THE BOOK--Playing The Percentages In Baseball

Friday, December 23, 2011

Transaction interface

I don’t know if this is available for the public, or for BPro-subs.  A great tool.  (Presumably at least the article is available to the public, because it sells the app.)

Seems to me this is the kind of thing you’d want for an iPhone especially.

Clubhouse Confidential - Glossary

Good stuff!

There are some tiny mistakes, and I’ll email Kenny tonight about it.  A couple like (IP/9) * BB should be BB / (IP/9)… that is BB per 9 innings.  Or “BABIP can used for hitters as well as pitchers. “ when really it should be “mostly for pitchers, and somewhat for hitters”.  In FIP, the “/IP” should apply to the whole thing, which is obvious of course, and no one would do it otherwise.  UZR is MGL not Fangraphs.

Other than those little nits aside, a fantastic job really of explaining it as simply as possible. I was impressed with the wOBA explanation.  Whoever on Kenny’s team worked on this: great job!

Glove-slap: NaOH

4 questions about a hypothetical pitcher…

If I told you that there was a 25 year old starting pitcher who threw at least 100 IP this year, how would you answer the following questions:

1) If he throws at least 50 IP next year as a starter, is he likely (better than 50% chance) to have improved or declined in performance, as measured by something like RA per 9 or component ERA?

2) Same question but rather than likely to improve or decline, is his average performance next year going to be better or worse?  One is a median and the other is a mean. For example, if he was 4.00 in year I and then had a 60% chance of being 3.50 next year and a 40% chance of being 6.00, the the answer to the first question is, “He improved,” and the answer to the second question is, “His average performance was a decline.”

Questions 3 and 4 are the same as 1 and 2, but the pitcher (he is still a starter) has no minimum number of IP in either Year I or Year II. 

Thursday, December 22, 2011

Deserved Leverage

I don’t remember this, but this was from two years ago, and talked about again today.

Basically, when you calculate the value of a reliever, you multiply whatever value you get by the Leverage Index he merits based on his talent.  This would be analogous to figuring out a player’s talent level as a fielder, and then multiplying it by the opportunities he sees (and the opps would be tied to his talent, such that a better fielder will find himself at SS, 2B, 3B, CF, and a worse fielder in the corners or 1B).

If you have a crappy fielder in CF, you can’t punish him too harshly because the team happens to put him there.  Think Junior near the end of his career.

Banal, mean-spirited, dated jokes: LGBT

Non-sports post.

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John Danks

Danks: 5/65 (one year of arbitration, 4 years of free agency).

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John Danks’ salary in his first year of arbitration was close to the salary of the big guys (Felix, Verlander, JJ, Weaver) in their first year.  His second year however was decidedly less (about 20% less).

In his third year, he’d have to settle for being one tier below those guys, if not lower.  The big 4 were at around 13MM$, so 20% below that puts him at close to 10MM$.  Let’s say that he would have signed for around that amount, either through arbitration, or as a result of negotiations (club submits 9, player submits 11) in 2012.

That really leaves us with a 4/55 extension, starting in 2013.

***

Because it’s an extension that doesn’t start for one year, he has to sign at a discount.  If he signs a 4/55 deal today, that starts in 2013, perhaps he signs a 4/61 deal today, that starts in 2012 (if he were a free agent today).  Basically, he signs a guaranteed deal early, in exchange for lesser money.  I don’t know if that discount is 10%.  It’s a number I pulled out of my a$$.  But, it seems to smell like a nice number.

So, the numbers you see below is based on delivering a performance consistent with a 4/61 deal in the years 2013-16.

***

He’s a young pitcher, born April 1985, just one year older than Felix.  Entering 2013, he’d be 28 years old, so we’re going to apply a somewhat modified aging curve.

So, this is what the Whitesox are paying for:
2012 3.7 wins
2013 3.4 wins
2014 3.0 wins
2015 2.5 wins
2016 2.0 wins

How much is a 3.7 WAR?  If you give him 198 IP in 2012, his effective win% (i.e., runs allowed converted to winning percentage) would be .538 in the AL.  A .538 win% means allowing runs at 8% below league average.

His career FIP is 7% better than league average and his career RA9 is 10% below league average.  (You would adjust that for regression toward the mean, but you’d also need to adjust for his age, which will pretty much cancel out the regression.)

So, his career indicates he has the talent level to give up runs at 7% to 10% better than league average for the 2012 season, and the Sox are paying him for delivering 8% better.

This seems about as perfectly fair deal as you should expect from both sides.

“Acquiring Power Isn’t More Valuable When a Team Has None”

Good stuff.

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Wednesday, December 21, 2011

Poz on HOF Candidates

Good stuff as only Joe can.  I like the one on Jack Morris.

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By the way, after Jack Morris is off the ballot, who will become the polarizing figure that the new-age would ignore, but the old-guard will trumpet?  Lee Smith?  I think he’s stuck at his 45% level.  Once Morris off the ballot, is the war over?  The closest I think will be David Wells among the newcomers.  But, given who he is up against (Clemens, RJ, Maddux, Pedro, Schilling, Mussina, Smoltz, Glavine), I don’t think he has a prayer of getting the Morris-love, even though, really, Wells, Morris, and Moyer are probably three peas in a pod.

Poll: Yu, Felix, Strasburg, Kershaw?

NOTE: Presume all of these pitchers are free agents.

Yu Forecast

Over the next five years, ZiPS says 22 wins.  That’s based on a 3.54 ERA on 918 IP.  Reverse-engineering shows a replacement-level of around 5.50 ERA.

