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I don’t have anything to say at the moment, but I did notice something interesting with him. In the last three years, the umpire has called “ball” on him 1125, 1117, and 1122 last year. How many called, swinging or in-play strikes? 2509, then 2309, then 2137. He’s still got good numbers, going from a Schilling-like 69.0% to 67.4% to 65.6%. I don’t know if it means anything, but I thought that was interesting.
I asked MLB.com about getting stopwatches for their scorers. Here is what the Director of Stats had to say:
Fantastic article by Sal Baxamusa. One of the little things I’ve done, which I’ve set aside for… I don’t know why… was to extend my Markov chains to counts. I could, in effect, tell you how many pitches Christy Mathewson threw, with just a few reasonable assumptions.
Sal however is making me think that one of my assumptions may not be reasonable. He says:
When the first pitch is a ball and the second pitch a strike (called, swinging, or foul), batters have a line of .243/.312/.378. Curiously, batters perform better when the all-important first pitch is a strike and the second pitch is a ball; they hit at a .257/.314/.402. That’s a 25-point difference in OPS; not world-breaking but statistically significant (p<0.001 for you stat wonks) nevertheless.
I’ve always wondered if the path to a particular state (1-1, 3-2, etc) matters. That is, is 1-1 itself a state, or do I now have to say the state was “0-1 to 1-1”, and “1-0 to 1-1”. What I would consider one state for Markov chain purposes is actually better described as two states. The interesting work is to see how far back the states need to go. That is, if you have a 3-2 state, how far back in the count do you have to go, in order to establish the state you are in.
Most pitch data research should be recognized and applauded, and this article, as well as all of the Appelman articles, fits the bill.
As an Expos fan, there was so greater bothersome sight than seeing Galarraga with an 0-2 count. Why? Because everyone knew what would happen: the pitcher would throw a low breaking ball away in the dirt, and Galarraga would swing, lunge, and miss. It may sound like I’m exaggerating when I say he has probably struck out in 75% of such occasions, but I’m probably close. I’d also be disappointed if there was anyone else who struck out more often in that situation. And, what was alarming is how good a hitter he was otherwise!
David Appelman shows us the year-to-year correlation on players swinging at pitches outside the strike zone. And the correlation is an astounding r=.87. That is HIGH. It’s like, players don’t learn. They have their approach, and they will stick to their approach, because their approach is what made them get there in the first place.
And, when you see former Expo Vladimir Guerrero as the “HR hitter who has swung the most at an outside pitch”, maybe the players are right. Who is anyone to tell such an elite hitter how to hit? And, this guy hardly ever strikes out! Perhaps if David did an additional category, which only includes balls that were swung and missed, or swings that resulted in an out, Vlad would not be in this list at all. Galarraga though definitely would.
The park factors for the 2007 Bill James Handbook can be found on the errata page. (Hat tip: DanAgonistes blog).
1. Download this file from BDB
2. Unzip it. This will create a folder, or subfolder, called adminDB. Move this to your c: drive. All text files will now be in c:\adminDB
3. Download this file from my site to anywhere.
4. Open the file from my site, click the MACROS tab.
5. Execute Steps 1, 2, 3.
6. You now have all the data loaded into your Access database. Verify the data.
Changes were made since 2003, and I didn’t really keep up with them. I had to make changes to these tables: ManagersHalf, Pitching, PitchingPost. If someone(s) can make a verification of all tables, and make a note in this thread as to which tables they verified against the SQL table definition files from the BDB dump, that’d be great. Otherwise, I will look at each table tomorrow.
Take one hard-working and generous Dan Fox, combine them with crazy Redsox fans who look at the spread of balls hit by JD Drew, fans who also overlap Dodger Stadium over Fenway Park, to see what happens. Or, take other crazy Redsox fans, who analyze all of JD’s long balls, and he says:
The overall net effect was -2 HR’s, -3 Triples, +8 Doubles and -3 Flyouts. So, you lose 17 bases and pick up 16 - practically a wash.
The best baseball stats site around continues to add feature after feature. Let this be a listen to corporate America. The best websites are not created by middle managers who self-annoint themselves with the pulse on America. They are done by creative, intelligent people. Imagine if Picasso worked at GE today.
