As any proper baseball fan will tell you, part of a catcher’s job is to create the illusion that balls are strikes—and to make darn sure that strikes look like strikes too. “Framing” a pitch, as these antics are known, exploits the fact that what really matters is not whether a pitch actually crosses through the strike zone, but whether the umpire believes it does.
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But a new study suggests that the likelihood of an umpire mistakenly calling a ball a strike (which the authors call “overrecognizing” the quality of the pitch) or mistakenly calling a strike a ball (“underrecognizing” it) is affected as much by who is pitching as by who is catching.
The study, by Jerry Kim of Columbia University and Brayden King, an associate professor of management and organizations at the Kellogg School, examines the cognitive biases that affect umpires in Major League Baseball. The researchers analyzed pitches thrown during the 2008 and 2009 seasons. They wondered: Would higher-status pitchers—those esteemed by teammates, coaches, and fans—receive more favorable calls on similar pitches than lower-status pitchers?
“When you are high status, you tend to get more recognition for your accomplishments.”
The research was motivated by the “Matthew Effect,” a phenomenon whose influence reaches far beyond baseball. It gets its name from a Bible verse that can be summed up as follows: the rich get richer, while the poor get poorer. Part of the Matthew Effect can be attributed to resources. High-status individuals tend to have more resources at their disposal, which they can use to achieve better results. But another part of the Matthew Effect is purely about perception. “When you are high status, you tend to get more recognition for your accomplishments,” explains King. “And that means that it’s much easier for people who are at the top of the hierarchy to … reproduce their success.” A scientific discovery made by an unknown scholar working with a Nobel Prize winner, for instance, tends to be attributed to the Nobel Prize winner, regardless of the other scientist’s contributions. Similarly, in the corporate world, a top administrator may receive disproportionate credit for the accomplishments of a subordinate.
So are similar status biases present in America’s National Pastime? Baseball represents a particularly strong test case because umpires are highly motivated not to be swayed by a player’s status. About a decade ago, Major League Baseball began using technology from a company called QuesTec to objectively determine, after the fact, the accuracy of an umpire’s decisions. This information is then used to incentivize umpires by, for example, assigning more-accurate umpires to lucrative play-off games.
The researchers analyzed whether, even given the incentives to be accurate, umpires would nonetheless favor high-status pitchers, more often overrecognizing their pitches and less often underrecognizing them. In other words, explains King, if status bias plays a role, “we would expect that umpires would want to widen the strike zone for high-status players and they would probably shrink the strike zone for low-status players.”
This is indeed what the researchers find. As an umpire, “you’re 25% more likely to call a real ball a strike for the 5-time All-Star” than for a pitcher with no All-Star appearances,” says King. And the favoritism goes the other way as well: “You’re 14% less likely to call a real strike a ball for a 5-time All-Star” than a non-All-Star.
And, as shown in the infographic at the top of the page, the benefit to high-status pitchers (as measured by the percentage of strikes that are incorrectly called balls) increases as pitches approach the edge of the strike zone. When a pitch heads straight through the heart of the zone, an umpire is likely to correctly call it a strike, regardless of how many All-Star appearances a pitcher has had. “But when there is a lot of uncertainty—when it’s not clear and you’re unsure—then the opportunity for biases to shape your decisions is much greater,” explains Kim.
Having a reputation for accuracy leads to additional favoritism. A pitcher like Greg Maddux—with a reputation for placing pitches wherever he wanted—has an advantage over a pitcher like Randy Johnson, who, though undoubtedly a great player, had a reputation for throwing wild pitches. “The pitchers who benefit the most are those pitchers who have a lot of All-Star experience and they also have a reputation for being somebody who can control the strike zone,” says King.
The unconscious favoritism can be powerful enough to influence the outcome of a game. “These things begin to accumulate,” says King. “The more errors that umpires make in favor of All-Star players, the greater [the] chance that team has of winning.” Every mistaken call in a pitcher’s favor increased his team’s likelihood of winning by 0.3%, while every call against him decreased the team’s chances of winning by the same amount.
A pitcher’s status influences the umpire—but what about the status of the batter? Interestingly, umpires are only modestly predisposed to give high-status batters the benefit of the doubt. This may be because umpires are primarily tasked with assessing the performance of the pitcher, rather than the batter: runs generally speak for themselves.
Catchers have more influence over an umpire’s calls—about as much as pitchers do. But their ability to sway umpires should not come as a surprise, given that they have the power to shape the strike zone. “In the pitcher’s case, it’s simply about who they are,” says King.
The study revealed other sources of bias as well. Additional years in the league favorably benefited pitchers, as did being Caucasian. Umpires were 10 percent less likely to expand the strike zone for African American pitchers than Caucasian pitchers, but race did not seem to influence underrecognition of actual strikes. Umpires were also likelier to favor pitches thrown by the home team or when the ratio of balls to strikes was high: with a count of 3-0 (meaning the batter is one ball away from walking to first base), the odds of overrecognition increased by nearly 20%.
“People have said that baseball is a lot like life,” says King. The fact that we see status bias in baseball probably means this type of bias is pervasive in our culture. If a hiring manager has a slew of highly qualified candidates for an open position, for instance, she is likely to make a decision based on where a candidate studied or interned, or the reputation of his recommender. “People who have high status are going to get the benefit of the doubt in these really competitive, close calls in job hiring situations,” says King.
“There’s a strategic element to this as well,” Kim points out: a high-status individual can afford to “push the envelope a little bit” because, during times of uncertainty, they’re even more likely to get the benefit of the doubt than usual. A low-status individual, on the other hand, may feel obliged to take fewer risks. “It speaks to some of the constraints on lower-status people,” says Kim.
Because it is inevitable that status will bias our assessments, how we evaluate people needs to change, King argues. In baseball, this could eventually mean relying on computers to call balls and strikes. Elsewhere, it could involve taking a status-blind approach to decision making: not giving managers the option of seeing where someone went to school, perhaps, or relying solely on quantitative measures of human performance. “We need to find other ways to evaluate besides just having humans sit around and talk about it,” says King.
What is at stake is basic fairness. In order to be taken as seriously as their higher-status competitors, “people who are at the bottom of the hierarchy have to expend a lot more effort and a lot more of what meager resources they have” says King. Hall of Fame pitcher Lefty Gomez once said he would rather be lucky than good. But in order to get a fair shake, his unsung colleagues likely needed to be lucky and good—and then some.
Kim, Jerry and Brayden G. King. Forthcoming. Seeing Stars: Matthew Effects and Status Bias in Major League Baseball Umpiring. Management Science.
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