I’ve run my defensive projections for 2011 using UZR as the primary input data source.  For a general feel for the methodology read this post.  A couple changes from last year

  1. Instead of using the average FSR for bins of players I’m using the FSR converted to runs as found on Fangraphs as my scouting component number.
  2. I took into account multiple positions this year.  I used the Fangraphs standard position adjustments to convert all UZR values from all positions to a player’s primary position.

As mentioned, this set of data is run with UZR as the primary data input.  Over the next few weeks/month I’ll be running the same process with DRS as an input, TZ as an input, and an average as an input.  I’ll post those files as they become available.

Click here for an excel download
Click here for the google docs version

Quick Edit:  Didn’t explicitly say this anywhere.  The numbers in the files are Runs/150 Games.

GOTW goes up a day early….

From my yet to be published defensive projections (this week probably)

But we’re supposed to be better this year defensively right?

With the Matt Holliday clock now ticking there has been a lot of talk about the plan B options, so I thought it would be a good time to bring out my WAR simulation (which I’ve expanded to include defense).

I looked at the following options that I’ve heard/read about at some time over the past couple of days [Quick update: as Dan at VEB points out this list is not exhaustive, and I’ll try to run at least some of the suggestions people make here or over there]

  • Holliday (hey I was curious) in left and David Freese at 3rd (MH)
  • Erik’s nightmare – AKA Miguel Tejeda at third and Allen Craig in Left (MT)
  • Mark Derosa at 3rd and Craig in Left (MD)
  • Freese at 3rd and an  Craig/Kelly Johnson platoon in LF (KJ/AC)

Here’s the CDF graph

The x axis is position player WAR and the y axis is probability.  For those that are not statistically inclined, the probability is the probability that the respective WAR would not be exceeded.  For example, the probability that the Holliday team won’t exceed the 2009 Phils is ~0.8.  More simply stated, there’s a 20% chance that (based on CHONE offensive and my defensive projections) a Cards team with Holliday would outperform the position player production of the 2009 Phils.

The MT line is under the MD line.

Clearly this exercise doesn’t factor in that money saved could be put towards pitching (I hope to add pitching to the sim this week).  That being said it’s fairly obvious (even without the sim) that Holliday>>these plan b options.  Also of note is that going young and rolling the dice on Johnson is likely better than the proven vet options.  We’ll see what pitching adds to the equation later this week.

Data: Offensive projections from CHONE, defensive projections mine (right sidebar) or CHONE for those with no MLB experience, 2009 data from fangraphs

A few weeks ago I posted a set of defensive projections for SS based on regressing a 3 year average UZR to a population based on the Fan’s Scouting Report created by tangotiger.  After some discussion over  at The Book Blog, I altered my methodology a little and have come up with a set of projections for all positions.

First a quick discussion about the methodology.  The projected values are a weighted average of the

  1. Players 3 year weighted UZR (5/4/3 style)
  2. The UZR mean of the “scouting population” to which the player belongs (more on this in a minute)
  3. The league average (i.e. 0).

The weights are

  1. Effective defensive games over the three year sample (also weighted, so not just the sum)
  2. 125 games
  3. 125 games

which basically means the larger the 3 year sample, the less impact the “regressions” have, which falls under the basic premise of the more data you have the less you need to regress.

The scouting population is determined by where the player ranks in Tango’s Fans Scouting Report (FSR).  I took the last three years of FSR data and found the average UZR/150s for various bins of players (currently done by ordinal ranking, but will likely transition to binning by overall score once 2009 numbers are computed by Tango ).  I then crossed that data with were the specific player ranked in the 2009 voting, with that number becoming the scouting regressing factor.