Oliver says 33 wins.  Oliver is showing no change in IP and no change in ERA (basically) year-to-year.  That’s based on a 2.62 ERA on 1051 IP.  (Kershaw shows similar numbers.) Reverse-engineering shows a replacement-level of around 5.20 ERA.

It’s hard to make a comparison here.  We really need to know the average that ZiPS and Oliver is using.

I checked PECOTA, and there’s no forecast yet.  I’m looking forward to MGL’s forecast.

I would MUCH prefer to see the forecast as RA9 divided by league-average RA9.

Alan Nathan’s site

Alan made some re-organization of his site, to make it cleaner and more user-friendly.

Hit and Run

Mike does a great job at identifying situations that are disproportionately hit and run situations:

Finally, we arrive at the definition used for a hit-and-run situation in this study: (1) runner on first, bases not loaded, (2) none or one out, (3) a ball-strike count of 0-0, 1-0, 2-0, 1-1, or 2-1, and (4) the team leading or trailing by four runs or less. If the runner went on the pitch and the batter swung in such a situation, I will consider it a likely hit-and-run play.

And gives us these results, among many others:

Teams that attempted the hit-and-run play scored 0.11 runs on the play and 0.69 runs in the remainder of the inning on average, compared to 0.17 runs scored on the play and 0.70 runs in the remainder of the inning by teams that did not attempt the hit-and-run play in hit-and-run situations.

There are a few biases here that need to be controlled, before we can compare the .69 to the .70 (i.e., a wash).  Later in the article, Mike does an excellent job of reviewing most of them, and adjusting for them.  What he does there is exactly the kind of thing a saberist should be doing: identifying reasons for bias, and adjusting for it, as best you can.

He ends up with this huge finding:

Thus, the advantage for attempting a hit-and-run play during 2003-2011 appears to be about .061 runs on average.

That is a much larger number than I expected when I embarked on this research. I have attempted to remove as much of the selection bias as I could reasonably identify. It is possible that I have overlooked some bias or used a mistaken assumption, but every direction from which I came at the analysis pointed to the hit-and-run being a positive offensive play in most circumstances in which it was attempted.

I agree that that number seems simply too high.  Adding .06 runs on one PA is the equivalent of one of the best hitters in baseball.  Basically, it’s too big to be taken as the final number.

One bias that he noted early on, but that it doesn’t look like he adjusted for, is that a hit and run is in neutral or moderate hitter’s counts.  So, we expect more runs on that basis.  This will probably account for .03 or .04 runs of bias.  But, Mike says:

The ball-strike count also plays a role. The more favorable the count is to the hitter, the less likely that the batter will be forced to swing at a pitch he does not like. On the other hand, the same is true if the batter is not protecting the runner, and in that case, he may be more selective and take more powerful swings.

But his chart ends up with actually a net benefit for the hit and run.  Which is confusing me.

In any case, it’s a great piece of research, and hopefully will inspire more people to take up the cause.  You really couldn’t ask for any more for an initial piece of work.  It was a real pleasure to read.

Psst… wanna intern for the Orioles?

Tell ‘em you heard it from Tango.  What follows below is the actual posting.

============================================
“The Baltimore Orioles are looking to hire a Baseball Analytics intern to work in our Baseball Operations Department. This individual will report to the Assistant Scouting Director and the Coordinator of Baseball Analytics.

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Tuesday, December 20, 2011

WPA on bunts

If you are going to compare to a baseline, you CANNOT compare to zero.  You have to compare to the actual hitter’s true talent level.  It’s not the average hitter that bunts, but a below average hitter.  So, we EXPECT to see a negative win value relative to the average hitter, not only on bunts, but on non-bunts too.

Glove-slap: Mike.

Bill Conlin

A family tragedy, based on these vivid and numerous accounts.

Worst hockey game of all-time?

It sure sounds like it.  Now, I want to see it the way I want to see how much fun the worst movie ever is.

Glove-slap: Brian.

Market forces v Central Planning

Great stuff on the promotion/relegation system versus USA/Canada system.

If we look to Europe, though, we might see a better approach. To understand it, let’s consider the arguments of Frederich Hayek, who argued that a centrally planned economy can’t work as well as a free market one because the central planner could never have enough information to make adequate decisions. OK, but what does this have to do with sports?

Essentially, North American sports leagues use central planners to determine the location of sports teams. In contrast, European sports leagues rely on the market.
...
If these owners were ever successful, then essentially American owners would be exporting central planning to a market-oriented industry in Europe.

Monday, December 19, 2011

A great online chat with the new Astros GM!

http://houston.astros.mlb.com/news/article.jsp?ymd=20111219&content_id=26202260&vkey=news_hou&c_id=hou

Jeff Luhnow, the new Astros GM, is a great, smart guy who is all about using all available resources to build and maintain a successful franchise.  As well, he is very fan friendly, as you can see from this chat.

Astros fans should be very excited.

When asked in the chat about web sites he frequents, this blog was mentioned along with BP and THT, so we know that he has great taste in baseball blogs!

Who’s your candidate?

Fun-little thing.  Mine came out to Obama as #1.  Weirdly, the picture they showed was of Ron Paul, not Obama.  (They have a black Obama on the front of the page, but when it came time to giving out my best match, it was a white Paul that they showed.)

Speculations and suspicions: The Yu Darvish Story, Jeff Bagwell, and being a sports “reporter”

Seems all that note-passing in the 7th grade is finally paying off for all concerned.