SO, I’M HANGING OUT with my 3-year-old niece the other afternoon, you know, just drinking Stellas (Lights, don’t be judgmental), thinking about my last two divorces, why Scott Howson has a full-time job and I don’t, and wondering if anyone would buy the film rights to my book of poetry so that I could pay off my substantial student loan debt or perhaps buy a fresh pack of Belmonts, and she says to me “Uncle Michael, you have no children because you are alone.” At first, I thought it was the Belgian ale talking, and that her comments were ill-informed and mean-spirited. But, you know, she’s three and her tolerance is embarrassingly low, and the more I thought about it, the more I realized that her declaration was born of both caring and ingenuity. She was reducing my existence to a very basic equation: (1 Uncle Michael) x (0 partner) = 0 children. At three, she was quantifying her uncle for the purposes of evaluating his position in life. She was, perhaps unknowingly, developing the philosophy of sabermetrics of love.

Sabermetrics is the “specialized analysis of baseball through objective, empirical evidence, specifically baseball statistics that measure in-game activity.”[i]

So with all that romanticism out of work, why not borrow it? Why not plug sabermetrics into the less quantifiable pastime of love? My niece, two sippy cups of Stella in, started the process, but since she naps often, is asleep by 7:11, and easily distracted, I thought I’d attempt to finish it.  First, let’s replace Bill James with Henry James. Makes sense, right? James was a realist, favoured celebrating the banal over stylized romanticism, and appreciated a good narrative, and what is baseball but an unending narrative? And what’s more banal than statistical analysis?

But the substitution of James for James is intriguing on many levels. Of knowledge, the exploitation of which fuels sabermetrics, Bill James wrote:

“There will always be people who are ahead of the curve, and people who are behind the curve. But knowledge moves the curve.”

Henry James had similar thoughts on knowledge:

“It isn’t knowledge, it’s ignorance that–as we’ve been beautifully told—is bliss.”

And what leads best to loneliness, but ignorance? Henry James enjoyed juxtaposing elements of the old world with those of the new, and what is sabermetrics but that exactly? My niece was on to something. Perhaps she could be the next Royals GM.

Once we’ve exchanged the James’, we’re forced to confront the acronyms—the seemingly endless list of statistics that excite the sabermetrics faithful. Where once baseball was about the digits of acronyms of yore—RBIs, HRs, and AVGs—love was about acquiring seven digits, getting past third base, and occasionally doubling up. But no more. Love, like baseball has become more complicated. The sheer number of forums in which you can meet another person is seemingly infinite. From Facebook to Twitter to Lavalife to J-Date to Second Life to speed dating to Tequila Tuesdays. Whatever happened to just going to the bar, getting drunk, lying, and letting the rest sort itself out? Well, the same thing that happened to greenies, the Triple Crown, and chewing tobacco, I suppose.

So, let us consider a few of sabermetrics’ most prominent statistics, and how they relate to relationships, and attempt to develop a working yet fluid philosophy of sabermetric relationships. Let’s see if we can’t build a winner. Let’s consider five stats borrowed from sabermetrics and try and get us some.

1. Wins Above Replacement (WAR) is a statistic that’s used to show how many more wins a player would give a team versus a replacement, be it a minor leaguer or bench. While WAR values are scaled equally for all players, the result is calculated differently for pitchers versus position players: position players are evaluated using stats for fielding and hitting, while pitchers are evaluated using stats related to the opposing batters’ hits, walks and strikeouts.

Basically, this is the baseball equivalent of measuring a prospective partner against his contemporaries. Let’s say you’re a single young woman, and you’re at a respectable bar with some friends for an evening of cocktails and frivolity. Sitting across from you is a table of like-minded young men, out for similar cocktails and hopes of frivolity. As a young woman, you’re immediately judging that table, calculating each individual at the table’s value in comparison to all the others. The table is the bench. The stats are simple at the evening’s beginning, generally based on aesthetic. As the evening progresses, as the night gets into the later innings, the stats change. Because WAR is non-standardized, on any given evening we can consider stats such as Drink Consumption, Conversational Acumen, Ability to Stand Up, and Tab Payment Quotient.  Depending on what point in the season we’re playing, and how deep our bench is, different considerations come into play within the umbrella of WAR. Most people strike out, some walk home, and some are fortunate enough to work the counts deep, score a few runs, and make it into extra innings. Okay, the metaphor is corny there and a bit weak, but remember this was the idea of a half-cut 3 year old. Work with me.

2. Walks + Hits ÷ Innings Pitched (WHIP) is perhaps one of the oldest sabermetrics stats. I remember being a kid and entering my first fantasy baseball league, and league commissioner Danny Cappe (twelve and over his head) was outlining the stats that would dictate the winner. I understood everything until he go to WHIP. WHIP? That’s not on the back of my Topps Charlie Lea card. But I played it cool, because all the other kids seemed to know what was going down. But it’s a good stat, because it takes into account the walk, the base-on-balls, the BB. In baseball, all bad innings begin with a walk.

