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AOPS 2004
Publication Date: September 7, 2004
The Power of a Name?
At one level, what you call a statistic wouldn't seem to matter much in the long run; I mean, it's just a name. On the other hand, there is power in names. For example, there's been an average of one college a year to change names since I started doing this (the latest is Troy State, which recently changed to Troy University). While I generally refer to these dismissively as MBA-driven, it is true that a name change can shake up the image of a place, both internally and externally. Likewise, regardless of their merits, "Runs Created" gets its point across much better than "Value over Replacement Player". Having created the worst-named metric in history (I mean, who uses the word "iterative" in a publicly-available system?), I'm aware of the benefits of a good name.
One side effect of this is that there's a tendency within the analytical community to cling to a name once it's given, even though the statistic it describes may have been modified or evolved as more information became available. Bill James, for example, has released at least six different versions of the RC formula by this point. A variation of that is to add a number to the end and then forget about it, the way the Baseball Prospectus authors did with PAP and PAP3.
A couple of years ago, based on the best information I had, I created a statistic called Adjusted OPS, or AOPS for short. This year, because I have better information, I'm adjusting the formula. Given the above, I think it's reasonable just to keep the name the same -- I don't think there are lots of folks sitting around out there tracking AOPS. The new formula includes park factors, which I now have and didn't then, and some thinking on the difference in run factors and on-base factors:
TPF SoS
AOPS = OPS / SQRT( --- ) * ---
100 100
OPS = OBP + SLG
OBP = On-base percentage
SLG = Slugging average
TPF = Team park factor
SoS = Strength of Schedule
The team park factor is the average park factor for all parks the team played in during the season. Park factors are computed based on runs; the square root represents the normal relationship between on-base percentage and run scoring.
This formulation works, to the extent I can prove it. For example, these factors produce statistics which correlate best to minor league stats for the same players in the same year.
The Players
So, if we do all this work to take out the context, who actually performed the best last year? Here's the top 100:
East Carolina Ryan Jones 1.425 Stanford Jed Lowrie 1.422 Cal State Fullerton Kurt Suzuki 1.375 Florida State Eddy Martinez-Esteve 1.366 Clemson Brad McCann 1.360 Nebraska Alex Gordon 1.354 Florida State Stephen Drew 1.349 Mississippi State Brad Corley 1.346 South Carolina Steve Pearce 1.338 Arkansas State Brad Hayes 1.298 Louisiana-Lafayette Dallas Morris 1.291 South Carolina Landon Powell 1.286 The Citadel Chip Cannon 1.282 Coastal Carolina Mike Costanzo 1.281 Louisiana-Lafayette Rhett Buras 1.280 Miami, Florida Jim Burt 1.278 Vanderbilt Warner Jones 1.271 Georgia Tech Mike Trapani 1.269 South Carolina Brendan Winn 1.265 Louisville Mark Jurich 1.264 Northern Colorado Patrick Perry 1.260 Stanford Danny Putnam 1.259 Mississippi Stephen Head 1.256 Georgia Josh Morris 1.254 South Alabama Adam Lind 1.238 Florida Ben Harrison 1.235 North Carolina Marshall Hubbard 1.234 Tulane Scott Madden 1.230 Louisiana State Jon Zeringue 1.219 Florida State Ryne Malone 1.213 North Carolina-Charlotte Jamie Rusco 1.213 Long Beach State Jason Vargas 1.212 East Tennessee State Caleb Moore 1.211 East Carolina Ryan Norwood 1.211 Cincinnati Steve Pickerell 1.210 Southern Darren Clark 1.207 Vanderbilt Cesar Nicolas 1.203 Georgia State Tim Burgess 1.202 Miami, Ohio Mike Ferris 1.200 William and Mary Chris Rahl 1.200 Florida Atlantic Jeff Fiorentino 1.199 Stanford Jr John Mayberry 1.198 Fresno State Richie Robnett 1.191 Wichita State Drew Moffitt 1.189 North Carolina Chris Iannetta 1.185 Texas-Arlington Hunter Pence 1.183 Clemson Lou Santangelo 1.179 Central Florida Matthew Lafleur 1.179 Louisiana-Lafayette Phillip Hawke 1.177 Missouri Cody Ehlers 1.175 Gonzaga Bobby Carlson 1.174 Miami, Florida Ryan Braun 1.174 Louisiana State J. C. Holt 1.172 Arkansas State Brad Burkhead 1.171 Arizona State Dustin Pedroia 1.171 Washington Zach Clem 1.171 Miami, Florida Erick San Pedro 1.167 Texas Curtis Thigpen 1.167 UC Irvine Jaime Martinez 1.160 Jacksonville Donald Brickle 1.159 Notre Dame Matt Macri 1.159 Miami, Florida Paco Figueroa 1.156 Nicholls State Anthony Hatch 1.154 Washington Kyle Larsen 1.154 Florida Matt Laporta 1.153 Texas Christian Chad Huffman 1.152 Northeastern Jeff Heriot 1.151 Rutgers Jeff Frazier 1.150 Stetson Chris Westervelt 1.149 Tulane Matt Barket 1.149 North Carolina-Asheville Sherman 1.147 Pittsburgh Pj Hiser 1.146 James Madison Mike Butia 1.146 Pepperdine Steve Kleen 1.146 Bowling Green State Nolan Reimold 1.145 Eastern Michigan Brian Bixler 1.145 Florida C. J. Smith 1.143 College of Charleston Brett Anderson 1.139 George Mason Shimer 1.138 Cal State Northridge Michael Paulk 1.138 Kentucky Caleb Stewart 1.138 Texas Tech Josh Brady 1.136 Gonzaga Kiel Thibault 1.129 Southern Mississippi Ryan Frith 1.129 Lamar Jordan Foster 1.127 Birmingham-Southern Adam Tucker 1.127 Southern Andrew Toussaint 1.126 Stanford Brian Hall 1.126 Elon Gary Morris 1.125 Belmont Jason Warpool 1.125 Oregon State Mike Lissman 1.125 Miami, Florida Brian Barton 1.124 Southern Mississippi Jarrett Hoffpauir 1.124 Oklahoma State Josh Fields 1.122 Tulane Greg Dini 1.120 Baylor Josh Ford 1.120 South Carolina Michael Campbell 1.117 Houston Kevin Roberts 1.117 Arkansas State Chris Rich 1.117 Tulane Brian Bogusevic 1.116
While I won't read the list to you, I will point out that Jones is apparently coming back for his senior year, so MLB will get another chance to get it right.
Next year, I plan to run AOPS on a real-time basis in the Filing Cabinet, so hopefully you'll be able to track it as the season unfolds.
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