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Should be: The Indispensible Baseball Musings

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Baseball Musings


DAVID PINTO WROTE: “Update: Jason Marquis is allowed to take a beating for the second time this year. He gives up two hits in the sixth before he comes out of the game. Just to finish his night off, the bullpen allows the runner they inherited from Jason to score. He’s charged with 12 runs. He allowed 14 against the White Sox earlier this season. Almost 30% of the runs Marquis allowed this year came in those two games.”

Pinto has created a baseball news site with fantasy relevance, excellent data tools, and it’s all free. Unless you do the right thing and pony up some cash, if you feel the way I do. I sent money last year and I’m not bragging, it wasn’t really enough. So I’m sending more this year.

Highly recommended.

As for Marquis, he’s killing me. Or Tony LaRussa is. I’d been riding the matchups the last couple of weeks (since the last time he was left in to take a beating) and it’s worked out well, so I didn’t see the spot to dump him. Mercy.

Midseason Fantasy Prices

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MLB.com Fantasy

As usual, my midseason fantasy prices (single and mixed leagues) are up at mlb.com. Even if you don’t play by the exact rules you can make use of them by comparing the preseason prices (guesses) and the actual thing. Most surprising to me is just how valueless Dontrelle Willis’s season has been so far, but pitching prices swing wildly when they run hot or cold.

WasWatching.com:

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It’s A-Rod Season!

Presents evidence that A-Rod is having a really crumby season when the Yankees are trailing by one or two runs, but it’s only 54 plate appearances. Everybody seems to have an opinion about whether A-Rod is always so bad in the clutch (though it should be noted, as the writer here does, that A-Rod has four hits after the seventh inning that put the Yankees ahead, while Justin Morneau leads the league with five).

Last year A-Rod had a couple of game score situations in which he didn’t hit nearly as well as in all other situations. One of them was down by two runs, but the other was up by two runs. He had a 1.096 OPS when down by one run.

In 2004 he was incredible in down by one run (1.416 OPS), fair when down by two runs (.910 OPS), sucked when down by three or up by two (.701/.556) and not so hot when the team was up by five runs (.724).

My conclusion? I love baseballmusings.com and David Pinto’s amazing database. Unconvincing attempts to impugn A-Rod’s clutchiness? Not so much.

David Appelman: Pujols’ hot spots

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SI.com – MLB  Wednesday May 17, 2006 12:26PM

When I was a boy perhaps the most influential thing I read was the issue of Sports Illustrated excerpting Ted Williams’ book about hitting, Science of Hitting. Most notably, a chart that showed his batting average when the ball was thrown in each spot in the strike zone and out.

I’m a little embarrassed now that I have no idea how the data for that chart was compiled and whether it was even real. Collecting such data in the early 60s was a lot harder than it is today. David Appelman is one of a growing number of baseball analysts who are drawing on the ever expanding trove of data Baseball Info Solutions has been collecting, and his Fangraphs.com site has been linked to here before.

These hitter charts are of interest, of course, but it seems to me that they tell the wrong half of the story. Player performance isn’t a constant, and wouldn’t it be really interesting to be able to see the distribution of pitches when Adrian Beltre was going bad and compare it to when he was going good?

The other thing that should be noted is that BIS derives most if not all of it’s data off of television broadcasts. While I trust that a reporter’s mark showing where the ball crossed the plate will be sort of accurate (and I believe the company employs multiple reporters for each game), there are plenty of reasons to suspect that they won’t be pinpoint. And if the analysis is meant to show scintillating differences in performance based on pitch location (remember, that the camera distance and angle is different in every ballpark), the noise of subjective judgement is likely to wipe out the little differences.

This isn’t to derogate Appelman’s work, or to impugn the value of what BIS is doing. But it is important to remember that better and more finely grained data isn’t necessarily objective data. Enjoy these excellent visuals, and imagine what they tell us about these hitters, but don’t imagine this is the end. In some ways it is just the beginning.

Games played streak ends after Matsui breaks wrist

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ESPN.com – MLB

One of the reasons I went after Hideki Matsui this year in the American Dream League (AL only) is because he’s been so consistent. Reliable. No more. Which got me thinking about a couple of attempts to gauge reliability that have surfaced in recent years.

One of these is Sig Mejdal’s Injury Projections. Mejdal list percentages of chance for players to get hurt. His Top 10 Hitters Most Likely to Get Hurt (published last November) was: Griffey (just getting off DL), Jordan (not yet), Cliff Floyd (playing like it), Gary Sheffield (on DL), Rondell White (playing like it), Sammy Sosa (retired), Reggie Sanders (gets off DL tomorrow), Jose Valentin (29 AB so far), Alomar Jr (back spasms and shoulder pain because he could’t play every fifth day), Geoff Jenkins (okay so far).

On the pitching side: Kerry Wood (like fish in a barrel), Orlando Hernandez (DL), Wade Miller (DL), Carl Pavano (DL), Jaret Wright (only 16 IP so far), Oscar Villareal (healthy), Randy Wolf (DL, out for season), Matt Mantei (DL), Rudy Seanez (ineffective, but pitching), Brad Penny (sharp).

That’s a lot of hits so far, but I’m not sure how useful that is.

Ron Shandler gave Matsui an 88 reliability score, on a scale of 100, reflecting his consistent performance and health over the past three years. Ken Griffey, on the other hand, scored a 7. Nomar? 22. All will have spent time on the DL this spring.

