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Batted_Ball
Monday, March 08, 2010
I always say that FIP is one component of pitching, much like OBP is one component of offense. What you should really do is break up the entire pitching line into its components, and see what you get. Studes for example has been doing this for a few years with his fantastic batted ball reports.
Now, Peter takes the same idea, by breaking up RE24 into various components. He also says this:
The other interesting aspect of the chart for me was the variety of run values for hit-ball runs. Remember these have already been adjusted for the quality of the defense on the pitcher’s team, so what remains should be mostly luck according to DIPS theory. If so, they should regress back toward zero with multi-year sample sizes. You’ll have to wait for Part 2 to find out if they do.
Not to spoil his fun too much, but I split up WPA by batted ball and non-batted ball events on my old blog at Primer:
also present a WAA2 column that assumes that 100% of the BIP goes to the pitcher, just so that you can see what the difference is. Not much is the short answer.
Here’s the top 20, and the bottom 10. I’m sorry, but for the moment, this is all I’m prepared to present.
pitcherid WA LA WAA WAA2
johnr005 83 60 23 24
martp001 55 35 20 21
schic002 67 54 13 14
maddg002 67 55 12 13
...
So, I’m all on-board with what Peter is trying to do, and what the original poster he quoted is saying: instead of discarding data, keep it all, partition it, and massage each partition. A component-based analysis that treats each component separately, and presents it separately, is the best way to show a pitcher’s performance line.
This is true of everything, and even to things like Plus/Minus. You want to show the who and the how that someone can have a +20 while someone else on the same team, possibly a better player, can be a minus 5. Split things into components, and work things from there.
Make sure everything adds up.
Friday, March 05, 2010
Good stuff from Pizza over at ESPN (and presumably soon at BPro):
Bradley’s inability to make contact with balls out of the zone in 2008 meant that when he did hit a pitch, it was a better pitch and he was able to hit it harder.
Pizza shows part of the data here from Fangraphs. O-Swing is swings at pitches outside the strike zone. Z-Zwing is swings at pitches inside the strike zone. Lots of good stuff in there, and Pizza gives us a slice of Bradley.
Wednesday, March 03, 2010
My. Oh my. Oh my. Courtesy of Sean at Katron.org. This image is Safeco batted ball imposed onto Fenway. Yeah, I know. Coooool.
(All you guys are so ~!@#$ awesome. Seriously. I’d put a hundred of you guys into a blender and create the perferct sabermetric monster.)
Saturday, February 27, 2010
Very cool stuff.
Tuesday, February 23, 2010
Great job by Harry:
The alarming issue? In a word, Huntsville. In a sentence, the Huntsville stringers stopped producing line drive tags early in 2009, using fly ball and ground ball only.
Friday, February 19, 2010
There was some great work done here, by a few of the commenters. I highly recommend reading it all the way through.
Tuesday, February 02, 2010
Good work by Harry:
Ignoring rookie ball, a five-point drop in ground ball rate appears to get picked up mostly by line drives over fly balls by nearly four to one. That’s important, as a ground ball turned into a line drive is about three times as costly as one turned into a fly ball. I know stuff is being redistributed in various directions across batted ball types, but it ends up as I’ve described.
As we know, the run value of a groundball (in MLB) is about the same as the run value of a flyball (if we exclude HR). Once we include the HR, the run value difference is about .15 runs. So, it would be interesting to see what happens to GB pitchers in the minors, whether the conversion of GB to line drive is general (in which case we don’t have any worries), or specific to kinds of pitchers. The difference in run value between a GB and LD is about .45 runs, and that’s enormous.
So, an aging trajectory chart of GB, FB, LD, Pop rates, from minor league to MLB. Great idea, Harry!
