New Version of Patton $ on Disk

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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.

Clutch Hitting: Fact or Fiction?

Clutch Hitting: Fact or Fiction?

This is not a recommendation, but it isn’t a condemnation either. Mr. Dolphin approaches the issue of Clutch Hitting with all his statistical wherewithall intact, and uses his tools to figure out if hitters perform better when the game’s on the line.

He swings and misses in part because, of course, clutch hitting is always in opposition to clutch pitching. If everyone wants to win how do you measure their desire?
His study doesn’t seem to take this into account. Yet he does find what he claims to be a statistically significant difference when hitters face pitchers in “clutch” situations.

Others may better critique Dolphin’s methods, but I find his attempt to take on the sabermetric shibboleth that there “is no such thing as clutch hitting” kind of charming. But I reference it here as a warning. He may well be right, but until he can clarify in English what all his efforts really amount to, I’m not going to pay much attention.

Ps. The author of this study is one of the authors of The Book, which attempts to statistically answer some of the more contentious baseball issues using genuine data and real math. The Book is on its way to my house, and I’ll write about it at some point. I guess my biggest point is that as interesting as technical baseball statistical issues are, if you can’t write about them as anything other than a math problem, you’re probably not going to get a lot of traction.

The Thomas George–Dollar Value Calculator

Fantasy Baseball – Dollar Value Calculator

With the 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.

Reviewing The Fielding Bible

The Crucible of Competition — The Hardball Times

I seem to have waded into the Hardball Times and I may never get out.

John Dewan is Bill James’ somewhat more pragmatic partner, and his attempt to harness the great cache of information that Baseball Info Solutions has harnessed the last three years in service of identifying what qualities make a good fielder have to be respected.

Dan Fox, in his review, gets pretty excited about some of the minutia, like whether Alfonso Soriano is better going to his right or left, or on balls in the air or on the ground. It would be so great to have confidence in these numbers, but even with all the safeguards and adjusters in place in TFB, the small samples and differing conditions for all players make it really really really hard to be definitive about objective defensive measures.

But this sytematic approach may teach us something we need to move to the next level. I’m not a naysayer at all. As Dan points out, the data is the thing here. How we massage it and to what ends is going to determine its value. My copy hasn’t come yet. I can’t wait.

Forecasting 2006 — Tom M. Tango and Marcel the Monkey

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.

The Amazing Fan Graphs

Baseball Stats, Graphs, Analysis | Fan Graphs

Have a month or two to do nothing but click on links on a website? Visit Fan Graphs. You’ll find stats here, but you’ll also find 70 charts for every player tracking daily and seasonal trends. Most immediately interesting to me were the daily graphs tracking AVG, OBP, SLG, K/9, BB/9, and on and on. Stats are compared to a ML average, so you can visually judge relative improvement or decline. Plus righty/lefty and home/away splits are also graphed. Simply awesome.

Make your own team stats lists

Statmaster : A Baseball Team Statistics Tool

Another way to make lists is this bit of webware from Baseball Almanac. As the site points out, every major site has player stat pages organized by teams, but it can be hard to find the particular stat you’re looking for. Statmaster has a long list of available stats, and you click off which ones you want to see. It doesn’t allow you to pull leaguewide lists, which is a shortcoming, but it does offer what could be a faster way to do research than sites where you have to scroll across multiple pages to find the more esoteric numbers. Worth checking out, and it will certainly be bookmarked by some.



This is a nifty piece of online software that comes with a price attached. You’ll have to decide if the early promise is worth the price, but I have a compulsive desire to make lists, and certainly feeds that addiction. The site advertised in the Fantasy Baseball Guide this year, and we appreciate advertisers. What I’d like to see is a way to plug other sets of numbers into the mechanism, so you could analyze projections, or 2004 numbers, or three year averages. Even if you don’t want to pay it’s worth checking out for the Top 10 lists that come for free, which hint at what’s possible.

The Best Projections in the Universe

Baseball HQ: HQ Today

I received a copy of John Burnson’s Graphical Pitcher 2006 today from Amazon. No time yet to delve deeply into charts, which present a cognitive problem, at least at first. How to absorb a ton of information until you speak fluently the local dialect? I did read all the text, which is informative and entertaining (as the ultra-bright and engergetic Burnson always, in my experience, is). But the real wow is a study he (they?) published at baseball HQ last year after randomly drafting gazzilions of virtual fantasy teams, calculating virtual standings, and tracking which players appeared more often on winning teams.

This is a brilliant way to solve so many player valuation problems, one that was hinted at when roto stat service pioneer Jerry Heath published which players appeared most often on the last place and first place roto teams in the leagues he served. But taken to this level I believe it qualifies as original rotisserie research, which is a rare thing and about the highest praise I can give.

Which got me to go to looking for the original article. I didn’t get to WOW before stumbling over this article Ron published in his free weekly newsletter last week. It doesn’t say much more than last year’s “Player Projections are a Crock” article did, but he says it more vehemently. I agree with him, as you know if you’ve been coming here regularly over the past few years, but I think he’s giving short shrift to the key role of the fantasy tout, which is to identify not only which players are going to get worse or better but which are going to get the most better or worse relative to public expectations.

The most important number to know, if you could, would be what price a guy is going to go for in your league.
The second most important is to know how to maximize each player’s contribution by putting together a solid roster. Ron has long focused on this in very constructive ways, but Burnson’s article in The Graphical Pitcher 2006 (and presumably archived somewhere at makes you say, “Wow.” Salaries Database Baseball salaries database

The new Ask Rotoman blog will be chockablock with references to useful and timewasting services on the web. This is a good one. Track your favorite team’s salary by year, or your favorite player’s, or see how your team in this year or that wasted its precious dough, here.