The loss column (drive or fly?)

On the Baseball Today podcast, Peter Pascarelli frequently presents a team's position in the standings only in terms of loss column differential--as in, "The Dodgers are only five back in the loss column, so don't count them out."

The use of the loss column alone is always strange. Unlike the sensible games behind formula every newspaper uses, the loss column stat ignores what we usually think of as the most fundamental stat in baseball: team wins. At this point in the season, there's no reason at all to speak of the standings in terms of the loss column only, as the absurdity of saying a 60-20 team is tied with an 18-20 team easily demonstrates. It matters if you've already won a game.

I assume that the whole loss column business got started as a way to describe pennant races at the very ends of seasons. If a team is 1.5 games behind but tied in the loss column, that team still controls its own destiny, as the saying goes, and we humans love that sense of control. (The famous fact that almost everybody fears flying more than the much more dangerous activity of driving derives from the same illusion of control.)

Therefore, it makes sense that measuring races by the loss column at the end of the year became routine back when teams had to be good to compete for the playoffs. The grain of truth in the loss column idea would lie in the fact that really good teams are likely to win any given game, so if the Yankees are three back of the Red Sox with five to play, the loss column standings could have a real effect on the probability of a comeback. The closer the two teams' winning percentages are to 1.000, the more the loss column matters. The less glorious divisional races of the twentieth-century, in which the Cardinals could realistically make the playoffs with a losing record, make the conventional standings a much better measure of a race.

The Optical Revolution in Baseball Analysis

This Slate article, brought to my notice by John Smick, has given me a sense of what I have missed by moving to the periphery of baseball analysis over the last five years or so. When I slipped from analytical wakefulness into a fog of half-awareness, my fellow contributors on the once-proud rec.sport.baseball Usenet group had followed the lead of Bill James and worked out the basics of modern statheadedness: adjusting statistics for park, league and era; understanding the value of adjusted minor league numbers; separating players' performance from their teammates' influence; and so forth. Some of the r.s.bb writers would go on to create the Baseball Prospectus and other publications. After Moneyball popularized our long-held belief that baseball's conventional wisdom rested on flawed assumptions, a few of them even worked their way into jobs with major league teams.

We knew back then that we didn't understand how to evaluate fielding very well. Whereas pitching and hitting were largely individual efforts, the team effects of fielding make judging fielders like judging football or basketball players, whose performance always depends on the actions of other players. But I thought I had a sense of where the breakthrough would lie: the statistics needed to be based on technological observations. With cameras or lasers or something (I'm, um, not an engineer), we could know exactly how players react to batted balls--how fast the players break, how fast and accurately they track the balls, how often they catch balls when they reach them. Given the amount of money floating around baseball, I wondered why some team hadn't already introduced this technology in a proprietary way.

At the end of the Slate article, author Nate DiMeo hints at "next year's rumored Gameday innovation--video cameras that cover the playing field. These cameras promise to yield important insights about the art and science of fielding." Apparently, the dream becomes reality next year, but wonderfully, the data will be public, not the jealously guarded property of certain teams, as I had imagined.

The other factor I hadn't imagined lies in the main point of DiMeo's piece: the whole-field cameras follow the introduction of similar cameras that analyze pitching. In the combination and extension of these developments lies the root of a real revolution in sports analysis, one that I predict will ultimately mean more than and largely replace the Jamesian statistical revolution.

This is the optical revolution.

The Jamesian revolution largely involved the proper adjustment of individual performance for context. Often the conventional wisdom had undervalued context: we needed to adjust statistics for park and league and era to get past the idea that a homer is a homer is a homer. Sometimes we needed to value context less: the Jamesian revolution led us to see a less fundamental difference between major and minor league numbers and to regard RBIs as essentially a measure of slugging percentage muddied by context.

While the Jamesian revolution generally refined the analysis of existing statistical observations, the optical revolution will change the means of observation and the nature of the observed. The result of the optical revolution will be the separation of performance and results; we will shift from analyzing the statistical record of games to analyzing players' performance in a hypothetical, parallel world.

