Assorted Baseball Thoughts
- By: Chris Liss
- On: 8/17/2010 4:56:00 PM
- View Comments : 31
Related: Chris Liss
We have a rule that you can play a player out of position, and his stats will count for you so long as he qualifies there eventually. For example, if you wanted to use Jake Fox at catcher in April, you could have even though he didn't qualify there at the start of the year. As long as he eventually got 10 games at catcher (he has 13), then the stats you got from him in April count for your team. If he never did make it to 10, you would get zeroes there. This rule has two benefits: (1) You don't have to wait 10 games for someone like Fox, or for Carlos Guillen to qualify at 2B, for example; and (2) instead of rostering a second scrub catcher (the league is AL only), you can use the roster space as an extra bench spot, so to speak, and take the zero on purpose.
That part of it, I was aware of. What I didn't know was that for rookies, they don't have positions initially, and wind up qualifying somewhere only if they eventually get to 10 games there, or barring that, whatever position they play the most. I had just assumed that rookies qualified wherever they played the most in the minors. Not the case. So when Chris Carter got called up from the A's, I put him at first base, in place of Justin Morneau. Carter was sent to the outfield where he played all six games before being demoted yesterday. He was also 0-for-19.
So imagine my surprise when I find out today that Carter was actually playing OUT OF POSITION! That means that unless he gets called up in September and plays first base for either 10 games, or more games than he plays in the outfield, his stats for that week are null and void. Considering I'm in a fight in batting average, that was pretty great news. But the kicker is that I've had Matt LaPorta in my outfield the entire time, and he qualifies both at 1B and OF! In other words, this never should have been an issue in the first place, and had I known I would certainly have switched the two and been stuck with the 0-for-19.
While I typically run lucky, this is taking it to a whole new level.
Jeter has been well above average with a much bigger role. Rivera has been the greatest ever in a smaller one. The total net above average definitely goes to Jeter, but with the Yanks and their payroll, the average should be a lot higher. So Jeter's advantage shrinks in larger proportion than Rivera's. There have been plenty of closers as good as Rivera for one year (Lidge, Putz, Papelbon, etc.), but it's easy to say that after the fact. Beforehand, there's no way to know what you'd get and hence no way for the Yanks or anyone else to acquire one. I'd say Rivera is more important, but Jeter has done more. Rivera's postseason stats by the way are retarded. (0.74 ERA, 0.77 WHIP in 133.1 IP). And of course, Posada's per-at-bat stats (.857 OPS) are arguably better than Jeter's (.840 OPS) and a good deal better when adjusted for position. But like Rivera, Jeter outdoes him on volume.
Plus I'd lay 20 to 1 that I could beat Posada in a footrace after drinking 8 beers.
This made me think the Rays would have to keep Hellickson stretched out the rest of the way - after all, how could you possibly mess him up down the stretch if you need him to be one of your frontline guys in the playoffs. Sheehan agreed to an extent but said they might very well go six starters in September (solves that problem as well as cutting down on Price's and Davis' innings counts). But Sheehan also suggested that basic clubhouse morale might be a big issue for Joe Maddon if he kicked his former ace to the curb for rookie with a handful of career starts. And that given Shields' excellent peripherals (and ostensibly bad luck), the difference between Hellickson and him didn't warrant opening that can of worms.
Joe might be right, but if Hellickson pitches lights out, say in a six man rotation the rest of the way, and Shields continues to have bad BABIP, strand and HR/FB luck, it's going to be a tough sell outside of the clubhouse.
Of course, I'm happy this happened, but had it not, the Yanks and Rays might be in a fierce battle for the AL Wildcard spot.
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Comments
On: 8/17/2010 5:28:00 PM
The best pitchers in baseball consistently beat the league average in HR/FB. Go look it up for yourself.
On: 8/17/2010 6:34:00 PM
On: 8/17/2010 8:33:00 PM
On: 8/17/2010 8:38:00 PM
On: 8/17/2010 8:47:00 PM
On: 8/18/2010 9:45:00 AM
On: 8/18/2010 11:05:00 AM
Scott, I'm not sure if the "otherwise intelligent people" comment was directed at me, but since the conversation has sort of turned that way, I figured I'd jump in. I looked up the HR/FB numbers, as you suggested, and here's what I found:
From 2004 to 2009, there were 43 pitchers (who spent at least half of their games starting - relievers are a different beast) who posted HR/OF rates below 10% (league average is 11%-ish) in at least 200 IP (one full season-ish). If we require 400 IP, we get 29 pitchers. At 600 IP, we get 22 pitchers. At 800 IP, we?re down to 13. Of course, there's a little bias here, but I think it's a pretty decent argument in favor of regression (if the endless, more rigorous studies aren?t enough). To phrase these results differently, the fewer innings he's pitched, the easier it is for a pitcher to beat a league average HR/FB ? luck! sThe more he pitches, the more he regresses and falls off our list. At the 3-year mark, we only have 5 pitchers below 9% (Cain, Kelvim Escobar, Clemens, Wainwright, and Wang). At the 4-year mark, it's only Cain.
