Let's make up an experimental productivity stat. This is going to be very long and kind of complex, so if you don't have enough time or aren't into stats, thanks for stopping by...but come back another day.

What I'm hoping is that I can loosely (yes, LOOSELY) figure out a player's production in comparison to his salary, and use both old school performance gauges (runs scored and RBI) in conjuction with newer metrics (OPS and total bases), and come up with a number to bounce off of a player's salary.

(Runs scored + RBI + Total Bases/3) x OPS/Salary (in millions)

What I'm hoping this will do is take into account a few things: 1) While runs scored and RBI are mostly a function of opportunity, they are of direct help to the team, plus you cannot rack up big totals of these if you are hurt a lot of the season. Total bases are thrown in to balance possible lack of opportunity to score runs and drive them in, and to factor in things like stolen bases and walks (as a raw number). 2) OPS is the sabermetric which will help out players who might not be in prime run scoring or RBI places in the lineup (leadoff, bottom of the order), yet are being productive.

Bear with me. I really do think this makes sense. What I want to do is throw up a few different player types into the mix to see what comes of this. Players who are productive making higher salaries, players who are productive making lower salaries, and players who have missed a large number of games while making a high salary.

Adding the runs scored, RBI, and total bases and dividing them by 3 will basically make it an average score, then multiplying it by the OPS (which is essentially a percentage) will determine how much of that average score the player will get to keep to divide by their salary. Dividing it by their salary will come up with a productivity number per million dollars. Higher numbers are obviously better.

My 1st experimental players to do this on will be some Giants: Ray Durham, Pedro Feliz, and Barry Bonds (three different salary grades), and I will do it for the 2004 and 2005 seasons, collectively, for Feliz and Durham, and do it for 2003 and 2004 for Bonds.

Ray Durham (2004 and 2005): 162 RS + 127 RBI + 441 TB = 730/3 = 243.3 average score

243.3 x an average .817 OPS for 2004 and 2005 makes for a total score of 199

199 / Durham's combined salary for '04 and '05 ($14.4 million) = 13.8 productivity score per million dollars for 2004 and 2005

Pedro Feliz (2004 and 2005): 141 RS + 165 RBI + 484 TB = 790/3 = 263.3 average score

263.3 x an average .754 OPS for '04 and '05 makes for a total score of 199 (believe it or not, same as Durham)

199 / Feliz's combined salary for '04 and '05 ($3.175 million) = 62.7 productivity score per million dollars for 2004 and 2005.

Barry Bonds (2003 and 2004): 240 RS + 191 RBI + 595 TB = 1026/3 = 342 average score

342 x an average 1.350 OPS for '03 and '04 makes for a total score of 461.7

461.7 / Bonds' combined salary for '04 and '05 ($33.5 million) = 13.8 productivity score per million dollars for 2004 and 2005.

I don't know if that's a satisfying result, so let's take two examples of abnormally high production with a lower salary: Albert Pujols for 2003 and 2004, and Miguel Cabrera for 2004 and 2005.

Albert Pujols (2003 and 2004): 270 RS + 247 RBI + 783 TB (yes, 783) = 1300/3 = 433.3 average score

433.3 x an average OPS of 1.089 for '04 and '05 makes for a total score of 471.9

471.9 / Pujols' combined salary for '03 and '04 ($7.9 million) = 59.7 productivity score for 2003 and 2004

Miguel Cabrera (2004 and 2005): 207 RS + 228 RBI + 653 TB = 1088/3 = 362.6 average score

362.6 x an average OPS of .912 for '04 and '05 makes for a total score of 330.7

330.7 / Cabrera's combined salary for '04 and '05 ($.69 million) = 479.3 productivity score per million dollars for 2004 and 2005

One more type, just for fun -- high salary and low production. Let's go with Adrian Beltre and Jim Thome of 2005.

Adrian Beltre (2005): 69 RS + 87 RBI + 249 TB = 405/3 = 135 average score...yech.

135 x a .716 OPS for 2005 makes for a total score of 96.7

96.7 / Beltre's salary for '05 ($11.4 million) = 8.5 productivity score per million dollars for 2005.

Jim Thome (2005): 26 RS + 30 RBI + 68 TB = 124/3 = 41.3 average score...ow, that hurts

41.3 x a .712 OPS for 2005 makes for a total score of 29.4

29.4 / Thome's salary for '05 ($13.167 million) = 2.2 productivity score per million dollars for 2005.

Okay, I'm done. What I think I ought to do with this is comparisons by position to get an idea of where a player stands in comparison to his positional peers, but for now I'm just throwing it out there to play around with.

Boy, am I a nerd. If you've somehow lasted until this point, tell me what you think, and I will take requests to apply this formula to any two players you want to compare...but I'm only going to do complete seasons at this point, so that means no 2006 comparisons. I don't want to tackle dividing salaries by games played on top of all that other stuff.

## 2 comments:

Are you working on calculation for pitchers?

No, and yes.

No, not at the moment, but yes, I do want to tackle that within the next few weeks -- I have to figure out what stats and metrics to utilize in a way that makes a tiny bit of sense.

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