Using advanced stats for Fantasy - BABIP

Ichiro Suzuki is the king of BABIP. (USATSI)
Ichiro Suzuki is the king of BABIP. (USATSI)

Listeners of the Fantasy Baseball Today podcast are already going to be familiar with BABIP, so I apologize if I'm covering familiar ground. So, while this might be BABIP overkill, I think it's necessary. BABIP, which stands for batting average on balls in play, is arguably the easiest way to pick out whether a player is headed for regression or ready for a breakout. 

Stat: BABIP (Batting average on balls in play)

Where can I find it: FanGraphs and Baseball Prospectus carry BABIP.

What does it do: BABIP tells you a player's batting average on all the balls he puts in play. The acronym is pretty self explanatory in this case. 

I still don't understand: I seem to be sending you here a lot. Chris Towers also wrote up a post about BABIP last night that can help you understand how to put your knowledge to work.

How can I use it: Alright, here we go. BABIP is mainly used to identify which players are having poor or above average luck on batted balls. An average BABIP settles around .300, so players with higher BABIPs are due for regression, and players with lower BABIPs should see their numbers rise. Think about it this way. Let's say Player X goes 0 for 4 during a game, but two of those outs were screaming line drives. Though he made strong contact, he was unlucky to have hit the ball directly at players. Eventually, those balls start falling for hits, and his numbers rise. Player Y, on the other hand, went 2 for 4, but his two hits were weak bloopers that managed to fall between two fielders. At some point, those balls turn into outs, and that player will see some decline. 

It's important to note that the .300 baseline isn't really the best way to utilize BABIP. I prefer to look at career rates for hitters. The truth is, some players are prone to higher or lower BABIPs based on their batted ball profiles. Adam Dunn puts a lot of balls in the air. While this leads to home runs, it also leads to a lower BABIP than normal. So, if Dunn's BABIP is around .265, you shouldn't expect it to jump to .300. On the other side, Ichiro Suzuki dominated BABIP for a long time. His ground ball approach, combined with his speed, helped him beat out more balls than the average player. His career BABIP is .344, far above the normal baseline. You'll have a more accurate picture of a player if you look at career rates.

Example: Check out Chris Towers' piece I linked to above. Towers did all the work for me, so I'm just going to tell you to click that link. There's also rarely a day the guys don't mention BABIP on Fantasy Baseball Today

What are the problems with this stat: As I outlined above, the .300 baseline isn't the ideal way to utilize BABIP. Certain hitters will typically always post higher or lower BABIPs based on their approaches at the plate. Speed typically leads to high BABIPs. Fly balls lead to low BABIPs. While BABIP tends to even out over the course of a season, that's not always the case. Chris Johnson had a .394 BABIP in 2013. Everyone predicted that would come down during the season, and it never did. Some players can get lucky for an entire year. It happens. They tend to regress the following season, though.

Anything else: I think we're good here.

Next post: We'll look at strikeout rate and batted ball data for hitters. 

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