Regression is real, but that's not to say that xFIP or LIPS or any other ERA estimator is the end all, because it's not. It's a shortcut, a quick way of seeing what a pitcher's peripherals tell us about him for that particular year. It?s not meant to be a forecast. It uses one year of data and implies 100% regression to the mean for BABIP, HR/FB, and LOB%, which is incorrect (but not terribly so for the vast majority of cases, which is why these things are usable if we know what we?re looking at).
Regression is real, but I think a lot of analysts give us the wrong impression of it. They either (out of laziness or ignorance) assume that every BABIP, HR/FB, LOB% should be league average at all times. That?s not what regression is! Regression means that the player?s numbers should move in the direction of a league or group average ? how far towards that number depends on a number of factors (in some cases it may not move much at all from the player?s actual performance).
For a guy like Aaron Harang, he has a .310 career BABIP and a .329 or so BABIP over the past three years. For a guy like this, with this much data, it would be foolish to assume he?ll post a .300 BABIP going forward. But it?s also foolish to assume that he?ll post a .329 BABIP going forward as well (in the absence of some other data that says he deserves a high BABIP). If we know something about Aaron Harang from scouting or other means, like I said about Haren, we can say that it?s best to regress Harang to, say a .320 BABIP. But if we don?t have these things, the best we can do is regress to league average (or some group average).
This doesn?t, however, mean that we assume Harang will have a league average BABIP. That?s not what regression is. It just means our estimate will move some distance toward that number. We take all the data we have on him, and based on that sample size and the league-wide variance in BABIP, we can come up with a good estimation of his BABIP going forward. This will be far more accurate than simply saying, ?For three years in a row, Harang has had a high BABIP and an ERA higher than his xFIP, so xFIP is useless (not just for Harang, but for all players) and we should just use Harang?s ERA or our gut impression of him.?
So to answer Chris?s question, yes, I would make the exact same case for Harang or Masterson. That is, yes, it?s possible that these guys truly deserve high BABIPs (or HR/FBs or whatever), but unless you have some sort of information that shows me that they should, I?m simply going to take the data I have, and regress the proper amount (and, ideally, treat vs. LHP and vs. RHP separately (but not independently), especially for Masterson). We?re just looking at a different magnitude here. For Haren?s BABIP, it?s one year and will be nearly completely erased when we account for previous seasons and regression. For Harang, it?s several years and will show up somewhat in our projection.
Just because there are these guys that look like they are ?exceptions? doesn?t mean that they don?t follow the rules of regression. They do ? they just regress less the more data we have on them. And if we have some scouting or other information, they regress to a number other than league average. Everyone regresses, but a lot of people assume that everyone regresses to league average, when in fact they don?t. In fact, very few players regress to league average. Everyone, truly, regresses to their own absolute true talent level (which is unknown), so we do the best we can to estimate that. League average is the bare minimum acceptable guess we can make, but once we know some things about the player, we can regress him to a group of players similar to him (for example, small-framed lefties with underwhelming stuff and a fastball-slider-change repertoire) or to some unique number that better suits him than league average.
million_dollar_sleeper,
I'm not sure where the animosity for the CR league comes from, although you?re certainly entitled to your opinion. Personally, I have found it to be a nice vehicle to vocalize some of these theoretical issues and have had a lot of fun with it. As to not being able to ?forecast my way out of a paper bag,? I think I?ll leave that alone, except to say that I disagree.
One thing I want to point out, however, is your inclusion of CAPS in your list of ERA estimators. CAPS is very different and stands for Context Adjusted Pitching Stats. Because I?m the one who came up with it, I?m assuming you read THTF, which leaves me wondering what you don?t like about it. CAPS adjusts for context: things like ballparks and quality of opponent. Are you saying that these effects don?t exist or are unimportant? I can see not liking ERA estimators if you?re using them wrong or don?t fully understand them, but CAPS is pretty straight-forward, at least in its concept.
Also, Chris, I'm completely with you on the Verducci Effect. Not a fan at all. Also, you?re right about the ?HR/FB regression? being ?weaker than BABIP one.? BABIP takes longer to stabilize than HR/FB, but both still take a long time (if BABIP takes six years ? which I know you?re not a fan of saying, but it?s an easy way to phrase it and makes for easy comparisons ? HR/FB takes four)
On: 8/18/2010 12:36:00 PM
A few months ago I made up an (admittedly subjective) list of the Top 15 starting pitchers in baseball and looked at their career HR/FB rates. Think up your own 15, I bet we have almost exactly the same names. Anyway, 11 had HR/FB rates below the industry average for their careers, one was on the fence, and three were over it (and slightly over it, at that). That's just step one in a journey of 1,000 steps, but I found it interesting.
On: 8/18/2010 1:17:00 PM
On: 8/18/2010 1:50:00 PM
On: 8/18/2010 1:51:00 PM
I don't think anyone would argue that death, divorce, etc don't affect players, it's that they are nearly impossible to quantify. And if we aren't quantifying them, how do we know we're even going in the right direction? If Player A gets a divorce, is he going to play better or worse? Is he going to be so distraught he plays worse, or will he be angry and play better? Or have more time to focus on baseball and play better? These are real things, they're just tough to include, especially when the overall effects may not even be that large or the direction knowable. As to trading, all the big leagues allow it (LABR, Tout, etc), and I'm a fan of the position eligibility rule. It allows you play a guy at a position you know he will eventually qualify for and may in fact be playing in real life but wouldn't otherwise qualify for in fantasy.