Tuesday, January 12, 2010
Here you go, with a comment from Alan Nathan:
In my own analysis of hitf/x data from last year, I pretty much confirm what Brian says about how BABIP depends on the vertical launch angle. Based on analysis of nearly 15k batted balls, I find that if the speed off bat is larger than about 80 mph (a rather modest number), then BABIP peaks in the angular range 10-15 degrees, with BABIP exceeding 85%. If you actually look at the trajectory of a ball hit at 85 mph, 12.5 deg, it lands about 240 ft from home plate with a hang time of 2.6 sec, so falls in front of the outfielders with high probability. Also, it eludes the infielders, since it is too high for them to catch (it is about 18 ft high when about 100 ft from home plate). The maximum height is a bit larger, ~20 ft. Whether you call it a line drive or something else is a matter of semantics. It is a very well-hit ball. If you look at home runs, then the home run probability peaks with a launch angle in the 25-35 deg range.
The message seems to be pretty clear, at least to me. If you want to get on base (as opposed to hit a home run), keep the launch angle low.
Unfortunately, there is not enough data that has been released to look at these numbers in a statistically meaningful way for specific hitters.
Friday, December 04, 2009
First, I will have to give out my nah-nah-nah, toldyouso. If BIS and STATS and MLBAM had simply listened to me all those years ago, and simply gave everyone a g-dd-mn stop watch, we wouldn’t be in this predicament. We don’t need to know if the ball was 2.3 or 2.35 seconds in the air. I’d be happy if the measurement error was even 0.5 seconds (which is huge considering that a pitch thrown from the mound to the plate takes less time than that). But no, I’m told, you don’t solve a problem with a regular hammer, when a jackhammer is more powerful and costly and harder to implement.
Now, here’s Colin showing us, with data, that a pressbox that is 45 feet high will have a 32% line drive rate, while one that is 65 feet high has a 36% line drive rate. But, at below 40 feet and above 70 feet, it might be different, because things don’t always follow a linear rate, and guys at extreme levels might rely on different methods to figure if a ball is a line drive or not.
I love the article, and I love any light that shows that data collected as a discrete value is not always “objective”.
Wednesday, November 25, 2009
By , 09:30 PM
His name is Jeremy Greenhouse (I never heard of him before).
http://baseballanalysts.com/archives/touching_bases/
Wednesday, September 30, 2009
Ah, this I like:
The bottom line is the horizontal location of the pitch (from the catcher’s view point, so a lefty hitter is on the right side, and the +1 means a pitch inside), and the top line is the angle of the HR (-45 is 3B and +45 is 1B). He also color-coded the lines by pitch type (legend not provided). So, for example, we see that the red-pitch (whichever one that is, let’s presume it’s a changeup) was thrown inside 4 times for a HR, and never outside.
It takes a little getting used to. If you look at the first red-line, you see that the horizontal location was near the middle of the plate, and the spray angle was around 30 degrees. The last red-line was thrown way inside, and had a spray angle of 45 degrees. But, the visual line you see is actually a sharper “angle” for the first line. So, that part is confusing. The visual angle you see of the line itself is meaningless: what we care about are the two endpoints that link the line.
Thursday, September 24, 2009
Matt presents SLG on balls in play (excludes HR).
Some of you may remember when Dan Fox released his BIP spray chart app, and I suggested adding “wOBA on contacted plays”. What Matt is doing here is similar in spirit, in that you want to count the doubles and triples differently from the single.
You simply could do a wOBA and exclude BB, HB, K, HR. That means setting the single and reaching on error to around .9 and a double or triple to 1.3 (or use the .90, .92, 1.24, 1.56 numbers from The Book). If that is too much, you can try to combine baBIP and slgBIP ala OPS.
Since we know from wOBA what the target coefficients need to be, then a weighting of .55 for baBIP and .35 for slgBIP does the trick in terms of aligning it to wOBA. That gives you the proper balance, and sets it on the baBIP scale (average of roughly = .300).
Friday, September 18, 2009
A well-written well-styled but poorly researched piece on the background of PITCHf/x… except for the last two paragraphs which do not follow the script leading up to it:
Fast forward to the 2010 season and beyond, should a Jeter-like prospect become available. He may never have a shot to ever play in MLB, for not only will he not necessarily fit the statistical profile, but scouts may no longer be considered useful to MLB clubs.
And what a shame it would be for the game of baseball to lose those intangibles which contribute to the elements of its mystique. And it is through its imperfections that allow for a new script for every game played, making us ever more appreciative of its outcome and yet continually indebted to the human element in its sport.
