Friday, October 17, 2008

What are the best MLB starting pitching free agents available for the 2009 season?

Question: What are the best MLB starting pitching free agents available for the 2009 season?

Note: I asked Tom Tango to comment on my methodology and here is his response: http://www.insidethebook.com/ee/index.php/site/comments/fip_extended/

Note: I did an update of pitcher that I believe the Royals will target:

FA Type Player Age BB K PA GB PPQ
Target Randy Wolf 32 547 1227 6303 1611 0.287
Target Brad Penny 30 475 1032 6179 2082 0.326
Target Braden Looper 34 309 569 4201 1637 0.335
Reclamation Carl Pavano 32 301 692 4660 1625 0.328
Reclamation Mark Prior 28 223 757 2771 655 0.358
Reclamation Matt Clement 33 650 1217 6189 2056 0.324
Reclamation Freddy Garcia 32 554 1264 7277 2370 0.326
Reclamation Mark Mulder 31 412 834 5562 2303 0.366
Chance Tony Armas 30 431 690 4055 1141 0.261
Chance Jason Jennings 30 477 705 4760 1603 0.284

Target – Pitcher the Royals should go after – young and good enough to help, but not too good to break the bank.

Reclamation – Pitcher with major past injuries and will be more of a chance – 1 year deal to turn career around.

Chance – Not the greatest pitcher, but may be signed for AAA/Pen and can be moved to starter

Why I asked the question: I wanted to see what free agent starting pitchers were available and the quality of the pitchers

Analysis:

I have been looking for a while to find a stat that uses only those attributes that are not effected by external factors that tell the strength of a pitcher. This is very important when comparing pitchers on different teams. W-L records are heavily determined by the teams offense, not the pitcher. Pitchers ERA is effected by how their bullpen handles inherited runners. Home Runs are determined by stadium elevation, distance to fences, wind direction and strength.

I had in the past like FIP (http://en.wikipedia.org/wiki/Defense_independent_pitching_statistics) as a measure, but because it takes HR into account and these can vary from one stadium to the next.

Another problem is that the attributes need to also be correlated from one season to the next. Baseball Prospectus,in the book Base ball Between the Numbers, examined what usefullstats are correlated from one season to the next and here are their results

Statistic - Year-to-year correlation

Winning percentage - .204

Batting average on balls in play (BABIP) - .272

ERA - .380

Home runs per batter faced - .470

Hits allowed per batter faced - .499

Walks (W) per batter faced - .676

Strikeouts (SO) per batter faced - .790

Ground ball (GB) percentage - .807

With the preceding information, a formula that takes W, SO and GB% into account was created.

First good events for the pitcher, SO and GB, will be given positive values, while BB will be subtracted away. The only problem is that not all ground balls hit into play will be an out. I decided to use the data from the work of Voros McCracken on BABIP historical determined that on average 29% of all balls hit should be hits and the rest should be outs. So GB will be multiplied by .71, getting the number of the ground balls will turn into outs. Finally the extrapolated number of GB outs and SO for the season are added together, W are then subtracted from the total and then the total is divided by the total number of batter faced over the season (TBF). Here is the equation:

(SO – W + (.7 * GB))/TBF

Currently I call the total Predictable Pitcher Quality (PPQ) until I come up with a more inventive name.

This stat is great way to compare pitchers and see how the rank without outside effects on them, stadiums, bullpen strength, run support, quality of competition, etc. As always I would love to have any feedback on the subject.

Here on the results of the available free agents and their PPQ number. Also the main starting pitchers for the Royals next season are included





2008



2007



PLAYER Age TEAM GB BB SO TBF PQ GB BB SO TBF PPQ
Derek Lowe 35 LAD 390 45 147 851 0.441 398 59 147 831 0.441
CC Sabathia 28 CLE/MIL 325 59 251 1023 0.410 326 37 209 975 0.410
Mike Mussina 39 NYY 306 31 150 819 0.407 217 35 91 656 0.317
Andy Pettitte 36 NYY 333 55 158 881 0.381 331 69 141 916 0.332
A.J. Burnett 31 TOR 302 86 231 957 0.372 243 66 176 691 0.405
John Lackey 29 LAA 223 40 130 675 0.365 307 52 179 929 0.368
Randy Johnson 45 ARI 215 44 173 778 0.359 56 13 72 233 0.421
Ryan Dempster 31 CHC 279 76 187 856 0.358 93 30 55 282 0.320
Ben Sheets 30 MIL 244 47 158 812 0.347 160 37 106 592 0.306
Braden Looper 33 STL 325 45 108 842 0.345 254 51 87 746 0.287
Jon Garland 29 LAA 347 59 90 864 0.317 289 57 98 883 0.276
Jamie Moyer 45 PHI 281 62 123 841 0.306 262 66 133 867 0.289
Randy Wolf 32 HOU/SDG 222 71 162 823 0.299 130 39 94 458 0.319
Brad Penny 30 LA 155 42 51 426 0.276 305 73 135 865 0.318
Paul Byrd 37 BOS/CLE 227 34 82 761 0.272 274 28 88 835 0.302
Oliver Perez 27 NYM 174 105 180 847 0.232 166 79 174 765 0.276













Zack Greinke 24 KAN 258 56 183 851 0.361 118 36 106 507 0.301
Gil Meche 30 KAN 246 73 183 886 0.319 319 62 156 906 0.350
Luke Hoechaver 25 KAN 228 47 72 566 0.326




Brian Bannister 27 KAN 237 58 113 811 0.272 230 44 77 683 0.284
Kyle Davis 25 KAN 144 43 71 487 0.264 174 70 99 628 0.240


6 comments:

Dave said...

Are you aware of xFIP at the Hardball Times? It takes FIP, but substitutes the major league average home run rate per outfield fly.

Jeff said...

Dave - Thanks, xFIPs is definitely than just FIPs. The one bit of information I liked that best is that ground balls correlate from one season to the next. What I need to find now is how well a pitcher's fly ball rate correlates from one season to the next. -Jeff

Fire Jim Leyland said...
This comment has been removed by the author.
Mike Rogers said...

Jeff,

I got here via Tango's blog and just thought I'd say that I've done something similar using K%, BB%, GB%.

(K% = (GB%*.72)-BB%

Here's my blog on it.

Mike Rogers said...

Damn. The "=" was supposed to be a "+". That's my 3rd time commenting on this post, haha. Sorry.

Jeff said...

Mike - its exactly the formula - thanks for the information