“The strike zone is that area over home plate, the upper limit of which is a horizontal line at the midpoint between the top of the shoulders and the top of the uniform pants, and the lower level is a line at the hollow beneath the kneecap. The strike zone shall be determined from the batter’s stance as the batter is prepared to swing at a pitched ball.”
But what looks at least reasonably clear on paper is anything but in practice. Indeed, far from every strike called meets the above criteria (not that this is news to any baseball fan). This reality is based — in no small measure — upon how each pitch is “framed” by the catcher.
In 2001, Sandy Alderson, then executive vice president of operations for MLB, initiated a campaign to get the umpires to call the rulebook strike zone. He was especially keen to see the return of the high strike, since virtually all pitches from the belt up were being called balls at that time. Due to modern technology, the various strike zones and umpires can be scrutinized in amazing detail, with interesting results (e.g., the MLB umpire with the smallest strike zone is nearly three standard deviations away from the mean). For example, left-handed hitters have a wider strike zone (2.3 inches wider, to be exact), but a smaller strike zone overall. And the stats geeks have clearly established that the strike zone influences the game – a lot. Most fundamentally, smaller strike zones mean more runs and vice versa. Indeed, the strike zone changes in a variety of situations: by inning, by pitcher age/experience, by pitcher control, by home/away team and more.
The most likely and comprehensive explanation for these disparities? How catchers tend to set up and handle pitches – to try to get balls called as strikes (and to get the call on all strikes) based upon how the pitch is “framed.” As summarized by Mike Fast in Baseball Prospectus with respect to the outside strike, “a mountain of circumstantial evidence points to the umpire [strike] zone being influenced by the location of the catcher’s target, rather than the other way around.” And the data seems to support that hypothesis.
Listen to long-time catcher Matt Nokes:
“Predictability is the key to getting borderline calls. If the pitcher is consistent, then the umpire knows where to be looking. But if the catcher is jerking all around the plate and the ump does not know what is coming in where, it’s going to be harder for him to focus on those close pitches and you won’t get them. If the pitcher is throwing consistently where the catcher is setting up, he doesn’t have to be so fine. But if I set up inside and the pitch is on the outside corner, even if it is a strike, we’re not likely to get that call. Even if the pitch is over the outer half of the plate, it will be called a ball, because it missed the catcher’s target so bad. That’s just the way it is.”
Padres back-up catcher John Baker is much more succinct: “If you’re jerking your glove around, you’re basically signaling to the umpire that it wasn’t a strike.” The primary issues in “losing” a strike are missing the target, catcher glove movement and catcher head-drop.
Analysts have looked at the issue of catcher framing and discovered dramatic and repeatable differences in framing performance among catchers, often to the extent of 20 runs per season. The best framing catchers (like Jose Molina) extend the strike zone well beyond its theoretical size while the worst (like Ryan Doumit) actually shrink it. Remarkably, the run differential between Molina’s team and Doumit’s is more than 60 runs per 120 games – essentially half a run per game.
How an issue is framed is also extremely significant for investors and within psychology generally. Sometimes it’s very simple. For example, we prefer the middle option of three far more often than when it is a choice of two and too many options means we tend to be paralyzed by choice. However, these examples are more about contextual inference than about framing.
The framing effect is a strong cognitive bias such that people react differently to particular choices depending on how it is presented (“framed”), most prominently whether it is presented as a loss or as a gain.We want to avoid a certain loss but we also favor a sure gain over a probabilistic gain and a probabilistic loss over a definite loss. Gain and loss in this context are descriptions of outcomes (e.g., lives lost or saved, disease patients treated or not treated, money gained or lost).
Accordingly, we tend to avoid risk when a positive frame is presented but seek risks when a negative frame is presented. As with so many instances when behavioral and cognitive biases are the issue, the seminal research was performed by Daniel Kahneman and the late Amos Tversky. Participants in this study were asked to choose between two treatments for 600 people affected by a deadly disease based upon two problem sets (choice percentages in parentheses).
- If Program A is adopted, 200 people will be saved. (72 percent)
- If Program B is adopted, there is a 1/3 probability that 600 people will be saved, and a 2/3 probability that no people will be saved. (28 percent)
- If Program C is adopted 400 people will die. (22 percent)
- If Program D is adopted there is a 1/3 probability that nobody will die, and 2/3 probability that 600 people will die. (78 percent)
From a probabilistic standpoint, these choices and results have the same expected result and are thus equivalent (a 66 percent chance of death for each person) but with outcomes either certain or within a range. How the problem is framed is the key factor with respect to our likely choices. In Problem 1, we prefer the certainty of saving people (“200 people will be saved”) and are thus risk averse. We want to avoid the choice that could result in everyone dying even if nobody dying is a possibility. But in Problem 2, most people are risk-seeking because they want to avoid the certainty of 400 people dying, even at the potential risk of all 600 people dying. Subsequent research has shown that this asymmetry of subjective values carries over into finance and that the pain of losing a sum of money is greater than the pleasure of winning the same amount – roughly two-to-two-and-a-half times greater. Financial advisors are well aware of such loss aversion, and all investors should be.
The implications of this “prospect theory” are profound. How something is framed may cause you to do something you otherwise would not do. Most significantly, when people rely on a single, “narrow” frame, even when evaluating outcomes with multiple prospects, they are most susceptible. On the other hand, multiple, “broad” frames provide a richer perspective and provide some protection from our inherent biases.
Thus investors who “broadly” frame investing decisions as portfolio-level decisions, rather than “narrowly” framing them as independent choices about individual investments tend to trade less often overall and to make simultaneous integrated portfolio-level decisions, leading to stronger and more diversified portfolios. Moreover, narrow framers who focus independently on individual investment decisions often exhibit the “disposition effect,” a well-documented observation that investors are more willing to sell winners in their portfolio but tend to hold on to losers – the exact opposite of what they should do.
Whether we’re talking about Major League pitching, managing a portfolio or even a sales pitch, how things are framed can make all the difference.
Update (5.15.13): Grantland has a terrific new article about catching and pitch framing available here.