Thirty years ago today, give or take a month or two, Bill James’s 1987 Baseball Abstract came out, and I’d like to take a moment to appreciate what that book meant to me. I’d been well aware of Bill’s vast talents for quite a few years by that time (I’m a proud owner of one of Bill’s pre-Ballantine Abstracts, tattered and falling-apart as it and I both are at this point, and my ramblings about outfield conversions to 3B had even filled a few pages of the 1986 Abstract) but the 1987 book just about blew my mind apart, an explosion I want to pause to remember here.

I consider it far and away the best of the Abstracts, the best book Bill has ever written, and quite possibly my favorite baseball book of all time. In addition to covering the 1986 season (one of my all-time favorite years) thoroughly, this yellow-covered Abstract was the one that featured a revolutionary study of rookies throughout baseball history, which opened my eyes to the still-incredible observation that a 20-year-old rookie is far more likely than a 21-year old with the same exact stat line to become a star, as a 21-year-old rookie is likelier than a 22-year old, and so on. Up until this point, I had considered players’ ages to be a junk stat, far too many of which cluttered up my brain, taking up space that I needed badly for such functions as remembering the sequence of events needed to get out of bed in the morning and get dressed and fed.

That same study (it went on for forty-one pages) was also remarkable for the bravery required to publish its conclusion about race. In examining rookie seasons, Bill concluded that black rookies went on to have different career paths from their identical white counterparts, and that overwhelmingly their careers were not only different but better, often far better. In case after case, Bill provided evidence that pairs of rookies who differed only in the color of their skin showed vastly greater development for the darker-hued players. Henry Aaron’s stat line in his rookie year, for example, looked an awful lot like that of Gus Bell, but over the course of their careers Aaron outplayed Bell (as he did with everybody else who played the game, of course), and so did black rookie after black rookie. There were a few exceptions (44 out of 54 comparisons concluded that the black player went on to have a better career than the white one), and Bill tested his conclusions in every way imaginable to see if he had committed some sort of methodological error, but the conclusion held its ground.

This information was shocking, not only from a baseball point of view, but from a sociological perspective as well. Not setting out to comment at all about American society, Bill confronted a basic truth underlying our entire culture, one that flies in the face of those bigots clinging to the belief that black people are lazy, genetically underprivileged perpetual under-achievers. On the contrary, Bill’s study showed that a black person (more specifically, a black major leaguer) will be able to advance his own career far more capably than his closest white counterpart.

This conclusion came about, I will remind you, not because Bill set out to prove it, but because Bill studied the subject of rookies so systematically that the conclusion was inescapable. By including 666 rookies (and not once alluding to the diabolical connotation of that number), Bill was able to show that his every conclusion, including the racial one, was far from a flukish outcome of a few skewed stats.

Speaking of stats, the 1987 Abstract also displayed how statistics are invented, how they evolve, and how they are used.  In the 1980 Abstract, Bill had introduced the concept of the Value Approximation Method, which sums up players’ entire seasons (and ultimately careers) in two digits. The V.A.M. was ultimately abandoned, mainly I think because it didn’t actually measure anything. It was just a number between zero and seventeen that, as the name says, measures the approximate overall value of a baseball player’s season. Oddly, though it has been superseded by WAR, which does claim to measure something tangible (Wins), approximately, Bill doesn’t seem to care for WAR on the grounds of imprecision. Personally, I apply to WAR the same caveat that Bill applies to his own VAM:  it is the Value APPROXIMATION Method, not the Value Precision Method. "It isn’t necessary that we agree with it in every case," Bill wrote on p. 46, "that it never evaluates the players differently than we might evaluate them. It is necessary only that the system be reasonable, consistent and fair."   Its purpose is to approximate value on a gross but rational level—ranking one integer higher on the VAM is not a guarantee that a player is better, or had a better year, or anything really. But ranking five integers or ten integers higher gives that sort of guarantee, with some degree of reliability.

That’s how I think WAR should be used, not as a yardstick of superiority, but as a rough yet reliable measurement of quality.  Would I trade every single player with a WAR of 7.0 for a player with a WAR of 8.0? Not necessarily. But do I feel comfortable saying that a player with a WAR of 9.0 had a better year than a player whose WAR was 4.0? I am at complete and utter peace with that concept.  That is what the VAM does, and that’s what it was designed to do, to make broad general statements about groups of players’ seasons (or groups of a player’s seasons) that are more accurate the larger the groups of seasons are.

