Baseball Statistics Most Useful in Supporting Roles

Statistics play a more prominent role in the analysis of baseball than any other sport in our country.  They provide the historical background upon which modern-day achievements can be assessed in their proper context.  They help determine the value of players.  Employed fairly and without extraneous agendas, they are quite helpful in forming predictions of future events. 

Baseball is an extraordinarily complex game whereby the line between success and failure is sometimes razor-thin.  The difference between a run-producing “grounder with eyes” and a hard smash resulting in an inning-ending double-play often comes down to nothing more than dumb luck.  The over-reliance on statistics to analyze the game can become overwhelmingly humbling at times because there are so many other factors that cannot be empirically measured.

We observe unfair representations of statistics by agenda-driven analysts out to prove a point.  But the more grievous misapplication of numbers seems to occur when folks rely entirely upon statistics to predict future outcomes.  Baseball statistics are far too variable to be entrusted on their own to project to external criteria.

Yes, statistics have a very important role in baseball analysis.  We can conclude with reasonable certainty that, based on his career numbers, Albert Pujols is probably going to have a decent offensive season.  Larger historical samples predict well to general conclusions.  However, the relationship between statistics and outcomes rapidly dissolves when the sample size is decreased or the outcome becomes too precise.  Our confidence in Pujols is bolstered by the long-standing body of evidence whereas predictions about playerd such as Desmond Jennings and Dan Johnson are far more difficult.  For this reason, we do chuckle sometimes when we observe posters making “guarantees” about players such as Jennings or Johnson.

Baseball predictions are fun.  Often they are just guesses or hunches, but they do trigger discussions.  But actual analysis and logical formations of expectations entail not only a measured use of statistics, but much deeper sources to additional information.  A hitter’s ability to catch up to a David Price heater on a Sunday afternoon may be more predicated on what he did after Saturday night’s game.  A batter’s chances of beating out a worm-killer may be affected by a hammie he’s nursing.  A pitcher’s intense focus on each and every one of his pitches could be impacted by some personal issue.  The point is, there are a myriad of factors that impact any given moment in a baseball game.   

The point is, there is so much more to predicting future outcomes of players and teams than can be derived solely from statistics about past performances.  No one could have ever fathomed BJ Upton would regress to a .240 hitter after his 2007 season.  By the same token, he just may grow up a little, play the game right, become a fan favorite again and eventually exceed all expectations.  But advanced notice of these trends will most likely come from an astute observer who is actually at the games, not the Stat Hound.

Of course statistics have their rightful place in the discussion of our pastime.   Player accomplishments will always be judged almost entirely by their numbers.  Lineup constructions and game strategies are based exclusively on statistics of individual matchups.  But statistics have a lesser role in predicting future outcomes, particularly when assessing younger players.  Rays Country authors are passionate fans who appreciate the incredible complexity of this magnificent game.  Our analyses certainly employ statistics, but we believe it is of paramount importance for us to zealously research the internal validity of the numbers we cite and use reason when predicting outcomes.