Monkeys Running the Mariners Front Office

Sabermetrics, the statistics revolution in baseball, gets a lot of flack for focusing too much on numbers that only exist in vacuums, and not enough on “the intangibles.” Ok, I’ll buy that statistics and data don’t have the answers to everything, but I see Sabermetrics as a more logical approach to making smart baseball decisions. Like don’t sac bunt in situation A because you actually reduce the expected number of runs you will score. Or don’t bring in reliever B because you have a gut feeling he’s due for a good performance when his splits against the next three batters are atrocious.

How about don’t dump your THIRD best reliever, Kanekoa Texeira, to bring up just about your worst, Sean White. This is what the Mariners just did. There’s no reason for me to repeat everything Mariner’s blogger Dave Cameron already wrote, so read his article here.

Data can help us fill in the holes that our brain leaves out, and aide us in making decisions without emotional bias, to which we humans are so susceptible. There’s a great scene in Bull Durham where Kevin Costner is talking about the difference between a .250 hitter, and a .300 hitter. In a 25-week season of about 500 at bats, that’s a one-hit-per-week difference. If you went to the ballpark every day for a week–or even a year–and didn’t look at any stats or box scores, you would not be able to tell the difference between Ichiro Suzuki and Josh Wilson, in terms of average, or OPS, or whatever. While batting average is not the most indicative stat of a player’s value to his team, the point is that only statistics can highlight minute differences in players that will eventually add up over the course of a season.

To ignore data collection and logical reasoning because you’re unwilling to believe that conventional statistics such as batting average and ERA might not be the best barometers of talent is simply stupid. There is a logical process behind statistics like xFIP (a predicted ERA) that attempt to spot out the questionable ERAs and predict a likely regression.

For instance, let’s look at all 52 pitchers who pitched a “qualifying” number of innings in both 2008 and 2009. Players’ 2008 xFIPs accurately predicted their respective rises and falls in 2009 ERAs in 38 of the 52 pitchers, good for 73%. Looking at the 58 starters who pitched enough innings in both 2009 and thus far in 2010, the 2009 xFIPs were able to accurately predict rises and falls in the 2010 ERAs in 60% of the pitchers. This was likely a slightly lower figure mostly because we’re not even halfway through this season, and true abilities will even out in the long haul.

This shows that xFIP is not exactly god-like in being able to predict future changes in ERA, but it’s significantly better than a monkey in the front office or dugout flipping a coin. Making “gut decisions” is the equivalent of flipping a coin and hoping you were right, and that’s what the Mariners organization has decided to do this year in a number of cases. This xFIP example is just one of many ways that an organization can attempt to better value its players and predict their futures. And it’s FREEEEEEE! So use it, Ms.

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