For those that read my previous post on it, Method 2 was the methodology adopted (as MGL pointed out that it was the correct method).  Anyway on to the results.  First the leaders (with a minimum of 60 effective DGs)

Name Pos UZR/150
Travis Ishikawa 1B 5.6
Chase Utley 2B 10.8
Omar Vizquel SS 9.3
Evan Longoria 3B 11.9
Carl Crawford LF 10.9
Franklin Gutierrez CF 12.2
Jayson Werth RF 11.2

You’ll note that the projections are for UZR/150 so you’d need to utilize an expected playing time to convert these to runs.  For example, I find it highly unlikely that Omar Vizquel will get enough playing time to save ~9 runs, but clearly if he played 75 DGs then he’d save ~4-5 runs.

Now for the laggards

Name Pos UZR/150
Jason Giambi 1B -5.6
Alberto Callaspo 2B -5.7
Yuniesky Betancourt SS -10.1
Edwin Encarnacion 3B -8.9
Adam Dunn LF -14.9
Vernon Wells CF -10.1
Brad Hawpe RF -19.1

For those that want to make the argument that Dunn won’t be playing left field again, second to last went to Delmon Young. For those making the same argument about Giambi, second to last there was Billy Butler. I’m posting the results spreadsheet on google docs with the link over on the sidebar, so feel free to download it and use it for whatever you want. The sheet contains the position the projection is for, the projection itself, 3 year UZR/150, and the effective DGs.

Finally, since this is a Cardinals blog, I wouldn’t leave you without giving you the key returning Cardinal players

Name Pos UZR/150
Brendan Ryan SS 7.2
Colby Rasmus CF 5.5
Albert Pujols 1B 5.0
Ryan Ludwick RF 1.0
Skip Schumaker 2B -5.1
Julio Lugo SS -5.9

A couple of final caveats about the projections. I know there are players missing, and there are definitely player/position combos missing. As a first pass I only projected the position that they had been identified with in the FSR. I plan to remedy that, but it’ll have to wait until the next iteration. Also, I didn’t apply an aging factor, which is clearly not a good way to go about projecting. In his BtB piece Jeff mentioned a -0.7 UZR, but I want to give some thought about how to apply that to UZR/150. Hopefully the next iteration will have some aging factor applied, up until then, apply whatever you see fit. Anyway, download away, and let me know if you have questions/problems.

I tweaked the original a bit and came up with exactly 87 wins this time.

  • This time I used CHONE projections. For some of the more optimistic projections, I scaled down some, as in the case of Molina, Greene.
  • For the pitchers, I used FIP instead of their projected ERAs. I then shaved off a .1 or .2 up or down, depending on the pitcher.

It’s not quite a perfect world scenario, but it does assume everyone but Carpenter remains healthy, so feel free to shave off 2-3 wins in your mind.

You’ll notice there are four tabs.  The 2nd tab I added Orlando Hudson and Randy Wolf.  John Perrotto today said that Hudson has received zero offers to this point and the poor team Nats are biding their time, hoping to scoop him up on the cheap for a 1 year, incentive-laced deal.  I would think the O-Dawg would prefer St. Louis, if the Cardinals are interested.  The downside: He’s a type A, which will make liveblogging the draft over at FR a real bore, at the minimum.  His projection of 2.4 WAR also concludes he’ll bounce back some defensively.

Derrick Goold also earlier in the week tweeted that the Cards are interested in Oliver Perez and Randy Wolf.  Ollie is still probably priced out of the Cards’ budget, while Wolf is more of an injury risk and should come for less $/yrs.  Goold also said the market may push Jon Garland their way.  Bah.  They may as well have offered Looper arbitration.  All three pitchers project to be around equal value, and again, if all goes well, then O-Dawg +  either Perez/Wolf/Looper/Garland could push the Cards up to 90 wins.

The third scenario is the Summer of Colby.  Pushing Luddy to LF, Slick Rick to RF and assuming Colby will provide some darn good defense in CF  bumps the Cards to 88 wins without adding anyone.  (87.7 to be exact)  Combine this w/ the “sign free agents” scenario and it might do the trick. 

The final tab is the ever hopeful, no moves, 90 win tab.  That’s the dreamland scenario of Carpenter winning the comeback player of the year award and Colby having a ROY campaign of a season.   Hope springs eternal.

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