BABIP Math

I still would like to see Teabag second right now. Ideally move Beckham up to 1. And for all things holy move Rios up to 5th. His early line drive rate is 22.5%. More Jones in LF please.

Baltimore LD% 16/ GB% 45.9 BABIP .265
Houston LD% 16.5/ GB 48.4 BABIP .258
Pirates LD% 17.3/GB 46.6 BABIP .280

Wsox LD% 17.2/GB 47.2% BABIP .220

along with their crap BABIP. and cold is approximately factored in because i used league average as of now, which is like 15 points lower than normal atm.

I’m sure there is a small (but not insignificant) effect thanks to the small park. You’ve got to figure that some would-be doubles are HR (which are not included in BABIP) and the relatively small outfield limits doubles, triples and singles in other ways as well.

If I was to guess USCF would have the the lowest (or in the bottom 5) BABIP park factor, while Fenway and Coors had the highest.

if we were really trying to do an exact p-value, we’d narrow it down farther since the Sox couldn’t actually make it outside the bottom three.

but let’s assume that everything is kosher with those stats. given 5500 AB, 1100 K and 160 HR and batted ball rates resulting in non-HR hits around something like:

non-HR FB – 15%
non-HR LD – 73%
non-HR GB – 24%

those numbers yield 4240 batted balls. if you trade 2% of batted balls that are normally landing for a hit 73% of the time for something that’s a hit 20% of the time, that’s a difference of ~40 hits per season, or the difference between a .300 and .290 BABIP for a team season. so it really doesn’t explain that much, since the Sox’ BABIP problems have been twice times that. of course, just because they are definitely bad doesn’t mean they are .280 bad. it’s probably more like .285. so maybe that plus the fact that the Cell suppresses BABIP is the difference maker.

but i would caution that, for example, 2008’s BABIP still sucked regardless of line drive percentage. but also, a lot of the research done regarding line drive percentage says that they’re fairly randomly distributed. the best hitters hit the ball hard, period and vice versa. that leads to less or more defensible batted balls based on the batter regardless of the categorization of the batted ball. and, like i said, there’s a pretty decent amount of error in the batted ball data. Colin Wyers had an article in BPro that was a little hyperbolic seeming but still had plenty of good data about the problem.

if line drives are fairly random, then what we should expect to see is simply hitters who don’t hit the ball that hard. 2006 was our last really good offense and, surprise, they didn’t have BABIP issues. i think it really is that simple, frankly. get good players and the rest sorts itself out.

unless it’s known he’s hurting. Never move him if he’s healthy.

http://kianakim.com/index2.html (NSFW)

I wouldn’t have to concern myself with all these stats either

It’s math. Why is it a crime to understand why some things are happening?

what do you want from me?

“ballyb makes unironic remarks about H-E-A-R-T”

i assume you mean nick swisher.

link

I see that his slider % 14.6 is much less than usual. Assuming a slider is something a batter is a little more likely to miss on anyone have a clue why he’s throwing more curveballs and changeups?

we sure don’t need any more of that