Ranking College Football Programs

If nothing else, sports enthusiasm is great for generating passionate debate about esoteric topics and hypothetical arguments. Within this realm lies the ever popular, hair-splitting activity of determining who is the greatest of all time. And college football is perhaps the most well attended of these masters of the universe feuds--for there can be only one.

You don't have to search for long to find many lists each with there own methodology. Here is one. Here is another. Here yet another. These all came from a quick Google search and all happen to have the Sooners at the top, but you probably can find lists with different results. 

Thinking about this topic myself but trying not to take too seriously any particular method of ranking (including my own), I have developed a ranking that is different from any I've ever come across. However, I believe it is more elegant and more defensible. My method uses historical average margin of victory to determine who's better, who's best. 

The reason this method may have a lot of credence is margin of victory (MoV) is a powerful determinant in predicting college football outcomes. In fact a simple MoV model adjusted for field neutrality can explain about 63% of the outcome in a typical FBS college football game. Keep in mind that this is not just predicting who will win but also by how much.*

So what did I do? Using the amazing data source from James Howell's page along with some supplemental data from the NCAA and College Football Stats, I compiled all the scores from all the college football games involving a Division I-A school for the past 43 years. Why start in 1970? Because that is when I started . . . but there is some foundation as that is around the beginning of the modern era of college football. Around that time saw the evolution of dynamic offensive strategies, the rise and proliferation of black athletes, the end of one platoon football (1966), and the beginnings of a more intrusive NCAA in the name of competitiveness. 

The results:

Since 1970, Nebraska is the clear leader. 

I include it through the top 26 since some would want to exclude Boise State from the rankings due to limited games played in the top level of college football.

Since 1998 (the BCS era):

Check out the workbook for yourself tweaking the constraints as you see fit. You can change the time period examined, the minimum number of games played to be included in the rankings, and the statistic you wish to sort by. 

*The out of sample prediction accuracy falls off some and the magnitude of the variance of outcomes matters such that the ability for such a model to beat Vegas (>~53% necessary prediction accuracy against the spread) is low (actual prediction accuracy ATS of between 51%-58%). 

WWCF: Self-Flying Plane or Self-Driving Car

Which will come first?

Self-flying aircraft commonly used over American airspace

or

Self-driving cars commonly used on American roads

This post is inspired from conversations with a colleague. We agree that these innovations are coming and that it will probably be in stages. I believe our ultimate predictions are in alignment as well.

The technology will likely be out in front of the legislation as is commonly the case, and the legislation will probably be waiting on public and special interest opinion as it commonly my contention. Yet encouraging signs have been seen. The FAA has approved test sites for aerial drones (a step toward but still shy of the subject here since today's drones are piloted albeit remotely). Similarly, Nevada, Florida, California, and to some extent Michigan have approved autonomous car testing on their public roadways. 

As for advancement coming in stages, my thinking is that regarding both public opinion and legislation there are fewer hurdles for package transportation than there are for human transportation. The first stage will be the delivery of cargo via self-guided vehicle. This might mean one method paves the way for the others and the other three follow suit together (e.g., a self-flying plane delivers packages for FedEx and then sometime after that self-flying planes for commercial passengers comes about just as self-driving delivery cars and personal cars/taxis are made available). 

That last example lends itself to my ultimate prediction on WWCF. Large-scale cargo shipments via plane have perhaps the most to gain with the least to risk in the self-guided future to come. Among the advantages are the economies of scale offered (routes no longer limited to pilot availability and scale in both vehicle and network), the limited natural enemies (taxi unions and personal-injury lawyers are more formidable than are the pilots potentially displaced), and the concentration of benefits (a few package delivery firms). 

I think self-flying planes will be with us to some significant extent within a decade and cars will follow ten years after that. The planes will carry cargo only for the first five years. 

So I predict we will soon be saying, "Look! Up in the sky. It's a bird! It's a plane! Yup, that's exactly what it is. A plane that self flies like a bird."

Update: I am reminded by the colleague mentioned above that there is another facet of self-flying planes that might in fact precede cargo delivery. That would be crop dusting. Search and rescue would be another use. The low risk of danger to bystanders might help these types of uses be the first mover.

Highly linkable

What happens when you combine hundreds of images of a sunset into one image? Magic.

Here and here are a couple of takes on photos of the year.

I want to go to there.

It is actually logical, but reprehensible, that part and parcel of the NCAA's enforcement includes limiting universities' abilities to provide additional tutoring.

Here is Landsburg's latest puzzle. It seems simple enough. Once you've attempted, go to the solution--I got it wrong and stumbled initially to see how the solution was true.

The free market is this era's Galileo.

The world needs radicals like the late, great Nelson Mandela. In fact it needs them to be even more radical.

So you're telling me they help write the rules that they will later be forced to follow? Like I said at Cafe Hayek, which deserves a hat tip for the link: "So many people delude themselves into believing that regulation is some benevolent construct created from pure knowledge, guided by thoughtful reason, immune to bad intentions, and protected from unintended consequences. If only the sausage factory were so."

