Introducing People to Sabermetrics
I love baseball, and I enjoy the objective analysis of baseball, otherwise known as Sabermetrics. I consider it a higher form of baseball enjoyment. I can be in the game, yelling at the umps after a bang-bang call at first base. But most of the time, I’m analyzing a player’s mechanics, his advanced statistics, or considering front-office decisions. Often, this has led me to step back from raw fandom and enjoy the uniquities of the game, like just watching Chipper Jones effortless swing, or focusing on the intensity that Craig Kimbrel pitches with, or seeing Kris Medlen’s deceiving pickoff move. For the record, I’m a Braves fan, born and raised in Atlanta.
When I meet people, I like to introduce them to this. I want them to understand why I find that Baseball is the most interesting sport. This is probably ironic to some people, who feel that Baseball is the least interesting major sport. But there are so many intricacies and ways to approach the game: fan, scout, front office, manager, pitcher, hitter, saberist, etc. Each perspective has its own way of thinking about the others and about the game itself.
When I start to indoctrinate a casual fan, the first thing I have to dissuade them of is the notion of Batting Average is in any way valuable. Most fans know it is flawed, but they still use it as a proxy for “good”. This is a false assumption. Batting Average is the 2nd worst conventional stat in current use (second only to Pitcher Wins). Why? The first thing a new convert to sabermetrics has to understand is that hits are heavily influenced by randomness. The difference between a liner and a fly-ball is a matter of millimeters in bat or ball position, milliseconds in timing. The human body is only capably of so much precision (in fact, we are precise in very little in our daily lives: its what makes engineers so unique, the ability to be precise when our nature doesn’t conform). Certainly some batters hit more liners than other, but once you consider the additional randomness of position players fielding the ball, it is even more hairy.
Ok, so what does random influences in Batting Averages mean? Of course, some players still have high batting averages every year. For instance, Ichiro has always held one of the best Batting Averages each year for the prime of his career. He is certainly not a random occurrence. Randomness, instead, means that there are wild variations in year-to-year BA (Ichiro over the years: .312, .372, .303, .310, .322, .351). You can see that some years he is mortal and some he is incredible. It is reasonable to assume he is not a very different hitter in the .372 year versus the surrounding years. Thus, it would be wrong of us to judge Ichiro on his .303 year, because he is clearly better than that. The same goes for any time we use BA without a large sample size (think at least 2 years).
The second big detractor of Batting Average is how its calculated. It counts home runs and singles the same. For a player like Dan Uggla or Jose Bautista, this is a travesty. Because it doesn’t weight each hit appropriately (and completely ignores walks and subtracts for errors), we can conclude it is not a good value metric (that is, it does not accurately represent the value of players). What it does measure is how much of the time a hit is made, which is good thing when in runners in scoring position situations (because singles become more valuable than walks in those situations).
Once someone understand what Batting Average is, and what it is not, they can start to think about the game in a new light. Hopefully, they’ll dig deeper, but maybe not. At least, they’ll know not to say “He’s not even hitting .300” anymore.