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.

We’ve previously talked about non-steal turnovers in this series, in which the offense had 59% influence. Forcing steals is clearly the more aggressive act by the defense and the offense has just 30% influence in this confrontation.

As we saw in the scatter plots from the non-steal turnover piece, there’s less of a connection between non-steal and steal turnovers on the defensive end than the offensive end. In other words, the team that avoids non-steals offensively also probably avoids having the ball stolen. This is not as true defensively.

First, let’s look at the coaches that have forced the most and fewest steals.

 1 Greg McDermott 7.6%
 2 Stew Morrill   7.7
 3 Bill Herrion   7.8
 4 Bob McKillop   8.1
 5 Mark Turgeon   8.1
 6 Scott Nagy     8.1
 7 Larry Eustachy 8.2
 8 Brian Gregory  8.2
 9 Rob Jeter      8.3
10 Jim Ferry      8.4

One way for a defense to help its offense is to get a lot of steals, but another way is to not put in the effort at all. McDermott, Morrill, McKillop, and Nagy have been renowned for their solid offensive units and this may be another example of getting more out of your offense by conserving effort on defense.

Here are the ten coaches with the best defensive steal rates.

 1 Mike Anderson  13.6%
 2 Jim Boeheim    12.6
 3 Rick Pitino    12.2
 4 Vann Pettaway  12.1
 5 Murry Bartow   11.9
 6 Blaine Taylor  11.8
 7 Joe Scott      11.8
 8 Derek Waugh    11.8
 9 Bobby Braswell 11.7
10 Bill Carmody   11.7

Honorable mention to Ralph Willard, who in eight seasons in my database averaged a 13.8 steal percentage. And Shaka Smart is at 14.7 with six seasons in the books. The way to a high steal percentage is to press, play zone, or ideally, both.

There is some judgment in recording steals and not surprisingly, the home team records more steals than the road team on average. How much of this is on the scorekeeper trying to boost the home player’s numbers and how much of it is a real home court advantage would require more analysis.

What I find interesting is that the home court advantage for non-steal turnovers is almost exactly the same. It’s inconceivable that a scorekeeper is cooking the books for non-steal turnovers, and turnovers as a whole are very difficult to fabricate, so it’s possible that a large majority of the home-court advantage in steals is an accurate reflection of what’s happening on the floor.

But here’s another theory: Both non-steals and steals benefit from different kinds of bias unrelated to the play on the floor. Steal totals for the home team may benefit from a scorekeeper boost and non-steals, which include charges and other violations, may benefit from…insert dramatic sound effect…an officiating bias.

Year  %Offense  HCA
2015     28     0.3%
2014     24     0.3
2013     29     0.5
2012     28     0.4
2011     25     0.4
2010     29     0.5
2009     33     0.5
2008     33     0.5
2007     38     0.5
2006     35     0.5
AVG      30     0.4%


Offensive Spectrum – Ordered by pct of offensive “control”

FT%  98%  (HCA=+0.5%, r(off)=.19, r(def)=.04)
APL  86%  (HCA=-0.1s, r(off)=.55, r(def)=.23)
3P%  83%  (HCA=+0.7%, r(off)=.12, r(def)=.06)
OR%  73%  (HCA=+1.1%, r(off)=.23, r(def)=.08)
3PA% 71%  (HCA=0.0%,  r(off)=.52, r(def)=.33)
A%   71%  (HCA=+2.6%, r(off)=.32, r(def)=.21)
PPP  64%  (HCA=+3.7,  r(off)=.51, r(def)=.36)
NST% 59%  (HCA=-0.4%, r(off)=.24, r(def)=.20)
2P%  50%  (HCA=+1.4%, r(off)=.26, r(def)=.25)
TO%  49%  (HCA=-0.7%, r(off)=.31, r(def)=.30)
FTR  36%  (HCA=+2.8,  r(off)=.20, r(def)=.27)
Stl% 30%  (HCA=+0.4%, r(off)=.21, r(def)=.32)
???  15%