Cass Sunstein says we need Moneyball-like metrics for non-profits. I agree and would take it further. We pay them to solve problems. Not to fail by trying to hit an arbitrary size of administrative expense.

A degree in English does not necessarily mean you can speak the language of business or economics. And here are two more from John Cochrane on why there is hope for healthcare after Obamacare completely fails.

Finally, 2013 saw yet another great economist pass on to that higher utility curve in the sky. Walter Oi is remembered quite well here by Steven Landsburg.

Put Me In Coach

I beat up on coaches a lot. More in conversation than in this blog in fact. I've done my share of armchair, from the bleachers, and Monday morning quarterbacking. Allow me to defend coaching a little and relate some economic concepts to the coaching profession.  I want to focus on college football coaches and to use Oklahoma's Bob Stoops in 2013 as a specific example, but this applies in large part to coaches at all levels and in all sports.

Flat out, coaches have a tough job. Yes, many are very, VERY well paid to do this job. Of course, many more are not. The job is tough because it is high-profile performance judged by a vast sea of people who have much less information and skills and who tend to approach the issue from an emotional standpoint. (Not me, of course; when I am yelling at my TV, it is because of my passion for reason and logical decision making.)

A coach has to balance between running an on-going training program while producing output that meets consumers' high demands. The training program is comprised of the gamut from relative beginners to high-value-producing experts (I'd call them professionals, but this isn't that blog post)--all of them thrown into the same "classroom".

Let me use the 2013 OU football team as an example of how coaches face issues involving asymmetric information, decision-making under uncertainty, skewed risk-reward payoffs, and management of public and intra-firm relations.

Throughout Bob Stoops' very successful 14 seasons as Oklahoma's head football coach he has either had a high-profile, all-star quarterback or an inexperienced newcomer who struggled not just when compared to his high-profile predecessor but also in absolute terms. 2013 was of the latter variety.

As Stoops sought to replace the 4-year record holder Landry Jones, he was evaluating the options with many backseat onlookers. The obvious choice to many was Blake Bell, the two-year backup. But in late August Stoops awarded the 2013 starting job to freshman Trevor Knight. When Knight stumbled some in early games, the natives including me grew restless for Bell to be given a shot. A combination of a bad first half and a slight injury gave the natives what they wanted in the West Virginia game, and Bell performed well. But then a few games into his starting role, Bell too fell into a malaise. The offense stumbled contributing greatly to OU's losses to Texas and Baylor. A little in and out substitution between Knight and Bell over a couple of games ended with Knight regaining the starting job for the Kansas State game (a victory) only to exit the role at half-time against OSU due to injury. Bell came in and played well if not better than Knight. Oh, and the formerly third-string sophomore Kendall Thompson was inserted before Bell replaced him in the OSU game.

To say this wasn't according to script is an understatement. But the script isn't actually written by fan dreams. It is an emergent process governed by both luck and coaching decisions. The coaching decisions are governed by a couple of underappreciated forces--uncertainty and asymmetric information. Coaches know a lot, and I mean A LOT, more than the rest of us. They see these players in practice and in games and in replayed videos of both. They interact with them. They also have a game plan and a complex strategy of plays to accomplish that plan. We don't know the plays, the formations, the game plan theories, or how well or poorly the players fit into them all. Add to that the complexity that combinations of players will imply different outcomes. Oh, and players are living lives all this time meaning they simply aren't the same in Spring of sophomore year as they are in December of senior year. Oh, and coaches are humans with biases and informational blind spots. They are operating in a cloud of uncertainty. We are in a fog orders of magnitude more dense than coaches are due to the asymmetric information.

And yet we judge them and will call for their heads if too many of their decisions turn out "wrong". Was Knight the right choice for Stoops to make in August? In September it seemed like the answer was no. In October and November it seemed more and more like the answer was probably yes. In one half of one game in December (n = .5 for statisticians out there) the best we could say was, "Looks like it was a toss up either way". It took us as onlookers an entire season to finally say what we should have been saying all along. To wit, "The coaches probably are making the best choice available, and that choice is still a guess".

"Coaches are paid the big bucks to make those calls and get them right!" you say. Well, yes and no. What is "get them right"? Right as judged by critics--media, fans, detractors, players, administrators, donors, parents, etc. Coaches have many masters. Effectively managing the intra-firm (i.e., players, assistant coaches, administrators, donors, some fans) relations along with the public (i.e., media, some fans, detractors, other team's coaches) relations implies they have interests that may conflict with simply maximizing the probability of long-term winning. Their risk-reward payoff matrix is skewed to a degree that is hard to appreciate. Balancing this well is an art.

Reflecting on the Sooners' 2013 season has humbled me and caused me to appreciate the coach's job(s). I don't think it is just because I view the season as a success with hindsight knowledge (it would be judged a failure from an ex ante point of view). Trying to put aside how a last-minute comeback victory over Oklahoma State makes me feel, I think I would feel that Stoops did a great job in 2013 win or lose that game.