In this parallel world, we will attempt to build links between players' actions and results. The optical revolution will attempt to imagine a world of baseball without chance.

We already see hints of this development in pitching statistics that have grown out of Voros McCracken's thesis that Major League pitchers have control over walks, strikeouts, and home runs, while chance dictates the results of other batted balls. McCracken and others have used that insight to measure assign to pitchers hypothetical ERAs, adjusted for luck and team defense--these statistics attempt to measure what should have happened rather than what did. This process goes beyond norming the stats for context; it involves evaluation that deliberately excludes results. These numbers, for example, that Matt Morris's relatively effective pitching for the Giants during the first half of this season was largely the result of random variation. (More of his batted balls than usual found their way to fielders' gloves.) The Giants probably capitalized on that knowledge when they unloaded Morris into that repository of all other teams' failed projects and miscalculations, the roster of the Pirates.

The optical revolution will extend this line of thinking much farther. We have always known that some balls are called strikes and vice versa; now we know which ones, and we will soon be able to adjust for those mistakes. We will be able to say how much of an excellent pitching performance arose from the pitcher, how much from defense, how much from the opposition, and how much from luck. We will be able to say how much setting up an outside curveball with an inside fastball changes the effectiveness of the curve. If a great hitter has a lousy playoff series, we will be able to say whether he simply faced great pitching or whether he failed to hit pitches he normally smokes. This last example illustrates the transformation of the Jamesian revolution: the Jamesians cast doubt on the notion of the clutch hitter by looking at aggregate statistics, but the optical revolution will enable us to see exactly how performance changes (or remains constant) as the season becomes the postseason.

The Jamesian revolution asked us to take our eyes off the ball and look at the numbers. The optical revolution will use technological eyes to follow the ball in unimagined ways.

Fire Joe Morgan on Fire

Here is a column I wish I'd written on A-Rod. Hat tip: David Archer.

The knee of the Tiger

Update, July 2008: I suspect that this post does not describe Tiger's now-famous knee injury, but I want nonetheless to acknowledge that yes, I realize how dumb it sounds now. So noted.

During Tiger Woods's victorious final round at the PGA championship on Sunday, Woods stumbled awkwardly as he pumped his fist after holing a birdie putt on the eighth hole. I was watching the round with two friends, and none of us saw anything of concern in the stumble, but the CBS announcers immediately speculated that Tiger had incurred a knee injury. (Come to think of it, they may have said ankle first, but they soon settled on knee.) For many holes afterwards, they relentlessly attributed every bump in Tiger's road to victory to his allegedly hurt knee, in spite of no limps or grimaces to bear out the theory. When Woods clinched the victory with spectacularly huge swings, the knee narrative disappeared. I found this to be an unusually clear demonstration of selection bias, and one that illustrated more general problems with sports journalism: the announcers had more incentive to set up a dramatic narrative than to evaluate the evidence in front of them. With the narrative established, they supported it at every opportunity and then wordlessly abandoned it as it proved to be nonsense.

The Sports Guy on the Donaghy scandal

I've been meaning to say more about what makes Bill Simmons a terrific sportswriter, one I'm almost always eager to read, even though his analytical instincts drive me nuts. This column on the NBA refereeing scandal is Simmons at his best. This is a sports story that is all about fan psychology--the way everybody will talk about games next year, and nobody covers that angle better than Simmons.

How about the Sports Guy Race Theorists?

Back in March, Bill Simmons got himself in a little hot water by saying that this was an "astounding realit[y]" of the 2005-06 college basketball season: "Two white guys (Adam Morrison and J.J. Redick) were indisputably the two best college basketball players alive."

Perhaps Simmons thought that Boston sports fans have such a longstanding record of interracial harmony and good cheer that nobody would notice that you can't explain the logic underneath that statement without cringing. Hey, I've got a minute. Go ahead and explain to yourself why the joke is funny. I guarantee at least two cringes, or a cringe and a wince.

