The U Files # 74: Reinforcement Review

The Mets are in a better position then they have been at this point in recent prior seasons; currently hanging on the fringes of contention. Whatever their chances of actually pulling off another Amazin' Mets upset ™ , the team is taken seriously enough that there is buzz about potential reinforcements. In the Pacific Nothhwest, the predictable rains have come – now on the Mariners' hopes. Pitcher Freddy Garcia may be traded before he reaches free agency. (Free Preview of Premium Content)

Freddy Garcia was acquired by the Mariners as a key to the trade of Randy Johnson, which should give one a pretty good idea of how well his talent is regarded. Though he pitched well at first, after two promising years his performance fell off. For the years 2002 and 2003, his lowest ERA was 4.39. The key to his performance is his home run rate. In his good years, a key to his success was his ability to keep the ball in the ballpark. The key component to his disappointing recent years is his failure to do so; in each of his letdown years he surrendered over 30 home runs.

If the Mets are to acquire Garcia, we should have some idea of what to expect. To this end I have done a projection. There are a number of projection systems. The most advanced is PECOTA, the brainchild of Nate Silver of Baseball Prospectus. This system uses performance in five statistical components to compile a list of the most comparable players in history, and uses their careers to forecast the career of the player on trial.

For those lacking the means to run such a system, there is a way of projecting for the common fan. Thousands of like minded folk use them, and the results of these low tech methods usually fall in line with the results of the more advanced systems. These projections follow a straightforward formula. Essentially they are generated from a weighted average of a sample of years (preferably three or more), adjusted for park and league where appropriate, and using regression to the mean where appropriate. It is also possible to adjust for age. For pitching projections, sabermetric wisdom suggests one first calculate the appropriate component statistics (strikeouts, walks, home runs allowed, and hit rate on balls in play), then calculate runs from these. In this case I use a linear weights formula.

In the case of Garcia, adjustments need to be made for a change in home ballpark and league. Park factors can easily be calculated for each component using home and road splits. Basic park factors are nothing more than home component per home out, divided by road component per out. These factors are for the home park; to apply them to full season data they are regressed by one half towards the mean (the mean for park factors is 1, which represents a perfectly neutral park as it regards the component). Park factors are most commonly expressed as the run factor; to be most accurate one uses component factors.

Both Shea Stadium and Safeco Field are pitcher's parks, though the profile of each park is different as it regards the appropriate components. League factors were also calculated for each of the years used. As I included 2004 to date in the sample and these data come in a small sample, these factors have been regressed more heavily. A factor of 1.000 is neutral, numbers below one indicate a park that reduces the component, and factors over 1 indicate a park that increases a factor.

Park Factors

Strikeout

Walk

Home Run

$H

Shea Stadium

1.016

.9957

.9404

.9912

Safeco Field

1.013

1.020

.9444

.9444



With these factors in hand we can thus translate Garcia's recent performance:

Year

IP

H

SO

BB

HR

$H

R

ER

ERA

2001

238.2

206

171

68

15

.259

84

75

2.82

2002

223.2

238

188

64

29

.302

118

107

4.31

2003

201.1

203

151

72

30

.277

108

97

4.34

2004

63

58

50

18

4

.280

24

20

2.86



With these translated data, the projection is an average of these component numbers, weighted by inning and with recent years counting for more than earlier years. For the year 2001, the weight was 238.6666 times 1, for 2002 it is 223.6666 times 2, up to 2004 (63 * 4). Thus we come to these projected rates: 2.825 bb/9, 6.910 SO/9, 1.045 HR/9, and $H of .280.

Adjusting his stats to the 2003 NL rates, we get: 2.790 bb/9, 6.87 SO/9, 1.083 HR/9. With these rates we can generate this line for Garcia:

IP

H

SO

BB

HR

R

ER

ERA

220

219

168

68

26

106

95

3.89



Naturally, this falls between the two extremes of Garcia. He has the potential to pitch better than this; however this line is an accurate reflection of the "true" level he has performed at.

Subscribe to NYfansonly.com today! Only $79.95 brings you one full year of Mets Inside Pitch subscription (10 issues), FREE Mets' Yearbook (while supplies last), Total Access Pass, and all premium content on NYfansonly.com, Scout™ Player and Roster Database (including the 'Hot News' at the top of the site), Breaking News and Information, Total Access to all TheInsiders.com Websites, and Player Pages, detailing the progress and careers of players from high school, the minors, and the pro ranks.

Sample the NYfansonly.com Total Access Pass™ at no risk for 5 days, then pay only $7.95 or $21.95. If you want to save 2 months off the monthly subscription price, simply choose the annual NYfansonly.com Total Access Pass™ at $79.95.

Subscribe to NYfansonly.com




Do you have an opinion on the Mets? Be sure to let us know on the message board. NYfansonly.com is always looking for die-hard Mets fans who would like to be writers for the site. Click here to learn more on how to become a Mets beat writer for NYfansonly.com.


Amazin Clubhouse Top Stories