Moneyball, Activism, and Policing

Every day, I wade through more anti-police rhetoric. After the Kyle Rittenhouse verdict, an article catches my eye on Twitter. I post a comment. And, as will happen, some random guy with an axe to grind finds my comment and replies.

"Problem is," he says, "Rittenhouse never would have gotten a trial if he'd been black. The cops would have gunned him down on the spot." As proof, he submits a photo with headshots of 12 people, 6 white and 6 black. Under each white person the caption reads, "heavily armed, arrested." Under each black person, it says, "unarmed, murdered."

I know this conclusion is widely-held in my left-liberal circles, some of them family and close friends. Problem is, in my research I've studied bodycam footage of a few hundred U.S. police shootings. For each headshot in the photo, I vividly recall several cases where the opposite happened.

It's not that I disagree. The cases I recollect are anecdotal too. But I don't agree either. I simply don't know and will suspend judgement until I do. My journey toward knowing is painstaking and data-based. To really know, means doing the science and following the data to where it actually leads, without imposing my values and assumptions. That's the Moneyball way.

Moneyball is a movie based on a book of the same name by Michael Lewis. It's a nerdy-cool story: baseball (starring Brad Pitt) meets data-science (starring Jonah Hill). The scientific foundation is Sabermetrics, a unique method for analyzing baseball statistics developed by Bill James.

In the movie and book--both based on a true story--the Oakland Athletics baseball club is struggling against teams like the New York Yankees with 3x the budget. Since Oakland can't pay top dollar for proven players, they have to develop. But as soon as they've created a star player, he's inevitably lured away by a big-money team.

So, Oakland discovers Sabernomics and uses it to help them find undervalued players and tactics. For example, by conventional baseball wisdom, batting-average is the most trumpeted statistic. Accordingly, players with high batting averages attract the most attention and command the highest salaries.

On the surface this makes sense. A successful hit is one that gets a player on base, and that may lead to the real goal, a run. So far, so good. Except that hitting isn't the only way to get on base. Getting a walk is just as valid. But wait, batting average doesn't include walks. For those, we have another statistic, on-base percentage, which accounts for both walks and hits.

Now, while on-base percentage is a better indicator of a player's productivity, it's less sexy and less remunerated. So, a player with many more walks than hits, might go unnoticed by the big-money teams. Unnoticed means lower cost, so potentially good value for a cash-strapped team like Oakland.

In other words, Oakland was using data strategically to develop unique competitive advantage. This required breaking with conventional interpretation of baseball statistics (how we've always done it) to find better, as yet undiscovered ways. The gap between conventional wisdom and true optimization is a distortion of reality. Oakland's new secret weapon was finding and correcting these distortions.

What does this have to do with today's anti-cop rhetoric? Well, word on the street is that policing is inherently brutal and racist. To prove the point, we're fed a steady stream of supporting cases. In response, millions have protested worldwide with demands to abolish or defund the police. Many protests have turned violent, featuring death, destruction, arson, and looting. In the aftermath, many city councils are rushing to scale back and reorganize police departments.

So, there's a large movement that's unhappy with policing and making things happen. What's wrong with that? Well, the big question is whether the direction we're taking is really where the evidence leads. Are we doing this the Moneyball way? Or are we knee-jerking (acting on premature conclusions) such that our solutions will cause more pain and suffering than the problem?