Championship Usage Patterns II

After yesterday’s post about optimal championship usage patterns, I got a lot of good feedback about possible alternative versions of the same study that would better capture the effect I was going for. When setting up for the initial study, I struggled between sorting by minutes played and by raw modified shot attempts (MSA), each of which had unique advantages. But a nice compromise (suggested by reader Brian) would be to isolate the top 5 players on each team by minutes — thereby approximating their most frequent 5-man unit — and then sort by MSA%, the percentage of team MSA that each player took while on the floor:

Modified shot att% by team rank
Year Team #1 MSA% #2 MSA% #3 MSA% #4 MSA% #5 MSA%
1952 Minneapolis Lakers 31.6 22.9 18.1 16.3 15.7
1953 Minneapolis Lakers 28.4 23.1 21.1 15.6 15.6
1954 Minneapolis Lakers 29.3 19.3 18.2 17.1 16.2
1955 Syracuse Nationals 25.8 20.7 19.8 18.5 15.0
1956 Philadelphia Warriors 26.6 23.0 22.7 17.9 16.4
1957 Boston Celtics 25.8 24.2 22.5 17.2 16.6
1958 St. Louis Hawks 25.7 25.0 18.0 17.2 14.3
1959 Boston Celtics 24.7 24.0 23.2 23.1 13.6
1960 Boston Celtics 26.0 25.8 22.9 17.9 15.5
1961 Boston Celtics 26.8 24.2 20.7 20.0 17.3
1962 Boston Celtics 26.8 25.4 22.2 17.5 12.0
1963 Boston Celtics 27.0 26.0 23.1 16.8 12.9
1964 Boston Celtics 25.7 22.7 15.6 14.5 14.0
1965 Boston Celtics 25.3 24.2 17.3 14.5 13.8
1966 Boston Celtics 27.1 24.4 17.7 16.8 12.3
1967 Philadelphia 76ers 24.1 22.3 20.2 18.0 13.1
1968 Boston Celtics 24.5 24.1 20.5 19.6 15.8
1969 Boston Celtics 27.0 23.4 19.1 16.3 13.2
1970 New York Knickerbockers 24.0 20.6 19.2 18.3 17.6
1971 Milwaukee Bucks 25.5 24.7 22.8 16.6 14.9
1972 Los Angeles Lakers 30.5 25.3 18.7 14.8 12.5
1973 New York Knickerbockers 22.0 22.0 21.5 20.6 19.8
1974 Boston Celtics 26.0 23.1 20.8 14.1 12.9
1975 Golden State Warriors 30.8 23.8 21.6 18.9 9.7
1976 Boston Celtics 25.0 24.1 22.5 19.2 11.9
1977 Portland Trail Blazers 25.2 22.8 20.9 17.7 17.6
1978 Washington Bullets 23.8 23.2 21.3 18.1 11.5
1979 Seattle Supersonics 32.0 24.1 17.6 17.5 17.3
1980 Los Angeles Lakers 26.5 21.2 20.7 20.4 16.7
1981 Boston Celtics 23.7 22.4 21.8 17.1 15.7
1982 Los Angeles Lakers 24.8 23.1 21.1 20.8 19.3
1983 Philadelphia 76ers 30.1 24.6 23.6 21.9 13.9
1984 Boston Celtics 25.9 22.5 18.6 16.9 14.5
1985 Los Angeles Lakers 25.1 24.1 20.4 20.2 15.4
1986 Boston Celtics 25.1 21.8 20.4 19.9 17.2
1987 Los Angeles Lakers 27.3 22.5 21.9 18.4 18.2
1988 Los Angeles Lakers 26.2 24.8 22.0 21.4 12.8
1989 Detroit Pistons 29.1 24.5 20.8 15.7 10.4
1990 Detroit Pistons 27.3 23.4 15.4 14.9 9.5
1991 Chicago Bulls 34.6 24.9 14.8 14.1 13.7
1992 Chicago Bulls 36.4 24.5 13.6 13.4 11.3
1993 Chicago Bulls 38.8 25.5 14.7 13.8 13.5
1994 Houston Rockets 29.7 21.2 17.8 17.8 13.5
1995 Houston Rockets 33.7 24.0 17.7 15.7 13.3
1996 Chicago Bulls 33.4 24.0 21.2 16.6 11.1
1997 Chicago Bulls 35.7 24.3 15.6 14.2 9.6
1998 Chicago Bulls 36.7 24.2 20.8 14.1 9.8
1999 San Antonio Spurs 25.4 22.0 21.3 18.1 15.9
2000 Los Angeles Lakers 30.0 26.7 17.6 17.1 15.0
2001 Los Angeles Lakers 30.9 30.0 15.4 13.6 12.9
2002 Los Angeles Lakers 30.4 29.9 16.2 13.9 12.3
2003 San Antonio Spurs 26.7 24.8 19.1 18.6 11.9
2004 Detroit Pistons 27.4 23.9 20.3 16.4 15.0
2005 San Antonio Spurs 31.0 26.7 26.1 16.3 9.5
2006 Miami Heat 32.8 25.5 19.9 18.9 14.3
2007 San Antonio Spurs 29.7 28.6 28.0 18.9 9.7
2008 Boston Celtics 25.9 25.4 22.9 19.3 10.4
2009 Los Angeles Lakers 34.3 18.3 16.7 15.7 15.2
Average Champ
28.2 23.9 19.9 17.3 14.0
Avg. Non-Champ 27.6 23.5 20.4 17.7 14.0