Study Reveals Baseball’s Great Clutch Hitters

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LiveScience.com

This site cites a study by Elan Fuld that uses some interesting and valuable methods to determine whether clutch hitters exist. While Fuld is able to identify a few hitters who exhibited reliable clutch tendencies throughout their careers, their numbers are so small that his ambitious study really seems to support the idea that clutch hitters don’t exist. To the extent Bill Buckner, Eddie Murray and Leo Gomez were clutch, maybe they were just a little luckier than the vast majority of players during the 30 years he looked at who weren’t clutch.

The role of psychological difference in baseball is an important one, and Fuld’s study apparently demonstrates just how narrow a swath the elite of baseball players are drawn from. That this purported science website could so misread the conclusion of this study should be an embarrassment.

Plus, they don’t even link to Fuld’s study, which you can find here.

You can also find a set of other clutch hitting studies compiled by Cyril Morong here.

Introducing Heater Magazine

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Heater Magazine – Home

John Hunt, who should need no introduction, Deric McKamey, the minor league expert at BaseballHQ.com, and Dave Studeman, of HardballTimes.com, have joined Graphical Pitcher author John Burnson to create Heater, an online magazine about baseball. While in the first issue Hunt and Studeman write fine “early season roto” columns, the heart of the Heater are the 30 pages of team statistical profiles and charts, and the umpteen more pages of position breakouts (as well as a page tracking minor leaguers).

Heater will be coming out each week, and for the fantasy player or the hard core baseball fan the wealth of charts, graphs, timelines and other details about this week, last week and next week, as well as a whole lot more stuff (I’m really just scratching the surface) is organized in an exacting and pleasing way. It’s like the back stats pages of Sports Weekly were totally rethought and reorganized to actually present the data in a way that made it easy to find trends and nuggets about players and teams. Radical.
In a word, all of it is useful, all of it is easy to understand, none of it is presented anywhere else in so fine and complete a manner. Don’t take my word for it. There is a sample copy at the link above. You’ll then have to decide if your money is well spent for this sort of thing. I’m hoping it is, because as long as they keep putting this stuff out my job is going to be a lot easier (and I’m going to look a lot smarter).

Alex Patton’s American Dream League Draft Sheet

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Patton $ on Disk Page

Alex has posted his bid prices for the AL only 4×4 American Dream League as and Excel workbook, as a way to show how he distributes draft inflation in clumps rather than in proportion. Of perhaps even greater interest are his quicknotes about players and how things went in the draft. Alex is leading the ADL in the still nascent season by close to 30 points, so there may be something to all this. And they’re free.

While you’re there, if you’re looking for software to help organize and sort your upcoming draft, you’ll get a chance to buy Patton $ on Disk 2006.

Ask Rotoman!

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Major League Baseball : Fantasy : Fantasy

Dear Rotoman:

While I have a great deal of respect for anyone that
compiles as much data for baseball fans and fantasy
addicts as you, I did want to point out some major
flaws with your projections for 2006 regarding
pitchers’ statistics. I am assuming you use some sort
of stat compiler or program you invented to project
season statistics. Of the pitchers you estimated
statistics for, you’ve projected only eight MLB
pitchers totaling 14 wins or more in 2006. Was this an
oversight? Colon finishes with 16, Oswalt and Santana
with 15 each, and Suppan, Sabathia, Lee, Prior and
Halladay with 14. I understand that its difficult to
pay individual attention to each pitcher, but there
must be a way to plug in the frequency of 20-game
winners, 19-game winners, 18-game winners, etc., into
whatever formula you are using to project stats. It’s
unrealistic to project such marginal stat lines, and
its a disservice to your fans to kick out these
figures like a robot, especially if you were being
intentionally conservative. SOMEBODY in the majors is
going to win at least 17 games. I’m willing to bet my
life savings on it. Wouldn’t you?

“Go for Broke”

Dear Go:

Absolutely, someone will win 18 games this year, but what good does it do to project the wrong guy to win 20 or 19 or 18 games?

It’s fun to model the whole year so it looks like the whole year (with 20 game winners and guys with 50+ homers) but it also means being wrong more often and by a larger amount, which doesn’t do anyone playing our game much good.

My projections are based on regressions of historical data modified by a few factors, the biggest one being age, combined with a different set of rate calculations, all of which are combined with a mechanical estimate of times at bat. I then go in and adjust based on probably changes in playing time and assessments of talent that don’t seem to be reflected in the projection. I call this tweaking, and it makes the boring regressions a little more lively and the overall correlation of the projections a good bit higher.

Then I scale everything so that the top 400 players projections are similar in total to the top 400 players actual stats. But the extremes in each stat just aren’t there, because the leaders in all categories usually change from year to year.

Thanks for writing,
Rotoman

Ps. I would not bet my life savings on the accumulation of any counting stat in a year when the Basic Agreement between the players and owners expires.

Rotoman!

You also have the MLB HR leader with 39 home runs.
When was the last time NOBODY hit 40 home runs?

“GFB”

Dear Go:

One of the byproducts of the system is that the AB of regular players are reduced about 10 percent off their usual peaks, with a similar reduction in the other stats. So all the guys who would project to 43 homers end up at 39 or 38.

The reason the AB get reduced is because about 10 percent of expected AB from year to year are lost to injury or other problems. This doesn’t happen evenly, but it happens consistently. There are two ways to handle this. One would be to ignore it and give all players their full measure of AB and stats. The other is to scale the pool of projected stats to the actual stats that will be produced by the pool.

I do the latter, because it gives a more accurate assessment of how groups of players perform on the year. The other looks better when everyone stays healthy, but since they never all do my method measures as more accurate.

Peter