Comments on: 2009 BABIP-xBABIP Splits

By: Andy Brunn

Andy Brunn — Fri, 08 Jan 2010 00:15:10 +0000

A large % of the “over-achievers” have above average speed and a large % of the “under-achievers have below average speed. This fact will account for a lot of the discrepencies in the numbers. Hanley Ramirez does does not need to hit the ball as hard as Jason Giambi in order to get a base hit. I think these numbers will always be skewed due to this fact and I do not think it is an accurate predictor of the next seasons batting average. I would discount all of the people from the “over-achievers” list that have above average speed in terms of predicting next year’s average. I would also do the same for all the players in the under-achiever” list that have below average speed. However, a guy like Pablo Sandoval, who is an over-achiever with below average speed, is probably due for a letdown. A guy like Ryan Spilborgh, an under-achiever with above average spee, is probably due for a spike in average.

By: David MVP Eckstein

David MVP Eckstein — Wed, 06 Jan 2010 09:06:25 +0000

When you calculated this data, what did you use as a base team from which to project xBABIP? I did something similar with excel and used the Kansas City Royals as the base team (Kaufman stadium had the most neutral park effect in 2008 and the 2008 royals were 18/30 in terms of cumulative fielding ability).

Suggestions to make a better excel chart? Also, can you make the GB/FB/IFFB data sortable? I had to estimate these specific figures using GB%/FB%/IFFB% and they are not quite right (ie, Eckstein’s estimated GB figure is 211.6, while his actual number is 209).

This resulted, for example, in my HanRam xBABIP being .323 rather than .319.

By: Chris Dutton

Chris Dutton — Tue, 05 Jan 2010 20:41:45 +0000

Hey guys, this spreadsheet let’s you look at all xBABIP (and adjusted lines) for all players in our database (if it’s locked, use the password “tuftsbat”):

http://www.hardballtimes.com/main/fantasy/article/simple-xbabip-calculator/

Derek Carty and I are also putting together a revised, more comprehensive dataset in order to refine the model, so expect to see a second iteration in the next few weeks.

-Chris

By: Cody

Cody — Sun, 03 Jan 2010 16:43:53 +0000

Bobby, my understanding of ESPN park factors is that they are derived by comparing home rates vs road rates for the home team, and park rates vs average rates for road teams.

So to use your example, a home team with a lot of flyball pitchers wouldn’t affect the HR park factor, since it’s based on how many more (or fewer) HR’s that pitching staff gives up at home than on the road — not just how many HR’s above (or below) average are hit in that park for the year.

The Red Sox and Mariners serve as decent examples, as their staffs had the 2nd and 3rd highest FB%, respectively, in 2009 but Fenway and Safeco played as the 10th and 3rd worst home run parks. Since the park factor is similar to looking at home-road splits, at least a few seasons of data is required to make a determination of the true park effect, which accounts for the annual swings you mention.

I agree that it is difficult to say whether the THT study is based on the same methodology.

By: Dan Budreika

Dan Budreika — Thu, 31 Dec 2009 05:52:00 +0000

Oh so I’m guessing David G. used the formula you had there to compile his own spreadsheet posted above since your link doesn’t work at your post.

By: Bobby Boden

Bobby Boden — Thu, 31 Dec 2009 02:54:06 +0000

I’m not exactly clear on the exact details of their study, but it seems to me like it would be really difficult to factor out other non-ballpark factors that seem much more likely to effect strikeouts in a given ballpark. Some pitching staffs are going to be more likely to give up more strikeouts, and some teams are going to be less likely to strikeout as well, how do you truly factor these out? I don’t think that ESPN’s ballpark factor does a good job of doing so, based on how much so many of their ballpark factors change from year to year.

Homerun ballpark factors are the same thing….if you go back and look at previous years history, a lot of ballparks will go from a homerun ballpark, to a pitcher friendly ballpark (the twins stadium if I recall is one).

I believe all they are doing is taking the # of K’s, Homeruns, or whatever for visiting team, and the home team (and giving more weight to visiting teams). Doing this, is going to be highly prone to error, because the home team’s batting, or hitting skill will surely play into those numbers (and that changes every year, unlike the ballpark itself).

Anyway, in summary, I’m just skeptical as to how good these various ballpark factors are, and how much they are really indicative of the ballpark itself, and not just a factor of something else. For instance, if a team has a ton of flyball pitchers on their staff, that’s going to drive the ballpark HR factor way up, no matter what the dimensions are. Same with strikeouts, Walks, etc.

By: joser

joser — Thu, 31 Dec 2009 01:14:00 +0000

Actually, according to this study at Hardball Times park factors affect just about everything -- including unexpected things like singles and walks and even groundball rates. Intuitively you wouldn't think that to be the case, and nobody seems to have a good explanation, but the data apparently supports it. I'd love to see a park factors adjustment that incorporates this data (as well as their home run park factors) because our current crude park factors don't seem to be adequately modelling their effect.

By: Scottwood

Scottwood — Thu, 31 Dec 2009 00:56:03 +0000

Is there a place where we can look at xBABIP for all players instead of just this listing of players?

By: Bobby Boden

Bobby Boden — Wed, 30 Dec 2009 21:54:46 +0000

Sorry about the google docs link, I guess it doesn’t work the way I had hoped (I can’t seem to just make a spreadsheet available to anybody who wants it). The data here is much more interesting then what I’ve got in that spreadsheet anyway (and the download should work I believe).

I guess I’m contradicting my initial post a little, but I’ve done a lot of thinking, and research since I wrote the original article, in my defense. I do currently believe that ballpark factors are worked into the calculator, at least somewhat, but probably not completely. A big outfield probably accounts for more fly balls dropping for hits, and that’s not factored in anywhere for instance. It’s only built in, as much as it’s built into the batted ball data that I’m working with allows. If I had access to an outfield flyball hit % that would help even more incorporate park factors.

By: Dan Budreika

Dan Budreika — Wed, 30 Dec 2009 20:45:10 +0000

I got this from the link of your article introducing the calculator:

“It’s worth noting, that I’m not taking into account ballpark factors (which surely have some kind of effect on BABIP as well)”

I do see how they are kinda incorporated in the %’s from your last post. But you don’t use the ESPN or Firstinning or some other park factor?

And when I try opening the link to your calculator why does it say I do not have permission to access this spreadsheet??