A Look At Luck: BABIP

Since the beginning of baseball, people have been trying to quantify a player's contributions to wining games. Traditional stats were batting average, runs, rbi's, and home runs. Today, more in depth statistics are being created, those mostly fall under the umbrella of sabermetric stats.

I have found, that there are two basic ways to categorize all hitting stats - both traditional and sabermetric. There are stats that attempt to quantify a players performance, simple ones are runs and rbi's. And then there are stats which try to determine if a player deserves their performance stats, which I call "luck stats." BABIP is an example of a luck stat.

So there are performance and luck stats. When comparing two players, the most basic way to compare them is by their performance stats, who has more runs, home runs, runs batted in - very basic stuff.

But here at the Baseball Aspect, we are more complex. We know that sometimes a players performance stats do not tell the whole story, so we must look deeper, into their luck stats. And today we will look deeper into one luck stat, BABIP.

BABIP stands for batting average on balls in play. It is the average of balls hit in play that fall for hits. The formula I use for it is (H-HR)/(AB-K-HR+SF). The SF stands for sacrifice flies.

This is a very basic measurement, but who said there's anything wrong with simple? The league average for BABIP is .300, so if a player's BABIP is .410, you can expect a regression in his performance stats.

This elevates your knowledge over someone who only pays attention to performance stats. So, for example:

Player A - .330 batting average
Player B - . 280 batting average

A person only looking at performance stats would say, Player A is clearly superior to Player B, however if i were to include that Player A's BABIP was .425, and Player B's was .275, then most-likely Player B would see their batting average go up, and Player A's go down. Small reductions in a players' BABIP can dramatically influence a players batting average. In fact, if I adjusted both players' BABIP to the league average .300, Player B's batting average would surpass Player A's.

This a very basic example, but that is exactly how you would go about finding players who have gotten lucky so far, and those who are bound to get better. Once you increase the amount of balls in play that fall for hits, a players runs, rbi's, steals - all those fantasy stats we love - will go up.

So now there is no more guessing whether a player is just plain bad, or whether he's simply been getting unlucky. This is great for trading in fantasy, because you can trade overachievers for underachievers, and get great production from those underachievers the rest of the season.

Unfortunately, BABIP is not that simple. This may be mind boggling, but a player's BABIP can be lucky. Think about that. . .a "luck stat" can be lucky. I'm not gonna go into that today, but I will surely talk about that soon.

All up-to-date BABIP numbers can be found at, of course, The Hardball Times.

I advise my readers to apply this when they evaluate a player. Apply what you learn!

Cheers!

Paul