March, 2007

2007 BDBL Farm Report

This is the eighth year I've published this report, so by now you all know how this works.  This year, our esteemed panel of prospect experts includes Jonathan Mayo (MLB.com), Deric McKamey (Baseball HQ), Bryan Smith (SI), Baseball America, Kevin Goldstein (Baseball Prospectus) and John Sickels (minorleagueball.com.)  I assign 100 points to the top prospect on each list, 99 for the #2 guy, and so on.  I then tally up all the points and make fun of the teams that score the lowest.

In the past, I've double-counted Sickels' lists, because he has issued two separate rankings (one for hitters, another for pitchers) for the past several years.  But this year, I've decided to give the players on his lists the same weighting they would have if Sickels weren't such a big ol' bag of wuss and issued one master list like everyone else in the world.  Other than that, the process hasn't changed.

The question you may be asking yourself is: What's the point of this?  I know that's the question I ask every year when I spend countless hours putting this report together.  After all, this study doesn't really reflect the quality of a team's young players.  (That's something I attempted to do last April.)  Nor does this study even truly reflect the quality of a team's farm system, since it doesn't account for high school or college players.  Nor does it include Japanese talent still playing in Japan.  Nor does it accurately represent the Japanese "rookies" now playing in the U.S. -- at least, not consistently, since some prospect experts include these players in their rankings and some don't.  Nor does it include minor leaguers who graduated to MLB and lost their "prospect" status, but then returned to the minor leagues for two years, like B.J. Upton and...well, B.J. Upton.

So what on earth does this study prove?

Nothing really.  It's just for fun.  It's a snapshot in time, showing how the players on your team who are considered "prospects" compare to other team's "prospects" at this instant in time.  Nothing more, nothing less.

Does a high or low ranking in this study really mean anything in terms of wins and losses?  Well, last year, I showed that there has been a significant correlation between farm ranking and team performance.  But does this mean that great farm systems make great teams?  Or does it mean that great teams are more likely to have great farm systems?  Who knows.  If nothing else, this annual report gives us something to talk about on the message board, so it has some value, right?