This is part of a series of posts examining whether offense or defense has more control of various aspects of a typical college basketball game. The introduction is here. A description of the methodology is here.

A common crutch for analyzing a college basketball game is to propose that the team that controls the pace will gain an advantage. It’s one of those things that sounds intelligent so it will never go away, but the analysis here shows that generally speaking, the offense has significant control of its own possession length. When forecasting a team’s possession length in a game, the modeling efforts described here reveal that the offense is responsible for 86% of the variance in the prediction. (Some of the plots in this post also give one the impression than offense is driving the pace bus.)

This is a general statement that should be reexamined on a team-by-team basis. For one counter-example, West Virginia had the shortest defensive possessions in the land by a wide margin last season. The Mountaineers’ press forced a bunch of turnovers, committed fouls more frequently than any other team, and gave up fast break points at an alarming rate. Their style was perfect for encouraging quick defensive possessions and even though their offense was slower than average, their overall tempo was ranked in the top 40.

But this study is looking at global trends, and as a starting point one should understand that West Virginia is an unusual case and the offense is normally going to impose its pace preference on the defense.
It’s not a completely futile exercise to try and make the opposing offense play at a pace it’s not used to, but the effort is often going to have limited results.

There’s a school of thought that the gradual slowing of the game is largely due to increasingly physical defense. But even without doing modeling, I think most people understand that the offense has more control over pace. And somehow offenses have avoided the complaints of physical play. While more rough play may be tolerated in the post, the standard for a legal screen – both on and off the ball – has surely slipped from where it was 20 years ago, giving the offense an advantage it didn’t have in the past.

Additionally, it’s incongruous to think that the defense’s physicality is simultaneously slowing the game, but having no effect on the offense’s ability to score. And that’s what you have to believe if the defense is responsible for the pace trend. Efficiency has been stable, or even slightly rising over the past decade. Considering the lack of transition opportunities in the sport, offenses are having as much success in the half-court as ever. The fact that they are taking longer to shoot appears to be mainly of their own free will.

Defenses have contributed to the reduction of possessions by preventing transition. But even there, it’s not a one-sided transaction. Offenses still have influence over how much they run. A stingy transition defense like San Diego State is going to give up more fast breaks to VMI than Wisconsin. It would require more work to determine how much control the defense has here.

The shrinking of the shot clock will nudge some offenses out of their comfort zone, but for the most part the slowing trend in the game has been the offense’s responsibility. While cleaning up physical play may encourage offenses to speed up, the connection between the two is not exactly clear. The focus on contact two seasons ago resulted in an increase in pace early in the season, but by March it had crashed to pre-crackdown levels.

In a less physical universe, an offense that doesn’t worry as much about committing turnovers could be just as willing to hunt a while for the perfect shot. While nobody, myself included, is expecting a transformative change in pace this season, it appears the most direct way to speed up the game is to bring the shot clock in line with the rest of the world.

Below are the year-by-year results of the offensive control of APL since the NCAA made comprehensive play-by-play data available in 2010. It’s interesting that there’s a consistent (and linear) home court affect. Offenses tend to play slower at home, perhaps because they are leading more often and strategic effects come in to play. Or perhaps it’s because the road team is making more mistakes, resulting in more of its possessions ending prematurely.

Year  %Offense  HCA
2015    81     -0.1 sec
2014    86     -0.1
2013    86     -0.1
2012    88     -0.1
2011    87     -0.1
2010    88     -0.1
AVG     86     -0.1

And here’s a summary of the findings to date.

Offensive Spectrum – Ordered by pct of offensive “control”

FT%  98%  (HCA=0.5%)
APL  86%  (HCA=-0.1s)
???  83%
???  73%
???  72%
???  71%
???  64%
???  59%
???  50%
???  49%
???  36%
???  30%
???  15%