A few months ago, I wrote an article for this series in which I looked at how home plate umpires can affect pitcher performance. The main thrust of the piece was that the power these umps have to determine balls and strikes can be an important factor in the success of a hurler on a given day. Thus, when selecting a pitcher for FanDuel play, I suggested that it is incumbent upon users looking for an edge to choose someone who can make use of a favorable official whenever possible.
As it turns out, there is another person involved in the game that can influence the outcome of a start for a pitcher. While itís likely not surprising to anyone that a catcher can play a part in the result of a ballgame on the receiving end, current research in the area of pitch framing tells us that the extent to which this is the case could make a great backstop the most valuable player on the field. This week, weíll become familiar with what constitutes pitch-framing research, and delve into how we may be able to use it to make more informed decisions regarding our plays going forward.
There is an ongoing debate in the analytics community about just how much value should be placed on pitch framing, as some confusion exists regarding how the credit for a called pitch should be divided amongst the pitcher, catcher and the umpire, but there is little question that an adept framer can help the pitcher succeed in some capacity. Matthew Carruth over at StatCorner
has taken the time to give a detailed explanation of the language of framing:
nZ- The number of pitches caught within the strike zone
nO- The number of pitches caught outside the strike zone
zBall - The number of called balls caught in the strike zone
oStr- The number of called strikes caught outside the strike zone
zBall / nZ = zBall%-
The percentage of pitches called a ball that are caught in the strike zone
oStr / nO = oStr%- The percentage of pitches called a strike that are caught outside of the strike zone
The usefulness of these kinds of statistics should become immediately apparent, as some catchers, through virtue of their ability, are able to get more strikes for their pitchers than others. A look at the 2014 leaders
in this regard lets us know that Padres catcher Rene Rivera
is at the head of the pack with a 10.1 percent oStr rate (minimum 4,000 pitches) while Cubs backstop Welington Castillo
tops the opposite list with a 17.6 percent zBall rate.
How can we use this information to our advantage? I noted above that there is some dispute over which of the three individuals who control the amount of called balls and strikes can lay the greatest claim to their existence. Thanks to previous research, however, that is not a problem we as FanDuel
players need to concern ourselves with. Instead, we can combine pitcher-friendly officials, hurlers with strong matchups, and catchers who can sway the count in the favor of their pitchers in order to find a candidate for selection who has a high probability of delivering a quality performance.
On the flip side, pitchers with shaky control who are throwing to catchers less skilled at framing could help make fine targets for stacking, especially when the man behind the backstop has the propensity to call ball four.
While we canít be sure of the umpires for the majority of the seriesí that begin this weekend as of the publication of this article, we know the Padres will face the Diamondbacks. This could be a particularly interesting set of games as far as this strategy is concerned, as Rivera may well see action behind the plate opposite Diamondbacks catcher Miguel Montero
, who has tallied a 9.8 oStr rate this season, which is the second-highest mark in the league.
It may be quite a while before the baseball research community has a complete understanding of everything that goes into a called strike (or ball), but FanDuel
players wonít have to wait that long, as we can use all the information at our disposal to select picks who have the ability to provide big point totals.