College Football Tempo: (R)Evolution in Pace of Play

Mike Carter-USA TODAY Sports

The HUNH virus is spreading.

I provided a snapshot look at the data through Week 3 on Tempo/Pace of Play for the conferences and each FBS team last week. I found it a fun and interesting little project to do, but lacking in context. I knew that the Hurry-Up, No Huddle (HUNH) offensive philosophy has been adopted by enough teams that it surely had changed the overall pace of play some, but I had no idea by how much.

Quick Aside: An alert reader also pointed out a bit of an error in the Week 3 data. Apparently I subconciously decided to include Nebraska in the Big XII for old time sake. Fixing the error didn't make a big difference to the overall numbers, but it was amusing to see that it actually resulted in increased tempo figures for both the Big XII and the Big Ten. Says something about the contrasting styles of the two conferences, I'd say.

Looking Back

In order to gain some context for what is going on today with tempo, I went back and calculated average clock seconds elapsed per play for every team from the beginning of the 2008 season, up through the fourth week of the 2013. I could have gone back farther, but the NCAA did some monkeying around with the clock rules in 2006 and 2007 and the data from those years isn't really comparable to what has been going on since the '08 season began.

A few points on methodology are in order. First of all, in order to keep things comparable, I didn't include teams added to FBS after 2008. That leaves Georgia State, South Alabama, UTSA, Texas State and UMass out of the data set. If you are a fan of one of those programs and are dying to see the data on your team's pace of play--seek help immediately. Because you need it.  For the sake of apples-to-apples conference comparisons, I have presented the conference data as if all of the recent realignment shenanigans had happened before 2008. There are pros and cons to doing it that way. I felt the pros outweighed the cons. Plus, it was easier, which is the ultimate tie-breaker.

What that leaves me with is 600 (120 teams 2008-12) full team-seasons worth of data and 120 sets of 2013 data through four weeks. I am sure the numbers for 2013 will continue to move around a bit, but I think presenting them at this stage is still more informative than it is potentially misleading.

First, lets look at how all 720 data points look like when we drop them into a histogram because...hey, histograms are fun! And they are also a great way to get a visual sense of the distribution. The histogram below shows average seconds per play arrayed into bins of 1 second each.

The mean for the whole distribution is 26 seconds flat, and the median is slightly higher at 26.4 seconds. There really isn't a lot more to say than that. It is a distribution that has a normal-ish shape, but it is clearly a bit irregular. It is close enough to normal that thinking about a standard deviation is useful and the standard deviation here is 2.6 seconds. It is also clear that the tail of the distribution is a bit longer on the fast side, which makes sense. So there are a few teams snapping the ball really fast, a vast majority of teams in a broad middle that extends from 24-28 seconds, and a small handful of teams whose pace we could measure with a sundial (almost).

Things get a lot more interesting and informative when we start to look at the metrics by vintage. The table below does just that. What you'll observe generally is that the average and median are falling slightly each year, but the standard deviation is growing at a much greater rate.

This makes perfect sense, because while the HUNH offensive philosophy has defintiely become more mainstream than it was 5-6 years ago, it is still truly embraced by a minority of programs within college football. And the traditionalists are perhaps becoming even more greedy in their Time of Possession hogging ways as a tactical response. So we see increased divergence in tempo from what we saw just a few years ago.


Median


Avg

Std
Dev

# < 22.0 Sec/P

2008

26.8

26.7

1.9

2

2009

26.8

26.7

2.1

1

2010

26.7

26.4

2.3

7

2011

26.2

26.0

2.4

10

2012

25.6

25.3

2.7

14

2013

25.2

25.1

3.2

24

My favorite column in the chart above is the last one on the right. It shows the number of teams averaging a snap of the ball in 22 seconds or less by year. Admittedly that is a slightly arbitrary cut off, but it is in the neighborhood of 1.5 standard deviations below the mean and it rounded nicely so that you could line it up with the tidy bins on the histogram. A couple of fun factoids to consider: (1) team's that average less than 22 seconds per play make up only 8% of the observations in the data set, and (2) 41% of those observations are from this season.

That column really shows the explosion of growth in adoption of the HUNH philosophy. I dare say it is approaching exponential growth. However you feel about the HUNH, it certainly appears we are at the moment in history where it goes from a curiosity to becoming a real thing. If Malcolm Gladwell were here, he might say we are at a tipping point. But he'd also say a lot of other stuff that would be obnoxiously self-congratulatory, so let's just be glad he isn't.

Differences by Conference

Looking at the data by conference and by year is also pretty interesting. What becomes readily apparent is that while there was a pretty high degree of homogeneity across all the conferences in terms of pace of play back in 2008 and even 2009, broader adoption of the HUNH has definitely increased the differences between the conferences over time.

Conf

2008

2009

2010

2011

2012

2013

AAC

26.6

27.4

28.4

27.1

27.8

25.6

ACC

27.5

27.4

26.9

26.1

24.7

26.1

Big Ten

26.6

26.7

27.8

26.5

26.9

27.0

Big XII

26.3

25.4

24.9

23.0

24.1

23.3

CUSA

25.7

26.0

24.8

25.9

25.2

25.1

Ind

27.4

29.1

26.7

26.1

26.6

26.5

MAC

26.2

26.2

27.4

25.3

24.8

25.2

MWC

26.7

26.4

27.0

25.9

25.2

23.7

Pac-12

27.3

27.2

26.7

27.1

25.5

23.5

SEC

27.1

27.0

26.7

27.3

26.3

26.8

Sun Belt

27.7

28.2

25.9

24.7

24.9

24.4

Not surprisingly, the Big Ten and SEC have been the most resistant to change. There are still coaches in both of those leagues for whom a three wide receiver set is so racy that it borders on pornographic. Okay, save your angry comments, that was a touch of hyperbole. But the B1G (still not sure how I feel about that abbreviation) and SEC are relative bastions of traditionalism in today's college football landscape, notwithstanding Hugh Freeze and a few other miscreants.

At the other end of the spectrum, the Big XII is inhabited by a cohort of speed freaks (must...resist...meth...jokes) who seem to want to go faster every year. And the imperative to increase pace seems to be catching on throughout the whole Western US, with the MWC and Pac-12 hot on the Big XII's heels.

Of course the HUNH "virus" has mainly been spread (oh Lordy, what a pun) through "carriers" from the Mike Leach/Air Raid coaching tree or the Rich Rodriguez/Spread-to-run philosophy. But the recent adoption of the HUNH by coaches and programs with a slightly more traditional bent (e.g. Washington, Boise State) is perhaps a sign of things to come. Coaches like Washington's Steve Sarkisian and BSU's Chris Peterson have no historical association or affinity with anything Air Raid-y or Gus Malzahn-ish, but have decided, for one reason or another, that the HUNH makes sense for their programs.

The final graphic I'll leave you with simply shows the change in the median tempo of each conference from an average of 2008/2009 (baseline, pre-HUNH explosion) to the fourth week of the 2013 season.  It is interesting to me that witht the exception of the Sun Belt, you can really draw a distinction in adoption rates between the generally Western US and the East Central/Eastern. Of course, West Virginia is a HUNH team in the Big XII and it is only really West of Virginia, so there's that. I also can't help but be amused that the pace of play in the Big Ten has actually gotten slower.

Did I do something stupid (again) in my calculations? Is there a conclusion worth challenging or an obvious one I am missing? Let's talk about it in the comments.

Note: I'll dump the team by team data through Week 4 into a table later this week, if people are interested.

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