Whenever people find out I’m a baseball writer, they want to know two things: how their team is going to do this year, and whether Player X is on steroids. (“Badly” and “yes,” respectively.) A great deal of the time, they want to know a third thing, which is how to make heads or tails of the statistical revolution that’s reshaped baseball over the last few years. I’ve had doctors, lawyers, novelists, investigative reporters, and stockbrokers shyly confess that it seems like there’s a great deal to it, but that it’s just too complicated for them.

Ridiculous as this may seem, there’s a simple explanation: People don’t understand baseball’s statistical revolution because there’s no such thing. What there has been is a management revolution, based only partly on new statistical research. Understanding the difference is the key to understanding what’s going on in baseball right now.

This may seem like a matter of semantics, but it’s a real distinction. Statistics, in and of themselves, are utterly meaningless trivia; what makes them important is the way they’re used. Gruff, old-school managers like the St. Louis Cardinals’ Tony LaRussa will talk themselves blue about how numbers never won a ballgame, then foolishly start a weak hitter because he’s had four hits in six lifetime at-bats against that night’s pitcher. On the opposite end of the credibility and influence scale, a clueless Cardinals fan will look at a minor-league player’s on-base percentage without any understanding of its context, then wail that the player is stuck in the minors and that men like Mr. LaRussa, who have spent their entire lives studying baseball, don’t know what they’re doing. Combine that with the kinds of useless numbers announcers use to fill dead air time – “David Wright hit .363 on the road on Tuesdays the day after it rained last year” – and it’s no wonder so many fans throw up their hands in despair.

When you think of all this in the context of baseball’s management revolution, everything makes a good deal more sense. The basic premise behind the way perennially successful teams like the Oakland Athletics and Boston Red Sox operate is that baseball is like any other market – to operate within it, you have to be able to systematically value assets and their relative worth going forward. Statistics – and the infamous spreadsheets and computers associated with them – are just tools that make it easier to organize information and draw conclusions. When you explain this to a lawyer with millions tied up in investments, the bewildering acronyms that seem to have taken over baseball make infinitely more sense.

Which brings us back to the original question: how to understand this sea change in baseball, whatever you want to call it? One way is to read two new books from Baseball Prospectus. The first is the 2006 edition of their annual (Basic Books, 454 pages, $24.95), and the second is “Baseball Between the Numbers” (Workman Publishing, 554 pages, $18.95), a collection of essays that purports, according to its subtitle, to prove “Why Everything You Know About the Game Is Wrong.” (Disclosure: I count several of the Prospectus writers as friends and colleagues.)

The annual is required reading for serious baseball fans. Every team gets its own essay, along with analysis of every significant player in its system, and there are several major essays on topics ranging from baseball’s offfield business to the utility of “datadriven management” in front offices (the English language has taken casualties in this revolution, though the essay is excellent).

The core of the book is statistical analysis; every player’s numbers are presented with the noise stripped out of them, so that rookie ball players can be compared to major leaguers and so on.The basic trick here is to establish a theoretical neutral context and see how each player would affect it. The Prospectus writers have also introduced a number of context-sensitive statistics based on play-by-play data, and some of the conclusions are quite surprising.

What’s interesting here is that the more sophisticated the numberscrunching gets, the more it accords with old-school baseball wisdom. To take one example, Prospectus’s projection system – which compares players with similar numbers and of similar sizes to come up with a range of possible outcomes – likes Mets shortstop Jose Reyes for the same reasons scouts do: He’s very young and athletic, has good power, and doesn’t strike out much. The computer thinks he has about a 50% shot of being an MVP candidate by the time he’s 26. A few years ago, Prospectus would have written him off because of his poor on-base percentage (and a number of this book’s writers still indulge in this kind of superficial analysis, and do so quite smugly); now, they’re able to arrive at a more nuanced appraisal of his strengths and weaknesses.

Indeed, it has become clear that many of the analytical crowd’s old dogmas – that the playoffs are mostly about luck, that strikeouts don’t matter, that there’s no such thing as a clutch hitter, that closers are overrated and interchangeable, etc. – don’t hold water. The best essays in “Baseball Between the Numbers” instead present detailed and compelling cases for why the traditional dogmas of baseball hold, just not as well as you might think. A massive analysis of play-by-play data confirms, for instance, that there is such a thing as a clutch hitter. You don’t need a computer to tell you that, but you probably would need one to discover that the best clutch hitter of the last 30 years was Matt Lawton.

An attentive,open-minded reading of the new Prospectus material will result in a certain amount of eye-glazing, just as reading a similar book about stockpicking would. But it will also reveal some fascinating things about the game to anyone from Mr. LaRussa to the guy who despises Mets manager Willie Randolph for batting Mr. Reyes leadoff and owns www.firewillie.com to the lawyer who thinks both of them are nuts.

Mr. Marchman’s baseball columns appear regularly in The New York Sun.