Joe MorganWho is Joe Morgan and why are these people so eager to have him fired? These days Joe is an avuncular chap who dresses like he owns a small chain of successful used car dealerships. Back in the late 70s, when I first started watching baseball, Joe was coming to the end of a glorious career playing second base. He then moved from the field to the commentary booth, where he resides comfortably to this day (and can be encountered by UK audiences deep in the night on Five). And from where the Fire Joe Morgan folk would like him evicted post-haste.

Is Joe that bad? I have no problem with him. I’ve heard an awful lot of sports punditry on an awful lot of sports in my time (bullfighting on the radio: now there’s a real test of broadcasting skill), and Joe is a considerably long way from the worst I have come across. In a world where Andy Townsend and Alan Shearer are generously paid to offer their opinions, Joe’s employment is no scandal.

Fire Joe Morgan make a good case, though, applying the scalpel of close analysis not only to Joe’s broadcasting work, but his writing for ESPN.com. The writing, I’ll admit, often falls apart under detailed inspection. The FJM writers also do a fine job of criticising and satirising the whole range of baseball pundits. They’re funny, they’re knowledgeable and some of them write well. And yet, they can also be rather creepy, because the FJMers appear to be dogmatists. Their underlying gripe against Morgan is that he refuses to agree that statistics offer the only sensible way of analysing baseball or running a baseball team.

Now, baseball has always been a stats-obsessed game: players have always been judged on their numbers, manager’s strategy has depended on them, American kids have probably grown up better at maths (or math, indeed) because they are brought up working out batting averages. But over recent years, there has been a massive escalation of the importance of numbers in the game, not to mention an extraordinary proliferation of statistics. Once upon a time, batters were judged mostly on batting average, runs batted in and home runs; pitchers on wins and losses (actually more arcane than you might think) and the relatively easy-to-explain earned run average. These have been joined in short order by OPS and ERA+ and WHIP and the frankly bonkers VORP (value over replacement player), which the stats geeks just love, and many more These are part of never-ending quest for the ultimate stat, the one that will explain a player’s worth beyond dispute.

It all started with a guy called Bill James, who from the 1970s attacked baseball conventional wisdom with detailed statistical analysis, a system eventually known as sabermetrics*. But it came of age in the late 1990s when Billy Beane, the general manager of the Oakland As, started using sabermetrics to run his club, as described in the bestselling book Moneyball]. Although Beane himself had been a (not very good) professional ballplayer, his disciples, who soon fanned out across the game, were a wave of Harvard and Yale grads who loved the numbers. And out in fandom, this was a magical time. For all those kids who loved the game, but had never been that big or strong or quick, who knew from the age of seven that they were never going to be pro athletes, the tide had turned. In the new dispensation, managers, the old lags who had played the game and looked after training and chewed tobacco making decisions during the game, were now deemed near irrelevant. The new kings of baseball were the GMs, suited and office-bound but running actual major league teams as if this was fantasy baseball. Twentysomething Ivy League brats like Theo Epstein of the Boston Red Sox and Paul DePodesta of the LA Dodgers had supposedly foregone making fortunes with hedge funds to shuffle squads of millionaire ballplayers, forever looking for the undervalued gem on an opponent’s playing staff. While in earlier times baseball stat madness had been focussed during games (should you bring in a lefthanded pitcher just to face a lefthanded batter because the percentages call for it?), now it seemed that all the work was done in the assembling of the squad. Few people grow up with a realistic dream of hitting a home run to win the World Series, many could imagine being a GM.

From this side of the Atlantic, it can all seem a little strange. Although the papers run OPTA data and coaches like Steve McClaren and Arsene Wenger are apparently forever checking diagrams on their laptops, football punditry in Britain is still ruled by calls for passion, Churchill and ‘Cry ‘God for Harry, England, and Saint George!’. Stranger still, perhaps, is the comparison between baseball and cricket. Cricket, after all, is a game that is pure numbers. On Test Match Special, they have a numbers bloke in the commentary booth, although he’s only allowed to speak when spoken to. Players are constantly ranked in terms of their figures. And cricket does something that I don’t think baseball stat freaks could possibly dream of: it officially decides who wins and loses rain-shortened one-day games on the basis of mathematical predictions of which team would have won.

Yet there is no peer pressure on the casual fan to understand the Duckworth-Lewis method. If basic bowling and batting averages are easy to grasp, then the long-established LG ICC Player Rankings, which assess player performance in relation to where the game was played, against who, under what conditions etc, are widely accepted without anyone suggesting that Geoffrey Boycott should be sacked if he can’t explain exactly how the algorithm that determines them works. But that is exactly what the Fire Joe Morgan people demand: for middle-aged ex-sportsmen to chat about maths with the assurance of seasoned economists, or else to step aside and leave discussion of the game to people who can do nonlinear regression in their sleep. Do they really think that would make for good TV or radio? (Mind you, in the digital age, this could and maybe should be an alternative: choose between analysis from some old-time pro or two representatives of Stanford’s TMSCSCS project.

I have no massive fear of stats. I was a big fan of Gavyn Davies’s Guardian numbers column. When it comes to issues of public health, housing and crime, evidence normally trumps hunches, although it is always worth remembering that it is easy, without twisting the figures, to show that the US is both the most and least generous country when it comes to providing foreign aid.

But a sport that could be worked out in advance – as if it were no more than Top Trumps – would be no fun at all. Here are some of things that the most dedicated baseball stats heads don’t believe exist: momentum, team spirit, the impact of stirring speeches, players who rise to the occasion in crucial situations. This approach is disturbingly deterministic. An episode of hokey math-thriller Numb3rs, oddly enough, suggested a connection between an unhealthy love of baseball stats and fascism, which is clearly taking things too far. But if I thought their hearts or heads could be swayed at all, I’d recommend that the FJM team watch Adam Curtis’s Pandora Box, about how assorted attempts to apply science to politics came a cropper.

Even Billy Beane, the original stats-friendly baseball general manager, admits there’s a limit to the power of stats. His (relatively) low-budget Oakland As have been very successful during the regular season. Beane, however, described the knockout play-off rounds that determine baseball’s champions as “a crapshoot”, and the Beane As have yet to make it to a World Series. Theo Epstein’s Red Sox did win it all, in 2004, but along the way they had discarded some of Bill James’s more radical theories, and no baseball team in recent memory has put more faith in the idea of team spirit. The numbers can tell you some of the story, but never the whole story. And Joe Morgan? He seems fairly secure in his well-paid job, so I guess he doesn’t need me to worry about him after all.

*(Bill James’ method foreshadowed the fashionable Freakonomics, although inevitably the two movements clash over who really understands the stats).