In life and love, a walk is the result of bad innings. As WHIP relates to the sabermetrics of love, the calculation is quite simple, and similarly humbling. If you consider walks to be breakups (a failure not unlike the free pass to first), and hits to be divorces (basically a walk with lawyers, or the possibility of extra bases), with innings pitched a standard duration of time, lets say a year, the calculation relates to quite well. The 2012 MLB leader in WHIP was the San Francisco Giants’ Matt Cain with an amazing 0.95. As a comparison, consider my 2006. In a year marred by excessive drinking and the popularity of my burgeoning poetry career, I successfully managed two breakups and a divorce. My WHIP would’ve been 3.00, which would’ve, had I been a major league pitcher, had me demoted back to A ball to work on my delivery. Which, in my case, I kind of did, except I went to Russia for 6 weeks and drank vodka until being alone was tolerable. Matt Cain I am not.

3. Batting Average on Balls in Play (BABIP) measures the number of balls in play go that for hits, excluding homeruns. There’s a good ball joke in here somewhere, but I’m above scatological humour. About 30% of all balls hit in play go for hits, and BABIP is a good measurement of a batter’s ability to connect for purpose. You can see where we’re going here. In the sabermetrics of love BABIP is essentially “getting some”.

According to Fangraphs “there are three main variables that can affect BABIP rates”[ii] for a hitter: defense, luck, and changes in talent. In terms of defence, you can be an attractive, affable sort with a good job and a full head of hair and some dude (or dudette) who is more attractive, more affable, has a job that is outside of the realm of poetry, does not live with his sister, has more than two pairs of shoes and/or pants, doesn’t call his ex-girlfriend at 4 in the morning on the 11th of every month, and does not wear a six year old ratty toque as a hair substitute, and has a great first step comes along and now your triple down the left field line has become a simple 6-3 out.

Luck is luck, and changes in talent is getting old and being unable to hold your liquor like you could in your twenties.

4. Win Expectancy is just what it sounds like. Expectation of success. According to David Appelman it is “the percent chance a particular team will win based on the score, inning, outs, runners on base, and the run environment.”[iii] Seems simple enough. I can’t be bothered to look up leaders in Win Expectancy, but let’s just say that the Royals have a 0.07 and the Yankees are a 342.6.

In the sabermetrics of love, Win Expectancy is about the rooms you walk into, the bars you frequent, the company you keep, the liquor you prefer, the conversations you maintain, and the point in your life you find yourself in. Win Expectancy, perhaps, becomes more important as you get older, but harder to excel in. Win Expectancy considers the veteran in the twilight of his or her career, coming to the plate in the bottom of the ninth with two out, runners on second and third, and the rest of your life at stake. Do you have one last hit left? Can you Jake Taylor[iv] one towards the third baseman? And do those around you, your teammates, have what it takes to anticipate what happens next? Do they have your back?

5. NERD (Narration, Exposition, Reflection, Description) is the kind of sabermetric stat that a mediocre writer who has experienced marginal success yet has a strong appreciation and understanding of the craft can really get on board with. NERD considers the intangibles, or at least attempts to. Is there a rookie playing? Can you truly be happy living in Kansas City? Does the player like his team’s new uniforms? Did the middle infield get drunk at an Applebee’s last night? Is there a girl sitting on the third baseline who looks exactly like the shortstop’s ex-wife?

NERD is essentially a first-year creative writing class. It is, by even the most ardent supporters of sabermetrics, a flawed stat. But, if you’re like me, you love a good flaw. NERD ignores looks, talent, charm, employability, number of fingers, hairline, success, shoe size, broadness of shoulders, choice of deodorant, style, and stamina, in favour of luck. In favour of chance. In favour of all that is not measurable, the right place at the right time with the right people. Like August of 2005. Or March of 2010. It is a statistic that attempts to measure the absence of statistical analysis. It is a sabermetric stat that ignores all sabermetrics. It’s meta, dude. It’s the Mets, dude.

What I love about baseball, what those of us who truly revere the game love about it, is the history of statistics, the way we can look back to 1982 and compare Gorman Thomas’ ability to get on base with two outs in the 7th inning of a matinee with how Carlos Gomez fared in the same situation last weekend. When we try to consider our own lives, our failures, our successes, it’s certainly more difficult to quantify. It’s impossible to quantify really. The sabermetrics of love is a start. More research is needed. I will need worshippers of the church, parishioners of quantifiable love. In the meantime, I’ll have to settle for teaching my niece how to fetch a Corona from the fridge, how to slice the perfect sized lime, and how to get back to Uncle Michael without spilling. The rest of life will just fall into place, like a bloop to right centre, finding the fissure between the second baseman and the right fielder. A perfect placement. A perfect, romantic moment. Last night, as a half a beet made it back to me from the kitchen, my niece sat next to me and in her infinite wisdom declared: “Uncle Michael’s job is watching baseball.” Damn right it is.

A version of this essay appeared in November 2011 on mikespry.org.