On: 8/18/2010 2:20:00 PM
On: 8/18/2010 2:26:00 PM
On: 8/18/2010 2:31:00 PM
As to trading, NFBC does it to promote fairness and isn't a strict experts league. It's high stakes, but not expert (and I consider CR more expert than high stakes). Because there are many leagues played out simultaneously and the overall standings get pulled from all leagues, trading promotes imbalance in case some leagues don't have as active traders or weaker players. Because CR is an expert league, I think trading makes sense as every other experts league I've ever seen has it. As to vetoes, that's a long discussion, but I (and most every expert league I've been in) am against them. To sum up my point (partially) about expert league vetoes, aren't we supposed to know what we're doing, as experts, and isn't it possible that one of us knows something the rest don't, leading to the decision to make a particular trade? We're supposed to be the learned minority, processing our thoughts and making decisions independently of conventional wisdom, and independently of each other, for that matter. And as experts, we're also supposed to understand that no one knows what the future holds and that vetoing trades based on the subjective judgment of one or two or three people is a bit ridiculous. If two experts feel that a trade will benefit their teams, shouldn't that be enough? Why does an arbitrary third member of the league get to decide if it does? I agree that some trades have seemed lopsided, but that is just my personal judgment of it. The rule in CR (and most other expert leagues) is that unless there is collusion, trades hold up.
On: 8/18/2010 3:05:00 PM
This is exactly what I was getting at in paragraph 9. League average has absolutely nothing to do with it. It's a misconception because it's the easiest and most common thing we regress to (Marcels, FIP, xFIP, etc), but it's not correct. To make my point easier to understand, let's use hitter BABIP. Ichiro Suzuki has posted a well above average BABIP every year of his career (except maybe 2005, which was merely a little above average). Why? Because league average has nothing to do with Ichiro! His BABIP skill is not league average. Instead of regressing Ichiro to league average, we might regress him to “speedy lefty” BABIP average. And we would have done that for his rookie year too.
For Harang, I’m only saying to regress him to .320 (or whatever number we arrive at *IF* we have evidence to suggest that this is where he should be. Otherwise, we would regress him to his group’s average (maybe big righties with above average stuff and a fastball-change-slider-curve repertoire). This group’s BABIP mean is nearly identical to league average, I’d imagine, which is why regressing to league average gives us a 'good enough' answer, doesn't draw suspicion, and why most people simply regress to league average. But if we throw “has mechanical flaws” or “tips pitches” or whatever into the mix (so it'd be big righties with above average stuff and a fastball-change-slider-curve repertoire who tip their pitches), then that group would likely look very different. That’s where the .320 BABIP would come in.
I absolutely agree that we can’t know for certainty beforehand, that we only know after the fact, and that Haren could end up like Harang, but that’s exactly it – we can’t know with any certainty! I can’t, and you can’t. So we regress to whatever group we have Harang in given the data that we have. Regression removes the proper amount of this uncertainty, and that's the best we can do absent more information.
To get even more technical, if I haven’t scared enough people away yet, regression to the mean is a shortcut for Bayesian statistics. Bayesian statistics basically says “what’s the chance that a guy with a true .250 BABIP posts a .317 career BABIP like Harang did,” then “what’s the chance that a guy with a true .255 BABIP posts a .317 career BABIP like Harang did,” then “what’s the chance that a guy with a true .260 BABIP posts a .317 career BABIP like Harang did,” etc. It does that for as many possibilities as we choose and then takes the weighted average to arrive at the most likely BABIP for Harang (I imagine your brain algorithm does something similar). Regression to the mean simplifies this process, but it’s really the same thing. Maybe that makes it easier to understand.
On: 8/18/2010 3:41:00 PM
On: 8/18/2010 3:41:00 PM
On: 8/18/2010 4:02:00 PM
On: 8/18/2010 8:26:00 PM
On: 8/18/2010 8:27:00 PM
On: 8/18/2010 8:31:00 PM
On: 8/18/2010 8:50:00 PM
On: 8/18/2010 10:16:00 PM
On: 8/19/2010 11:04:00 AM
On: 8/19/2010 3:04:00 PM
I'd give you a more convincing proof, but I don't really need too since my common sense tells my you're super wrong.
On: 8/19/2010 3:58:00 PM
I'm not here to get into a pissing contest. Nothing is going to be accomplished when three ego maniacs butt heads. I don't expect anyone to agree with me, that's why I beat everyone. Liss can keep asking his army of ass kissers to bow before him, Carty can go back to thinking he's the love child of Phil Helmuth and Albert Einstein and I'll just keep beating people. I'm happy.
On: 8/19/2010 4:27:00 PM
On: 8/20/2010 1:40:00 PM
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