When readers called Simmons on the comment, he thoughtfully offered this olive branch: "For anyone who was offended, I'm sorry … not for the joke, but for the bug up your ass." Yes, it takes a lot of courage and integrity to go for the old "bug up your ass" line. Not to mention writing skill.

Bill Simmons is a skilled writer and often a skilled thinker, too, but his head seems to shrink when he tries to joke about race. Here is his reason number 929 why he loves sports:


The Utah Jazz
I will never get used to this: One of our most white-bread American cities roots for an NBA franchise named for a musical movement created by African-Americans. It's genuinely insane. You can brainstorm with your buddies all weekend to come up with a name for a sports franchise that makes less sense -- there's no way you're topping Utah Jazz. Not even with Dallas Indians.

Let's leave aside the lack of originality here--seriously, has anybody not heard this before?--and go to the hysteria of Simmons's resistance to the idea of jazz in Utah. Obviously, Utah Jazz an odd name, with the oddity stemming from the team's move from New Orleans to Salt Lake City. Probably nobody would have considered giving the name to a new franchise. But "genuinely insane"? There's no topping it, even with hypothetical names?

I find Simmons's adolescent excitement about an old joke revealing. Utah Jazz is an oxymoron only in the dull-witted logic of bad jokes, in which all Utahans are Mormons, all Mormons are white, and no white people play jazz. The fact that lots of people have played and do play jazz in Utah is a side point, though, compared to the revelation that in Simmons's imagination, a loose association between a broad style of music and a racial group has more force than anything else he can imagine. So I take up the challenge to think of team names nuttier than Utah Jazz. Simmons offers us a weekend, but I'll take five minutes:

Laramie Surf
Minneapolis Camels
Havana Barons
Miami Frost
New York Humility
Hartford Rebels
Cedar Rapids Mountaineers

It's not so hard--if you think about it.

Inauspicious: Pascarelli on Polanco

Last year and this, I have listened regularly to ESPN's Baseball Today podcast, hosted until this week by Alan Schwarz. I have enjoyed the podcast in part because Schwarz and his guests (especially Rob Neyer and Steve Phillips) did a good job of combining responsible statistical analysis with current news and anecdotes.

Schwarz has now departed to work for the New York Times, and Peter Pascarelli has taken over the hosting duties. Yesterday, an email asked him to discuss the best second basemen in the American league. After entertaining a couple of other possibilities, Pascarelli brought up his own choice. He began,

My favorite second baseman, though, in the American League is Placido Polanco, who I think is one of the most underrated players in baseball.

This surprised me: I've long thought of Polanco as an overrated player, a useful guy talked about as a star because he's versatile and makes contact well. But I haven't followed the story for a while, so I waited for more details. Pascarelli continued,


And those of you who like stats might be interested to know ...

At this point I literally stopped in my tracks and waited, suspecting that I was about to hear a customized statistic designed to carve out a little slice of Polanco's performance that makes him look especially good. Sure enough:


... that since 2005, Placido Polanco has the best average with runners in scoring position of any player in baseball, and that is something which I bet a lot of you didn't know.

Well, I certainly hope most people didn't know that. It's a misleading fact in three ways: 1) it's about batting average, a stat whose limitations favor Polanco; 2) it relies on one measure of clutch hitting--clutch hitting is an idea enormously susceptible to distortions and small-sample variations, and people who pick one measure are almost always doing so to slant their evidence; and 3) it arbitrarily chooses 2005 to the present as its time frame.

In fact, if you look at different time periods and a different measure of clutch hitting, Polanco will look much worse; he has stunk with men on and two out, for example.

My point is not to knock Polanco, who is a very good player. My point is to knock Pascarelli, who (like Bill Simmons, to relate this to my blog title) seems to confuse statistical expertise with the recitation of isolated and slanted numbers--which is pretty nearly the opposite of statistical expertise. Pascarelli closed his comment thus:

All of you who think of yourselves as experts, well, take a back seat to me, pal, I knew that number and you didn't.

He sounded like he was kidding. Sort of. I fear we've lost an excellent podcast.