The subject of Christopher Phillips’s “Scouting and Scoring: How We Know What We Know About Baseball” (Princeton) is baseball, but it’s worth reading for more than just the baseball. The book is an effort to help us understand one of the oldest problems in modern societies, which is how to evaluate human beings. Do we scout or do we score?

The “scouting” in Phillips’s title refers to the traditional baseball scout. He’s the guy who sizes up the young prospect playing high-school or college ball, gets to know him away from the diamond, and draws on many years of experience hanging out with professional ballplayers to decide what the chances are that this one will make it to the bigs—and therefore what his price point should be for the club that signs him.

The “scorer” is what’s known in baseball as a sabermetrician. (And they don’t call it scoring; they call it “data capture.”) He’s the guy who punches numbers into a laptop to calculate a player’s score in multivariable categories like WAR (wins above replacement), FIP (fielding independent pitching), WHIP (walks plus hits per inning pitched), wOBA (weighted on-base average), and O.P.S. (on-base percentage plus slugging). Quantifying a player’s production in this way allows him to be compared numerically with other available players and assigned a dollar value.

The scout thinks that you have to see a player to know if he has what it takes; the scorer thinks that observation is a distraction, that all you need are the stats. The scout judges: he wants to know what a person is like. The scorer measures: he adds up what a person has done. Both methods, scouting and scoring, propose themselves as a sound basis for making a bet, which is what major-league baseball clubs are doing when they sign a prospect. Which method is more trustworthy?

The question is worth contemplating, because we’re confronted with it fairly regularly in life. Which applicant do we admit to our college? Which comrade do we invite to join our revolutionary cell? Whom do we hire to clean up our yard or do our taxes? Do we go with our intuition (“He just looks like an accountant”)? Or are we more comfortable with a number (“She gets four and a half stars on Yelp”)?

Many readers will already be familiar with the scout-versus-scorer dilemma in baseball from Michael Lewis’s best-selling “Moneyball,” which was published in 2003 and made into a movie, starring Brad Pitt. “Moneyball” is the story of how a baseball team that did not have a lot of money to spend on players, the Oakland A’s, deployed a new way of evaluating talent and proceeded, for several years, to compete with teams that had much bigger stars and much higher payrolls, like the New York Yankees. It was a way for small-market teams to keep up with their richer big-city rivals.

Lewis colorized his story a bit by casting the scouts as a bunch of Don Zimmer-y old-timers who spit tobacco juice and say things like “I can see this guy in somebody’s pen throwing aspirin tablets someday” (meaning he throws hard) and “This kid wears a large pair of underwear” (meaning his body is wrong for baseball). The scouts put a lot of stock in whether a player has “the good face”—a time-honored term of the scouting art. Lewis writes, “The old scouts are like a Greek chorus; it is their job to underscore the eternal themes of baseball.”

Lewis’s “scorers” are geeky Harvard grads who speak stats-talk and who actively disidentify with the culture of the game. Their whole approach is based on disdaining the wisdom of the scouts. They don’t need to see prospects, they don’t even need to see games, because, for them, a player is not a body; he’s a row of numbers. As it must be for all industry disrupters, the scorers’ advice has to be the opposite of the scouts’: if it was identical, their services would not be needed. As Lewis puts it, “The new outsider’s view of baseball was all about exposing the illusions created by the insiders on the field.”

Between the scouts and the scorers in “Moneyball” is the general manager of the A’s, Billy Beane, a former hot prospect who fizzled out in the major leagues, and therefore knows the world of the scouts, but who, from a kind of manic desperation, puts his faith in the geeks and is rewarded for it by the sporting gods. Lewis is a journalist; he’s trying to tell a story. But his sympathies are with the scorers. Phillips is an academic. His field is the history of science, and he is not telling a story. He is making an argument based on scholarship. And “Scouting and Scoring” is basically presented as an answer to “Moneyball.”

People-measuring arose with the modern nation-state—the word “statistics” comes from the word for “state.” In the beginning, the data that states collected were demographic: population size, birth and death rates, marriage, disease. In the early nineteenth century, statistical methods started being applied to human beings, and were used to determine, for example, the chest size of the average Scot.

Statistics were also used to make predictions. How many suicides would there be in France next year? How many homicides? How many homicides involving the use of poison? It turned out that there were regularities in all these categories. There was a kind of natural law governing the rate of murder by poison.

Debate ensued about whether the state could reduce the average annual number of these murders by, say, restricting access to poison. The statistician’s—the scorer’s—answer was that poison doesn’t kill people; people kill people. Homicides are going to occur at a certain rate per unit of population no matter what the laws are. We’re having the same debate today.

More scandalously, statisticians also began to correlate one measurement with other measurements to determine things like, for example, the relation between the marriage rate and the price of corn. Many people found this sort of thing deterministic and upsetting. Why? Again, it was a case of scouts versus scorers. Scout types refused to believe that people decide to marry in accordance with some statistical law. Marriage is about feelings, not the price of goods. Scorer types argued that, whatever unique sentiments might motivate the partners to marry in any specific case, the numbers do not lie. The fact is that when corn is cheap more people will get married. It’s a prediction you can take to the bank.

It is during this period of statistics mania, the mid-nineteenth century, that baseball, basketball, tennis, football, rugby, soccer, and other forms of organized athletic competition come into prominence, and we start to get leagues and championships and standardized rules of play. It is also when we start to get widespread scoring in sports. As both Phillips and Lewis point out, baseball scoring begins almost as soon as there is baseball. The first known box scores, breaking down the stats of games, appear in 1845; by the eighteen-sixties, Phillips says, “nearly everyone in baseball was counting in one form or another.”