Statistics

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).

Pundits on Parade 2006

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Ask Rotoman News

Ron Shandler did the heavy lifting. He collected a bunch of player projections (but not mine) and commented on them.

I copped his charts of other people’s projections and added mine.

The lesson, I think, is that all of our projections could be wrong, but we mostly agree on what they are. That qualifies as information.

This Week’s Ask Rotoman

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Major League Baseball Fantasy

I didn’t anticipate that with Ian Kinsler going down with a bum finger that Gary Matthews would be called up right away. Knowing what I know now, especially given Matthews’ three-run triple tonight, take him over the recommended Kevin Millar. . . Wait! I recommended Millar instead of Matthews and Millar hit two homers, drove in four runs. Sweet! As usual, you should sort it all out for your league.

Elsewhere in this week’s model, frank discussion about Jeff Francoeur, the breakout (break down?) of a trade of big players (for educational purposes only), and some chatter about some Hots and Nots.

Be there! As some of us used to say in college.

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

New Version of Patton $ on Disk

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Support Ask Rotoman Page

A weekend of bug squishing led to the release of an updated and improved Patton $ on Disk.

The program includes updated projections, bid prices from me and Alex Patton for 4×4 and Mike Fenger for 5×5. It is a great program for sorting lists and pricing players in the traditional 4×4 and 5×5 formats. The ease of updating projections and prices, the auction manager with bid values and all that make it useful for smaller mixed formats, too, but the pricing is not adjustable.

There is also an Excel worksheet with all the data available, and text and Word files will be out tonight.

The price: $25.

The Thomas George–Dollar Value Calculator

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Fantasy Baseball – Dollar Value Calculator

With the Rototimes.com dollar value calculator skulking into the site’s pay section, hidden away like the Rotowire price calculator, an old standby moves on. The Thomas George is a venerable roto site with its own free calculator. It allocates percentages to hitters by percentage, which is not right unless you play in a league that auctions position by position, but a quick runthrough found it to be usefully accurate nonetheless. Maybe you can hack the percentages so that they treat all production equally.

Forecasting 2006 — Tom M. Tango and Marcel the Monkey

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The Hardball Times

It has been clear for years that the science of player projection is something of a scam. There is a finite amount of stuff we can know about a player’s performance the next year and a certain amount that is stochastic, random, unknowable. I’ve put the unknowable part at about 25 percent, based on various ways of measuring the accuracy of my expert projections.

This big random component means that the lens of a single season tells us only a little about about a player’s actual abilities. And while we use these small slices to tell us more about the player’s game, as a player ages his game changes. The measures that matter for a 25 year old are different for a 30 year old and different still for a 35 year old. The very smart Tom Tango set out to see how much of the potentially knowable 75 percent he could project using a very raw set of weighted averages building in regressive factors, and writes about it here.