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What a country!

I've suspected this for some time, and I don't think it will be very controversial before too long except maybe among old-timers.

Mungowitz at KPC had a couple of very good ones worth reposting. Here is the first--graffiti unchained. Here is the second--close calls.

A few years back I did a 180 on antibacterial soaps, et al. because of reading and learning and doing some thinking about what makes the most sense biologically/evolutionarily. Megan McArdle has more to that end. (If I had been doing it back then, this could have been the fulfillment of my continual New Year's Resolution.)

Here is a very good summary on why we MUST END the senseless, horrific war on drugs.

I want to go to there.

The Regulator's Dilemma

Imagine two rooms: one is a group of consumers and one is a group of producers. For now the rooms are completely isolated from one another. As they are labeled, these two groups will interact in trade.

Now imagine a regulator whose job is to, well, to do something. The regulator has imperfect information but is guided by a few beliefs about the job to be done. The first is a belief that the job exists somewhere along the dimension of necessity, which extends from anti-necessary to necessary. At the extreme of necessary the regulatory job is required for a good outcome. Anti-necessary is not the same as unnecessary; rather it means the job of regulation is in fact destructive—that the execution of the regulatory job brings a clear net harm.

The second belief is about where the need exists. Is it the consumers or the producers who need "help"? Let's call this dimension need.

The third belief is that he as the regulator will do a good job of fulfilling the regulatory mission. Let's call this dimension effectiveness. This dimension obviously extends from positive to negative meaning he does a good job or a bad job regulating.

The regulator has limited resources in addition to imperfect information. He must make tradeoffs. The interaction of where his beliefs land on the three-dimensional grid of necessity, need, and effectiveness will determine how he approaches the job of regulator (of course, it may not just be his beliefs that guide that decision, but he is a good proxy for the fact that something guides those beliefs).

For example he can concentrate his efforts on the group of consumers. In this case he surveys the room of consumers with the underlying belief that 'there are people in this room who can't be trusted to make good decisions even if there is no fraud involved. I must protect those idiots from themselves.' Call this option 1.

Alternatively he can concentrate on the producers thinking 'there are people in this room who can't be trusted to act ethically. I must stop those crooks.' Call this option 2.

And of course there is the more likely option that he divides his efforts between both groups. Call this option 3.

Here are my thoughts:

• We unfortunately tend to view the job of regulation and regulators as highly necessary and highly effective. This means they punch hard and with impunity. The only thing left to decide is where they punch.
• Option 1 can be a realistic point of view or it can be a disgusting point of view. People do make poor choices—all the time, every day. But the magnitude of those poor choices matters. So does the incentive arrangement—who is in the best position to benefit from a good choice and hurt but learn from a bad choice. At the extreme this point of view relies on a paternalistic philosophy that assumes the best way to make decisions is through a poorly incentivized and poorly informed regulator. Free market processes are highly superior to a regulator if option 1 is our focus for regulation.
• Option 2 is the best case that can be made for regulation. There will be fraud and with it real blood. But again the role of the regulator can and should be limited here. The regulator can be a blunt and poor instrument for discovering and preventing fraud in all its forms including unintentional harm. Liability law via common law and contract law (both emergent processes) can be equal or better regulators than a pure regulator himself.
• Option 3 is where most regulation tends to land from the SEC to the FDA. And think about how the more dynamic real world plays out. The rooms aren’t actually isolated from one another nor are the groups mutually exclusive. Everyone is in one big room wearing multiple labels. The imperfectly informed regulator is going to look for the help of the relatively informed producers to help guide his attempts at helping consumers. He is asking people, some of whom are crooks and many of whom have ulterior motives, to structure and enforce option 1. He will also look to define fraud from the point of view of the “victim”. The relatively injured consumers (who will self-select among those who have suffered a harm—happy people don’t complain) will help guide the regulator. He is asking people, some of whom are notoriously making bad decisions but not bearing the full burden of those choices, to structure and enforce option 2. This is a formula for regulation that is anti-necessary, ineffective at all the wrong times, and fulfilling mythical needs.

Highly linkable

As we of historically unimaginable wealth prepare for a wonderful holiday season, it is important to remember that Americans (among too few others) enjoy a life better than any before.

Looking for a New Year's Resolution? How about becoming a Jedi Knight?

More help for the Pope.

Whether you are a libertarian or are critical of the libertarian ideal, you should read this to better understand what libertarianism, the ideology of against, is actually for.

Three more strong challenges for the minimum wage policy of pricing low-skilled workers out of jobs: here, here, and here.

What you think you know about the Great Depression that just ain't so.

With bureaucracy we get one small step forward for many hundreds back.

Playing the lottery may be hazardous to your health.

Remember my post on common things today that will horrify or simply humor future generations? Bryan Caplan has a similar post that does a great job identifying an example for each of the three major ideologies: conservatives, progressives, and libertarians.

And how about these guys with the deal of the century? (HT: Mungowitz)