Chris St. John and I have been talking this over for the past few days. Anyone interested? Click here and type in League ID and password listed below:

If you have any questions, leave a comment here or tweet me @cobradave

With the huge free agent signings this winter, and also with the release of the top 100 prospects (For MLB.com's rankings, http://www.mlb.com/mlb/prospects/watch/y2012/) it got me to thinking, "Is Prince Fielder really only worth two draft picks, even if they're first rounders?" Of course Fielder, Albert Pujols, and C.J. Wilson are worth more than that. So how much is a first rounder worth? Note: All WAR numbers are from Baseball Reference.

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Analysts and commentators frequently rave about a player’s ability to hit to the opposite field. Extreme pull-hitters are often knocked by many fans who consider hitting to the opposite field a key indicator of a great hitter. However, some of the best hitters in the game - Albert Pujols, Alex Rodriguez, Ben Zobrist, Carlos Beltran, Paul Konerko, Mark Teixeira, and Ken Griffey Jr. - could be considered pull-hitters: hitters who have pull rates above the 84th percentile, or one standard deviation above the mean, among all players. Thus, I wanted to understand the value of hitters with extreme split tendencies versus hitters without any extreme split tendencies, (spray hitters).

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In an earlier fan post at http://www.beyondtheboxscore.com/posts/preview/2049891, StrikeThree! made an error by ascribing Washington JFK Stadium (29,200 sq. ft) foul area to Washington's Griffith Stadium (33,900 sq. ft). for the years 1954-1961. This increase of 1.8% foul area has required an adjustment in data, analyses, and charts. However, the error has had little effect on the general message to date: there is statistical evidence that foul area affects strikeouts by hitters, and by inference, pitchers as well. The magnitude of the effect is yet to be accurately measured, however.

In addition, the error will require a small adjustment in a number of subsequent posts, including those regarding overall foul area, SO/ square foot, etc. These will be performed as time allows.

By adjusting the high-strikeout, high foul area Senators of '54-61 in the analysis, an interesting observation comes to light. If you're a poor club playing in a big stadium at that time (e.g., Kansas City, Washington), the effect of high SO by hitters plus the effect of more foul balls caught on the field (larger foul area) and not going into the stands, isn't a good recipe for success. Only exceptional team pitching might theoretically overcome it. Washington....highest in hitters' SO..... high in foul area....lowest in the American League standings!

I am trying to build a fielding metric using gameday, but I'm not very good with computers. I have mySQL installed, and I want to use baseball on a stick because I can get minor league data for BBOS too and Mike Fast's parser script dosen't work for me. Does anyone know how to use baseball on a stick? I have python installed, but when I try to run the scripts that load the games, nothing happens. Please can someone help me, as I can't use computers for my life.

It is tough to compare two completely different players like Michael Bourne and Albert Pujols. There is no easy way to have all of the categories weigh in and you can just add up there stats and compare them. Homeruns are more difficult to come by than a RBI, so therefore should have more value to each one that a player hits. So what I have created is a method that weighs each individual stat for the players. The stat is called PAR.

I am basing this stat off the average stats ,of my main fantasy league's 8 team standard format, over the past couple years and I found the following averages, 1040 Runs, 1038 RBIs, 272 HRs, 164 SBs, and a batting average of .272. These come from your standard league roster of C, 1B, 2B, 3B, SS, CI (corner infielder), MI (middle infielder), and 5 outfielders. So for the statistic I am going to say that Runs and RBIs have the same weight of 1. I am going to give HRs, a weight of 3.8 (average number of runs/ average number of hrs (1040/272)). So this means if player x hits 26 homers he will have a PAR of 100, you must forget about his other stats for the example. I then used the same method for figuring out the weight of stolen bases which is 6.3 (1040/164).

So as you can see homers and stolen bases contribute more to a player’s PAR than that of RBIs and Runs. So for example a player that posts the line of 10 HRs, 100 Runs, 65 RBIs, and 35 stolen bases will have a PAR of roughly 424. A player who hits 30 Hrs, 100 Runs, 110 RBIs, and 5 SBs will have a PAR of roughly 365. I know there are some of you who are saying that the stat puts too much emphasis on stolen bases, and yes if you draft a team solely based on PAR you may have team that has a good number of base stealers. But you have to think, a player who gives you 50 stolen bases is a huge asset, but his PAR contribution from HRs and RBIs will likely be lacking.

So overall the stat gives you a good idea on how the player performs in the four offensive categories, and how he will contribute to your team.


Preliminary Top 20 Projected PAR
527.1 Jacoby Ellsbury 526.4 Matt Kemp 471.3 Jose Reyes 465.3 Justin Upton 455.3 Hanley Ramirez 422.7 Jose Bautista 416.1 Carlos Gonzalez 413.9 Albert Pujols 403 Dustin Pedroia 395.3 Joey Votto 390.9 David Wright 380.1Miguel Cabrera 374.7 Troy Tulowitzki 372.1 Evan Longoria 366.2 Mark Teixeira 356.9 Prince Fielder 354.4 Josh Hamilton 347.3 Adrian Gonzalez 346.6 Robinson Cano 297.7 Ryan Zimmerman

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Despite losing Carl Crawford to free agency last year, the Tampa Bay Rays had one of the best outfields in all of baseball. For the first part of the season, Matt Joyce, B.J. Upton and Sam Fuld manned the outfield. During the second half, top prospect Desmond Jennings took away most of Fuld’s time. At first glance you wouldn’t think that a combination of these four would be one of the better outfields in all of baseball. If you dig a little deeper you will notice that they combined for a total of 13 WAR, which was good for 8th overall in all of baseball. Offensively, they had the 7th best wRC+. Defensively, the Rays came in second in UZR and first in DRS.

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I've been looking for one good xBABIP calculator. The best I've found so far was slash12's which was posted on this site. I decided to test it and make my own xBABIP. The tests are from 2002-2011.

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This, and Game 7 against my Braves, is the reason why Morris is getting HOF consideration. I know others have shown that he did not have a uncanny ability to allow runs more often only when he had sizable leads. I am showing another, even if it's a less arduous, way that this wasn't true. Using B-R's HR Log, I found the mini-table that shows how far ahead/behind a team is when the home runs are allowed. For this study, I only counted the HR allowed when the pitcher was up 4+ runs. For example, Morris allowed 57 of his 389 HR - 14.7% - up 4 or more runs. Here is a table of 19 pitchers who primarily played from 1960-1995 and their respective percentages.

Morris is high on the list, but not enough to warrant his "pitch to the score" reputation. Of the pitchers ahead of him, Blyleven was much, much better, Tiant was better, and Kaat and Martinez were nearly as good. There are many limitations to this statistic, but it's pretty safe to say Morris was not the pitcher many people think he was.