Indeed, the author had a fairly good command of the subject material, but in no way is her conclusion supported by the rest of her article. Maybe she’s right, but she didn’t show anything plausible to lead up to the conclusion.
What PITCHf/x, FIELDf/x, and HITf/x is uncover the truths. And we can feed those truths to the scouts, so they can have a better efficiency at finding the next Jeter. In no way should scouts feel threatened here. Sportvision, like computers and the internet, provides tool so humans can do a better job.
Thursday, September 17, 2009
Dave shows:
In 2007, pitching exclusively out of the bullpen, Hyphen posted a 33.6% GB%, one of the lowest marks in the league. He pitched up in the zone, and since his fastball averaged 91 out of the bullpen, he was able to rack up a bunch of strikeouts. It was an effective combination for him, and he continued to pitch that way out of the bullpen last year, actually getting even a bit more extreme – his GB% as a relief pitcher in 2008 was just 29%, a crazy low total.
But, after the M’s sent him to Triple-A to convert him to a starting pitcher, he came back a different guy. Over the 10 starts he made to finish last season, 46% of his 206 balls in play were hit on the ground. By moving to the rotation, he gave up some velocity, but also started using his fastball differently. I’m sure he’s smart enough to realize that he’s not going to get an 88 MPH high fastball by too many people, so he started locating it down in the zone more often, trading strikeouts for groundballs.
That’s continued this year, and especially of late. His GB% for the 2009 season stands at 41%, just a tick below league average, but he’s at 49% ground balls over his last four starts, when he’s been working deep into ballgames and solidifying his role as an innings eater. Between 2008 and 2009, his GB% as a starter is 43%. That’s a far cry from the 31% he was posting as a relief pitcher.
Tuesday, September 15, 2009
Yet more data from Harry. At Busch Stadium, 9.6% of batted balls are tagged as hard or soft hit. At Dodger Stadium, that number is 1.6%.
It’s possible that having that information, however biased, might have some value for one-year of data. But, once you get into multi-year data, having this information probably is more costly than it is useful. One more reason to stick to factual information as much as possible.
Thursday, August 27, 2009
Jonathan shows us:
Tuesday, August 25, 2009
Andruw Jones has not been any more unlucky in his career than Jeter has been lucky, with regards to BABIP. There is one parameter missing in these metrics that try to estimate a player’s BABIP: his ability to hit the ball away from fielders. Jeter has it, and Andruw does not. That is, by far, the biggest explanation for how much they diverge. A pitcher also has an ability to make the batter hit the ball to his fielders, but it is far far less in scope. It’s so small, that sometimes we think it might be non-existant. And sometimes, we try to think it works the same with hitters. It doesn’t.
Wednesday, August 19, 2009
Pat presents partial data:
Below are some of your 2009 New York Yankees, accompanied by their 2009 FB%, their 2008 FB%, and where this season’s FB% ranks along with how many seasons the data has been available for.
Player
Mark Teixeira: 45.1%, 36.5%, 1/7
Derek Jeter: 26%, 23.8%, 2/8
Jorge Posada: 43.2%, 39.7%, 1/8
Johnny Damon: 44.6%, 34.2% , 1/8
Hideki Matsui: 42%, 34.5%, 2/7
Nick Swisher: 44.8%, 44.5%, 4/6
Jose Molina: 41%, 33%, 1/8
It’s better to show all the data when you do stuff like this.
Blogger VEB uses Mike Fast’s PITCHf/x tutorial to make his own tutorial:
Consider this a laymen’s thought process when reading Mike’s tutorial. Hopefully, more computer savy guys like Dan and Harry can help answer my questions and any others that other readers have.
Saturday, August 08, 2009
Mike Fast contends that our spokesperson, the now-groundballing Banny, has to contend with a SS that is not up to speed:
Betancourt can’t field balls hit up the middle on the shortstop side of second base, even if the second baseman can reach them. He can’t field balls hit into the hole. I must be missing some of those “other factors” like defensive positioning and what not, although I’m not sure what positioning gives you problems with balls up the middle and in the hole.
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