clock menu more-arrow no yes

Filed under:

Intermediate MLB DFS: BABIP

We continue our breakdown of the basics for MLB DFS. In this section, we look at BABIP, with definitions and some basic strategy.

Yoan Moncada #10 of the Chicago White Sox bats against the Kansas City Royals on March 8, 2020 at Camelback Ranch in Glendale Arizona. Photo by Ron Vesely/Getty Images

In daily fantasy baseball, like in most things, getting the fundamentals down is integral toward laying a foundation of knowledge to build from as you progress as a player. For DFS, that means understanding how the BABIP statistic can help you build your lineups.

BABIP

Definition

BABIP, or Batting Average on Balls In Play, tells us how often a player hits the ball in play and what happens with that ball. Getting the ball into play is the toughest part, what happens after that is often based on luck. BABIP helps us understand if a player has been lucky or unlucky.

Strategy

Hitters

On average, hitters put up around .300 in BABIP, with top hitters landing around .340 and poor hitters around .260. The actual number isn’t as important as the difference between recent BABIP and longterm or average BABIP. This stat is one of the few that can be useful when looking at small sample sizes, as it helps show if a player’s recent production has been based on good or bad luck. But, we also want a large sample size to see where a hitter’s average BABIP has leveled out. A longterm BABIP baseline will help us see if a hitter is poised to get luckier or unluckier moving forward.

Daily vs. Yearly fantasy

The question here is, will BABIP help us in the short term, as in one DFS slate or is it more useful for season long leagues? On the surface, it makes sense to lean more toward BABIP numbers in season long than DFS, as players with a higher or lower BABIP than their career average can be said to be on a hot or cold streak and betting against their current streak would be counterproductive. But, when it comes to streaks, there is very little evidence that they are real things.

It is difficult to deny the existence of streaky play, as we see players put up extreme numbers way above or below their averages for a week or even a month. The problem is, those numbers are impossible to contextualize enough to say what is causing them. Are balls put into play just missing gloves? Has he seen a parade of poor pitchers bunched into a few weeks? Are we framing his “streak” in ways to make it look better than it is? Complete randomness often looks streaky and basing our picks off something that may have little support while also picking players who cost more because they’ve been on a streak, isn’t optimal.

If we can cut through the noise of streakiness, we can then stick to stats that are stable and will help us in the longterm. We know that BABIP will level out, an in doing so, a hitter will, on average, put up numbers moving forward that push him to that average.

Pitchers

Pitchers also have an BABIP statistic, but it is based on what hitters accomplish against them. Pitchers don’t have as much control as hitters do over what happens once a ball is put into play. Their BABIP will fluctuate based on defense as well as their own ability. To get a good view of BABIP for pitchers you’ll need a good baseline, which means a couple years of starting pitching stats and a stable defense.