- missing a shot that is rebounded by the defense.
*Edited to add: Where did this come from? See the end of the article.
Why? Simply, because someone else on the court is using possessions at a disproptionately higher rate. There are a few reasons why this could be (here comes another list):
- the coach has instructed the team to allow certain player(s) to use more possessions
- certain player(s) have decided on their own that they should use more possessions
- the player in question thinks other player(s) should use more possessions
Ken Pomeroy's - remember Ken? we started out by talking about him - thesis is "role players don't usually become go-to guys from one year to the next, or at any point during their careers."
To prove his point, he provided a couple of nice charts, showing the change in %Poss from one year to the next, or one year to two years later. I'll reproduce them here (as always, click any image to enlarge).
There are 4 types of fitted lines on these charts.
- The thick black line represents the best fit of the data (all 2005, 2006 and 2007 college players, I think).
- The thick dark blue lines indicate the 50% prediction interval around the fit - that is, 50% of all players should be between these two lines. Another way to think of the lines is that 25% of all players will fall below the lower line, and 75% of players will fall below the upper line (and therefore 25% of players will be above the upper line).
- The thin black lines are 95% prediction intervals - only 2.5% of all players should fall below the bottom line, or lie above the upper line.
- Finally, there is the dashed line, which the is the 1:1 line. A player lying on this line would have no change in his %Poss from year 1 to year 2 (or 3).
This is not to say that all players will eventually become 22.5% possession users, but rather that this is the point where increasing possession usage becomes more difficult than not, likely due to increased competition with teammates for available possessions.
So, is there a point to all of this?
Since KenPom has %Poss data available back to 2005, I decided to plot all Big East players from the last 3 seasons (or 2 seasons) on his charts, to see if the Big East behaves as the rest of college basketball with respect to changes in usage.
Here's season 2 vs. season 1 (you'll need to click to expand to see things clearly):
A bit of explanation is in order (if there's one thing I want to be famous for, it's busy charts).
- I've sized the markers by Season 1 %Min (% of available minutes played), so that end-of-bench players wouldn't swamp regular players on the scatter plot.
- I've color-coded the markers by Season 2 Off. Rating. When I initially ran this analysis, I expected that the rate of increase from year 1 to year 2 would be strongly related to how well the player performed in the 2nd year, but this is obviously not the case - the color appears random.
- I've also color-coded Georgetown players as gray rather than on the color scale, so they'd stand out. Nothing of exception with this group.
- I've added tags identifying a few outliers.
- Finally, I've added a horizontal and vertical line at 22.5%, indicating the point where more possessions become scarce.
What's of most interest to me are the two points in the upper left quadrant: James Holmes and Draelon Burns. These two players represent the exception to KenPom's rule, in that they made the leap from role players (%Poss = 18.7 & 19.5, respectively) to go-to players (27.5 & 28.4) in a year. Since I wasn't paying much attention to either team at the time (or now), I'll leave it to someone else to explain what happened in each case.
On to the two-year gap (season 3 vs. season 1):
Many fewer data points here (n=80 here; n=274 for the previous plot), but again the analysis by KenPom seems appropriate for the Big East.
The players of interest here include Daryll Hill, who fell from go-to to role player due to injuries, and three rising seniors: Anthony Mason, Levance Fields, and Georgetown's own Jessie Sapp. Only Mason has made the leap into true got-to status (17.1 to 23.0 to 26.9), but Jessie Sapp has made an extraordinary rise from pass-only to important cog (12.2 to 18.7 to 22.6). It will be interesting to watch these three to see if they can continue to absorb possessions.
Edited 10-27-08, 10:00pm to add:
While playing with the data, one thing I did look at was the distribution of %Poss for Big East players. Here are the histograms for all players (n=611) from 2005-2008, and also for those with %Min > 40% (n=395). What's interesting is that majority of players who play less than 40% of available minutes also use less than 18% of available possessions (note that KenPom has his own filter of %Min > 10% on the data, so players with very little playing time [< 4 min / game] are already dropped from the data set).
I suspect that the subset of players with 10% < %Min < 40% group has a significant number of freshmen who are slowly being introduced to their coach's respective systems. I used the median value of the entire population in the discussion above, since many starters began their career in this role as bench / role players (e.g. Jessie Sapp).
I hadn't thought to plot %Poss vs. %Min before tonight, but the histograms above imply a relationship. Here it is:
The data points are both colored and sized by offensive rating, but there doesn't seem to be much trend in that variable. The slope of the line is ~0.085; in other words, an increase in %Min by 23% will increase %Poss by 2%, on average.
You've got to love D. Caracter's freshman season at Louisville.