Anyway, Sean allows you to set players as he says “into a neutral setting or any setting you chose from Coors circa 2000 to Dodger Stadium in 1968.”. On its face, this is pretty cool. In reality, it is of course b.s. To get technical, he allows you to see how a player’s stats changes if the *run environment* changes, and not if he moves into that particular year/league/park. After all, Coors/2000 and Dodger Stadium/1968 doesn’t affect everyone the same way. To say nothing of the actual timeline adjustment itself. So, I don’t really get why he bothers to let you choose something as specific as that. Why not just let you put in a run environment, say 4.31, and be on your way? I think it gets people excited to present it the way he does, because, on its face, it looks cool. But, it pretends more than it shines. I wouldn’t have a problem if he says “6.39 RPG”. I have a problem if he says “Coors 2001”.
According to this, it seems it’s only 150:1. I’m guessing it’s more like 4 million to 1. Here’s what I did:
SNY calls it TROE, we called it RBOE in THE BOOK, and Retrosheet calls it ROE (though Ruane added a wrinkle by also including reaching base on a fielder’s choice, where no outs were recorded). All to say that it should be recorded officially as its own category, and not lumped into all the other batting outs.
Thanks to the recovery of the Tangotiger Archives, we have a great article from MGL, as well as my component regression values.
Using Tom Tippett data, here is the wOBA, BABIP, and the big three, by count, excluding IBB:
http://www.usatoday.com/sports/soccer/world/2006-11-27-smartball_x.htm
Ten years ago, Fox launched the Fox Puck, to track where the puck was at all times. What they did with the technology (real-time floating lights, trail blazing shots) was silly. But, to track where the puck is at all times was beyond fantastic. Embed GPS on players’ sweaters, and you have a gold mine. The same for soccer, football, and baseball. Combine that with video games’ player motions, and you are near perfection. Add in a reality show that tracks what players do after hours, and you will have the complete model.
When will the revolution start?
Sean’s going all-out to make the Retro data really useful. Check it out, and offer your opinions:
http://www.baseball-reference.com/blog/
I have restored the Tangotiger Archives from my old blog at Baseball Primer. Enjoy!
If you see anything wrong, let me know. Since I’ve moved to this new server, all my files are now case-sensitive, which means I get broken links. I’ll handle those as they come up.
Sabermetrics is the convergence of performance analysis and scouting observations. David scratches the surface. Tracking pitch-by-pitch, including count, pitch type, velocity, location, famigli of batters, pitchers, as well as tracking hit-location, millisecond-by-millisecond, including fielder positioning, is the holy grail. There is a mountain of haystack for us to find that needle. All we need is more researchers.
One interesting question is…
I recommend Joe Adler’s Baseball Hacks. This blog entry will be some of my hacks in using various data. Here’s one for the Lahman database:
What happens when you take a guy who spends alot of time collecting and presenting data, and another guy who spends alot of time analyzing said data? You get great research, and potential for even more:
http://sonsofsamhorn.net/index.php?showtopic=12439
I will reiterate here what I said there:
Cool article on MLB.com Here’s but a little snippet:
Zumaya’s final three strikes thrown to Alex Rodriguez in the eighth inning of that game, according to the Enhanced Gameday showing speed at release and then speed crossing home plate, were as follows:
102.5 / 93.4
102.2 / 91.9
100.2 / 90.7
And the data for the holy grail:
In the future, this technology could lead to such advances as camera-mapping of the entire field, so that the complete movement of every player in every inning can be captured and then depicted in ways that benefit coaching of defense, baserunning, umpiring, pitching mechanics, self-analysis by players and more.
John Jarvis has expanded his team summary pages going back to 1957:
http://knology.net/~johnfjarvis/stats.html
Just to give you a thought…
May 16 22:50
Dodgers’ win reversed because Mattingly did not attest to proper score!
May 16 20:44
How to beat the shift
May 16 20:02
Sponsoring MLB jerseys
May 16 19:34
Now you frame it, now you don’t
May 16 16:56
Did Manny Pacquaio actually quote Leviticus?
May 16 16:06
Does changing your pitch frequency lead to substantial change in results?
May 16 14:18
Extra Innings: One-minute review
May 16 14:16
This particular criticism of UZR is unfounded
May 16 13:21
Psst… wanna intern for the Astros?
May 16 12:23
Arena wars
THREADS
May 16, 2012
Now you frame it, now you don’t
May 16, 2012
Dodgers’ win reversed because Mattingly did not attest to proper score!
May 16, 2012
Does changing your pitch frequency lead to substantial change in results?
May 16, 2012
Sponsoring MLB jerseys
May 15, 2012
Andre The Hawk Dawson speaks
May 15, 2012
Euro 2012 Preview
May 15, 2012
How to beat the shift
May 15, 2012
Will Pujols end the season with at least 30 HR and .500 SLG?
May 15, 2012
Kershaw v Strasburg, part 2
May 15, 2012
Did Manny Pacquaio actually quote Leviticus?
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