, but playing good defense, I was left in the lurch. I’ve since spent the entire day trying to figure out what to say that hasn’t been said elsewhere, by people who are much better writers than I am, and who are actually clever and witty all the time without having to work at it. I’m still clueless. Let’s get to the numbers, and maybe something will come to me by the time I have to wrap this up.

Team Statistics

Possessions. The number of possessions (i.e., each time a team brings the ball up court) is a way to measure the pace of the game. For games involving running or trapping teams, the number of possessions will be high, possibly more than 100. For more methodical teams, the number of possessions may be closer to 80. Possessions can (generally) end one of three ways: on a field goal attempt that is not rebounded by the offense (this includes successful FG attempts); on a turnover, or through some free throws. Since this is an estimate based upon various statistics, and because the number of possessions should be approximately the same for both teams, we will just present the average estimated number of possessions for both teams.

Possessions 93

Offensive Rating. A team’s offensive rating is just the number of points scored per 100 possessions. The opponent's offensive rating can be considered the team's Defensive Rating. For the past few seasons, the average team offensive rating in
the NBA has hovered around 105.

Boston 119.9
New Jersey 108.1

Assist Percentage. The assist percentage measures the frequency that successful field goals have been assisted.

Boston 75.0%
New Jersey 57.6%

"Big Four" Factors. The four primary factors that determine the outcome of a basketball game are: field goal percentage, offensive rebound percentage, turnovers, and the ability to get to the line and hit free throws. Offensive rebound percentage is measured as a percentage of rebound opportunities; turnovers are measured as a percentage of possessions; and free throws are measured by the percentage of time the team got to the line in relation to field goal shot attempts.

Boston New Jersey
FG% 45.6% 44.6%
OREB% 30.0% 14.0%
TOV% 11.8% 15.0%
FTA/FGA 44.3% 50.0%

And the effective field goal percentage:

Boston 51.9%
New Jersey 48.0%

From these figures, we can see that the Celtics’ domination of the offensive boards was the deciding factor in this one. Had the Nets’ rebounded equally, the Celtics may well have still won—they were marginally better in field goal percentage and turnover percentage—but the game would have been a heck of a lot closer.

Nets Individual Statistics

Player Scoring Poss'ns Poss'ns. Floor% Offense Rating Points Prod. Points Scored % Tm Poss Plus/ Minus
J. Kidd 10.1 20.7 48.6% 109.3 22.6 17 27.9% -8
V. Carter 7.5 15.9 47.0% 92.7 14.7 17 26.8% -16
R. Jefferson 12.0 24.4 49.3% 107.0 26.1 28 29.7% -11
J. Collins 0.6 1.6 38.1% 81.5 1.3 0 5.0% -5
N. Krstic 1.2 2.9 42.1% 86.0 2.5 2 8.8% -9
A. Wright 2.8 5.5 51.1% 115.0 6.4 9 10.3% -5
B. Nachbar 3.6 11.7 30.5% 65.9 7.7 8 31.4% -4
D. Armstrong 2.8 3.6 76.6% 208.8 7.6 10 10.2% +4
J. Magloire 0.0 1.7 0.0% 0.0 0.0 0 0.0% -5
M. Allen 0.8 1.6 47.6% 101.7 1.7 0 24.9% -3
J. Boone 0.0 0.0 0.0% 0.0 0.0 0 0.0% -8
S. Williams 3.3 4.1 79.5% 169.4 7.0 10 19.3% +15

I think I have an idea what to do next. One of the subthemes underlying this game was how the Nets would do against Boston’s big frontcourt. As you know, the Nets’ small lineups—mostly the Kidd-Carter-Wright-Jefferson combination, but others as well—have been the most effective units thus far, but they had yet to go against a team with two legitimate post threats. In Boston, you have a team that can (and did) play two of Garnett, Perkins, and Glen Davis at the same time. How did the Nets do against these frontcourts when using a small lineup? As I’ve described it before, I use the phrase "small lineup" to describe a unit with four of [Kidd/Armstrong/Carter/Wright/Jefferson/Nachbar], supported by one center. In some cases, the Nets could play five of those guys as well. This is probably self-evident, but it’s worth tossing the definition in here just to ensure we’re all on the same page. In this game, of course, the Nets were denied the ability to bring out their most effective small units after Carter’s injury, but it still may be a fascinating analysis. Let me make it clear from the outset that I have no idea what the numbers will show; while some sportswriters appear to have a particular predetermined slant and try to back it up with handpicked stats, I have no such agenda. Let’s take a look together and see what we find.

It turns out that, as far as I can tell (hint: don’t hold me to this), when the Nets went with a small lineup against two post threats, the nets were minus-11 in roughly 14 minutes of play. When the Nets faced a small lineup with one of their own, however, the Nets were a combined plus-4 in nearly 18 minutes. This disparity can really be seen in the third and fourth quarter. In the third, the Nets played the last 8:19 against Garnett and Glen Davis with four smalls and either Collins, Magloire, or Boone, and were outscored by nine. In the fourth quarter, however, the Celtics solely played a lineup that included a single big, mostly Garnett but with a little Davis to open the quarter, and the Nets destroyed them with a small lineup of their own. Some critics may argue that the Celtics took it easy during the final quarter, but I think it may have been more than that. I am starting to suspect that the Nets’ small lineups could be among the best in the league at this point in time. It may have turned out, then, that Brian Scalabrine’s injury was beneficial to the Celtics, because it forced them to use Glen Davis more than they otherwise would have. The challenge for the Nets will be in figuring out whether such lineups can play effectively against two bigs. New Orleans will be another test.

These individual statistics are estimates based on the premise that teammates should share credit for points and scoring possessions based upon their individual contributions to each play. They are derived from the research of Dean Oliver, and more can be read in his book, "Basketball on Paper."

Glossary for Individual Statistics:

Scoring Possessions: A scoring possession is awarded to an individual when he contributes to a team scoring possession. If multiple players contribute, then credit is split among teammates based upon a formula.

Possessions: Number of team possessions used by a particular player.

Floor percentage: The percentage of a player’s possessions on which there is a scoring possession.

Offensive Rating: Points produced by an individual per 100 possessions, as calculated by a complex formula.

Points Produced: The number of points a player generates through various offensive contributions, including assists, field goals, free throws, and offensive rebounds.

Points Scored: Number of points actually scored by the player in the game, which is included here for comparison to points produced.

Percentage of Team Possessions: How often a player uses a team possession when he is in the game. With five players on the court, an average value would be 20%.

Plus/Minus: How much the team outscores the opposition when the player is in the game.