Does it ever seem as though certain Texas Rangers are performing so far beyond their individual offensive expectations that it's completely unrealistic to assume they can keep it up over the long haul?
Conversely, do you ever get the vibe that your favorite Ranger just can't seem to catch a break at the plate - in spite of seemingly smashing line drives all over the ballpark that are conveniently gloved far more often than those of his teammates?
If so, what follows might come as just a tad reassuring.
Three years ago, noted baseball analyst J.C. Bradbury - author of The Baseball Economist and associate professor at Kennesaw State University - devised PrOPS, or Predicted OPS, a new metric that utilized linear regression estimation and an assortment of relevant variables (including line drives per batted ball, ground-to-fly ball ratio, walk rate, hit-by-pitch rate, strikeout rate, home run rate and home park) in attempting to decipher just how much of each player's offensive performance was attributable to luck, be it good or bad.
In his original introduction to PrOPS at The Hardball Times, Bradbury expanded a bit on his methodology:
This model uses estimated weights of hitting performances that are not necessarily officially scored outcomes to generate a predicted OPS, or PrOPS. With this model I can evaluate players by the process with which they reached these outcomes; thereby, hopefully separating useful information from the noise of raw statistics.
While many of these variables (walk rate, strikeout rate, etc.) are official scorebook outcomes, we know that players do happen to have skills in these areas, and that these skills translate directly and indirectly into a player's OPS. I am most concerned with the random bounces of batted balls in play, which is why I included line drives and the groundball-to-flyball ratio in the model. It turns out that these variables are important in predicting a hitter's OPS.
The R2 of the overall regression model was .81, which indicates that about 80% of the differences in OPS from player to player were explained by the changes in the included variables.
Bearing all this in mind, here are the five "luckiest" and "unluckiest" Rangers in the PrOPS department that received at least 100 plate appearances at the Major League level in 2008:
|2008 Texas Rangers - Projected Vs. Actual OPS|
|- - - - -|
A few miscellaneous notes:
? With regard to PrOPS, Bradbury later issues this important caveat:
Now, when I say "luck" I want to be clear as to what I mean. Given the batting statistics included in the regression, PrOPS tells us what all other players in MLB did, on average, based on the variables included in the regression model. You can think of PrOPS as similar to DIPS for pitchers.
It is entirely possible that some of these players got lucky with hitting line drives, striking out, etc.; however, given their actual numbers for these events we would have expected them to perform much differently.
? Had Taylor Teagarden accumulated the requisite 100 plate appearances needed to qualify, he would have placed second in the PrOPS+ department (.058). Milton Bradley (.025), Chris Davis (.024), Josh Hamilton (.015), David Murphy (.014), Gerald Laird (.009), Hank Blalock (-.003) and Ramon Vazquez (-.008) all finished within 25 points of their season PrOPS totals.
? There's a bit of a selection bias built into the bottom five; players who dramatically underperformed were far less likely to rack up the 100 plate appearances required, such as Jason Botts (-.119) and Ben Broussard (-.247) - neither of whom was nearly as terrible in 2008 as we were widely led to believe.