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Remember high school math?

When I was in high school, that was a world of calculators, equations, and solving for x.

Solving for x was fine for my brain, but when there were more variables, like a, b, c, and d, things quickly became desk-poundingly complex to manage, follow, or undertand. Only the very gifted and hardworking (those to make a lot of money now, but in high school were feared, and, if applicable, ridiculed for their lack of athletic prowess) really got that stuff.

When you tried to apply the fairly simple math that I learned in high school to real world issues, it always seemed impossibly simple. It just couldn't account for nearly enough variables. 

For instance, if you wanted to use my high school math to come up with a little graph of how many people are likely to come to school on any given day in the future, you could make some graph based on some equation. But then you throw in things like: What about the summer, weekends, and Christmas and spring breaks, when nobody comes? What about the winter, when lots of people are sick? What about the school district's plan to send a third of the kids to a new school down the road? What about fluctuations in local populations? What about ...

All those things would inform your graph, if your graph was to be really stellar. But they were all well beyond the math I could understand.

But have you heard about computers?

They don't mind all those variables. In fact, they eat them for breakfast.

And computers have been around math classes for a while now, which means a whole big mess of people out there have been tinkering with complicated equations from a young age. 

Turns out some of them have gotten pretty good at it.

The result is that the very pleasing "I don't care what the dumb numbers say, I'll use my own eyes, thanks" stance is looking to be a dumber and dumber approach every day. 

There just are, now, a lot of things you get to prove with evidence that you once had to guess at.

In baseball, for instance, stuff like who is a better fielder used to be about measuring a guy's arms, looking at highlight reels, and nodding with the wisdom of the ages. Now you can actually know of all the balls that were hit into his area, how many did he catch? How does that compare to the rest of the players at this position? 

You can stick with the old arm measurement and nodding thing if you want. But it's not doing all you can do to know what's going on. Not in this day and age.

Baseball, of course, a slow game of isolated and well-charted interactions, was an early beneficiary of this kind of math. It's pretty easy to study.

Basketball, it has been said, is too fast and complex to really put into meaningful numerical form.

And maybe that's true. Maybe you can't build a model to replicate the entire game. But I'm willing to bet you can dive deep enough to learn a lot of useful stuff.

Let me ask you this: Is basketball more complex than healthcare?

Because I learned from a most unusual Op-Ed in The New York Times today, written by -- quite a list -- Billy Beane (famous for being Oakland A's GM and star of Michael Lewis' amazing book "Moneyball"), Newt Gingrich (famous for being Newt Gingrich) and John Kerry (famous, I have just learned from the internet, for playing acoustic guitar with Kiss) -- that statistics can be very effective in making even healthcare more effecient. They write:

Look at what's happened in baseball. For decades, executives, managers and scouts built their teams and managed games based on their personal experiences and a handful of dubious statistics. This romantic approach has been replaced with a statistics-based creed called sabermetrics.

These are not the stats we studied as children on the backs of baseball cards. Sabermetrics relies on obscure statistics like WHIP (walks and hits per inning pitched), VORP (value over replacement player) or runs created -- a number derived from the formula [(hits + walks) x total bases]/(at bats + walks). Franchises have used this data to answer some of the key questions in baseball: When is an attempted steal worth the risk? Whom should we draft, and in what order? Should we re-sign an aging star player and run the risk of paying for past performance rather than future results?

Similarly, a health care system that is driven by robust comparative clinical evidence will save lives and money. One success story is Cochrane Collaboration, a nonprofit group that evaluates medical research. Cochrane performs systematic, evidence-based reviews of medical literature. In 1992, a Cochrane review found that many women at risk of premature delivery were not getting corticosteroids, which improve the lung function of premature babies.

Based on this evidence, the use of corticosteroids tripled. The result? A nearly 10 percentage point drop in the deaths of low-birth-weight babies and millions of dollars in savings by avoiding the costs of treating complications.

Another example is Intermountain Healthcare, a nonprofit health-care system in Utah, where 80 percent of the care is based on evidence. Treatment data is collected by electronic medical records. The data is analyzed by researchers, and the best practices are then incorporated into the clinical process, resulting in far better quality care at a cost that is one-third less than the national average. (Disclosure: Intermountain Healthcare is a member of Mr. Gingrich's organization.)

Evidence-based health care would not strip doctors of their decision-making authority nor replace their expertise. Instead, data and evidence should complement a lifetime of experience, so that doctors can deliver the best quality care at the lowest possible cost.

So, what does all this mean?

If math can be helpful in the health of millions of humans, it can certainly help in something as simple as basketball.

I think it means that all those teams out there that are contracting with various statistical experts, and actually listening to them ... they're going down a road that is promising. Over time, I think they'll find some nuggets of wisdom that will make them smarter.

And those teams that are just doing things the old-fashioned way, using only old-fashioned box score statistics, at some point they're going to suffer from their lack of knowledge.

UPDATE: Extremely relevant: ESPN's excellent Eric Neel on how Daryl Morey and the Rockets are putting statistics to work in Houston.