So, in the playoffs, teams that win it all tend to have a small (but significant) tendency to allocate more possessions to their top two options — and fewer to their #3 & #4 options — than teams who lose. In other words, the model of a superstar “Alpha Dog” plus another quasi-star and 3 role players seems to be the dominant usage pattern that differentiates NBA champs from teams that fall short.

This is borne out by the logistic equation that best models the data above:

p(Championship) ~ 1 / (1 + exp(3.23 – 0.01*MSA#1 – 0.10*MSA#2 + 0.10*MSA#3 + 0.01*MSA#4 – 0.03*MSA#5))

All else being held equal, the effect is strongest when looking at the #2 and #3 options in the primary lineup; the closer the two numbers are, the worse the probability is that the team in question will win the championship. For instance, a team with an allocation of 27%/21.5%/20.5%/17%/14% will be expected to win the title 6.8% of the time, but for a team with an allocation of 27%/24.5%/17.5%/17%/14%, the expected p(C) becomes 11.7% — almost doubled from the first lineup, simply by allocating 3% more MSA to the #2 and 3% less to the #3.

The 2010 playoff team that seemed to fit this model best was the OKC Thunder, whose Kevin DurantRussell Westbrook combo was reminiscent of great 1-2 punches of days past. However, it’s important to remember that the model only works when holding everything else equal, and the Thunder’s overall talent level (#9 in SRS) was not equal to that of the best teams in the league this year. However, among the Final Four teams (who should theoretically be roughly equal in talent), the Lakers are the best fit for the model — their Alpha Dog‘s ability is undisputed, and perhaps more importantly, the gap between their #2 (Pau Gasol) and #3 (Ron Artest) is 4.6 points of MSA%. The teams the formula likes the least are Phoenix and Boston, who have essentially no difference between their #2 and #3 options in terms of MSA% (the Celtics, with Rajon Rondo + the Big 3, take this to a real extreme: less than 4 points of MSA% separate their #1 option from their #4).

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About Neil Paine

I work for Sports-Reference.com. I've been a freelance writer for ESPN, Sports Illustrated, The New York Times, and Basketball Prospectus.

Posted on May 19, 2010, in Analysis, Playoffs, Statgeekery. Bookmark the permalink. 10 Comments.

  1. Much better that part I, I’d say.

  2. The 1973 Knicks might never be beaten for flatness. The 1978 Bullets total under 100, which I suppose says you can win if you keep your mad bombers mostly on the bench.

    The 2010 Celtics look a lot like the 1982 Lakers, only older.

  3. I’m not sure what to think here. Averages are ok but there is a lot of variance and the sample size is pretty small. Caveat: these are generic criticisms, and I’m not trying to say that statistical studies of NBA finalists are futile.

    In this case though, it might be good to compare these teams to NBA average, or teams with a losing record. Either way the variance makes me hesitant to draw conclusions from the averages. There are a good number of teams with the third guy at 15-16%, and a good number with the third guy over 20%. We sort of know intuitively that champions usually have a dominant player, a second all star, and beyond that it varies. These numbers confirm that idea but I don’t see a lot else there.

  4. Remember, for every data point in that table, there are 10-15 that I didn’t show (i.e., teams that didn’t win the championship). The general trend is apparent from the regression on 700 teams — between two teams with equal offensive skill levels, the one that’s more balanced between its #2 & #3 options is less likely to win a championship.

  5. This really doesn’t have a whole lot to do with this post, but I thought of it after watching last night’s game and wanted to mention it somewhere. Can we please stop referring to Pierce, Garnett, and Allen as “The Big 3”? I think the 2010 Celtics can much more adequately be described as “Rajon Rondo and the Medium 3”

  6. Sort by column number one and you find the Alpha Dog being the Alpha Dog again.

  7. Meh, Column three (#1 MSA%)

  8. I’m new to this advanced stat stuff, but do find it interesting (always thought the sexy stats really don’t say much).. So who are the best players within their msa% and what would be the ultimate nba team and/or us national team based on this theory?

  9. Hmm, how about weighting things? I think the 2001 LAL squad had the most dominant playoff run ever. And they had 1a and 1b + “fluff”. So the top tier playoff runs should maybe more inform the average? Also, by eyeball the “good” championships teams seems to have the a total of ~60 for the top 2…

  10. Looking at the average post-merger, from ’77 to present, the two top dogs split looks even more pronounced.
    29.56 24.22 19.58 17.19 13.57

    Not sure that making a split there (or somewhere else) is valid, but the game has changed since the days of Russell’s Celtics so averaging over all champs would seem to flatten what’s happening now.

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