As far as a single season goes, sometimes people will understandably use these figures as tie-breakers, as in, "You think X had a better year than Y, I don’t, and we’ve keep going around and around on that, so I’m just going to go with ‘My guy had a higher WAR than yours.’" Next thing you know, you’re using it to settle every dispute under the night sky. That’s an error, but as I say an understandable error.

Eventually, Win Shares replaced (or Win Shares and Loss Shares is going to replace) the VAM, in a never-ending quest for precision and tangibility in approximating players’ values. Until Win Shares and Loss Shares are presented to us, WAR will have to do, performing the valuable function of allowing us to generalize about great groups of seasons in a meaningful way. Some analysts (including Bill) find WAR presumptuous or inaccurate or unreliable, but I maintain that WAR (and WS & LS, and obviously VAM) was not intended to be humble, pinpoint-accurate nor completely reliable in the first place, just a method of reducing a page full of numbers down to two digits, which it did well. The 1987 Abstract used VAM widely, and in large groups, where it made the most sense. It was an instructive shortcut, letting us think about pages full of numbers with maximum efficiency.

This efficiency proved mind-blowingly useful in the study of rookies, for example. Bill could say (and did say) that Henry Aaron had essentially the same value as a rookie that Gus Bell did, according to VAM, but a much larger VAM over the course of his career. He didn’t need to cite how often they got on base, or scored runs, or accumulated total bases, or a zillion other incremental integers that showed their abilities, just a couple of digits worth of VAM, permitting him to make his points in only 41 pages instead of the several hundred pages he would otherwise have needed to make the same points less convincingly.

VAM was a great statistic, now superseded by other broad measuring stats, which it inevitably led to. Bill’s other attempt at a synoptic stat was his Runs Created stat, which also, I think, led directly to WAR, once folks figured out how many runs it took to make a win. The appendix at the back of the 1987 Abstract also usefully defined these and the other tools Bill invented or refined up to that point: Brock2, Trade Value (which was a refinement of Approximate Value), and Speed Scores, which were fun. It let you quantify how fast players were, again settling a lot of dumb arguments and thoughts about who was faster than who, and how do you know when a player is losing speed or just having a bad year on the basepaths.

Sim Scores got introduced around here too (I’m not vouching for the actual first-use date, just noting that by 1987, Bill was referring to them), a stat that’s so common now I think people have forgotten where it came from or when. But as epochal as these advancements may be in baseball history, I was mostly charmed by Bill’s writing, which ranged from the eloquent to the profound. Thumbing through it, which I do every other year or two, so much seems fresh out of the oven: this was the Abstract where some of my favorite bits appear, the hilarious "Will the McMeeting Come to Order?" parody of a San Diego Padres board meeting, the close analyses of the 1978 and 1986 AL MVP races, with Guidry, Clemens, Mattingly and Rice having their candidacies considered and compared and rejected and promoted, objectively and coolly,  "The Greatest Outfields Ever" essay, "The Ken Phelps All-Star Team," the cruel but dead-on "Chuck Tanner’s Funeral Home"—this was back when Bill wrote mean, accurate critiques of players and managers, sometimes so mean and so accurate that I still gasp a little bit, even though I’ve read what’s coming two dozen times before.

But as much fun as Mean Bill was to read, it was Accurate Bill, Obsessive-About-Accuracy Bill, who made me think about this stuff like I’d never thought about it before.  He wrote a kind of preface, "Meaningful and Meaningless Statistics," that ranked stats on a very thorough grid, in three main categories (Category Importance, Reliability, and Intelligibility)  that considered  each stat’s virtues and vices, and ranked each one on a scale of 1-10, and then wrote a conclusion "Putting the Elements Together" that distinguished the wheat from the chaff.  ("ERA" was the most meaningful stat, followed by OBP, and at the bottom of the list was "Sacrifice Hits.") I was sorry to find Game-Winning RBIs ranked as low as it was, partly because the All-Time GW-RBI leader was one of my heroes, Keith Hernandez, but that was another important lesson Bill taught me: it’s not about players you like or dislike, Bub, it’s about what’s true and what’s accurate. If you want to rave about your faves, well, that’s a few doors down from here.