Analyzing Analytics

Yesterday ESPN published kind of an interesting piece in which all 122 professional teams in the country’s four major sports -- that is, the MLB, NBA, NHL, and NFL -- were assessed with regard to their relative commitment to “analytics” or using the advanced stats available to guide them in the development of their franchises.

They say they came up with the list “after looking at the stats, reaching out to every team and dozens of informed sources and evaluating each front office." Not sure what stats they looked at, actually. In fact, it almost sounds like they eyeballed it. (Rim shot.)

I wrote a couple of posts some time back about reading Moneyball and reinvigorating an interest in the topic that for me traced all of the way back to reading Bill James’ Baseball Abstract each year as a teen.

The Oakland A’s and their sabermetrics-using general manager Billy Beane were the focus of that book, and they earned a spot inside the top 10 at No. 9 in the rankings. Meanwhile the Philadelphia 76ers -- for a time earlier this year the worst team in the NBA -- sit atop the rankings as the franchise that has “embraced data the most.”

Within each league teams are broken down into categories as either being “all-in” with analytics (using a poker metaphor), “believers,” having “one foot in,” being “skeptics,” or being “nonbelievers.” The New York Knicks -- the team that took over the distinction as the NBA’s worst this year from the Sixers -- ranks dead last among NBA teams, with their president Phil Jackson described as a “conscientious objector.” The Knicks rank just above the Philadelphia Phillies at the very bottom of the overall list.

There are a handful of NBA teams who are “all-in,” but in the NFL not one team is accorded that status. Only one NHL team is -- the Chicago Blackhawks -- while the MLB has the highest percentage of teams “all-in” with analytics (nine of 30 teams), reflecting how most of the earliest work in that area occurred in baseball before making its way to other sports.

My Panthers are described as “skeptics,” while my Hornets have “one foot in” the analytics door. I’d probably describe myself as having “one foot in” as well, and so tend to feel better about the Hornets’ commitment than that of the Panthers.

In fact, I would guess that each team’s fans feel more or less encouraged by the report according to how closely their team’s evaluation matches their own views of using advanced stats to guide roster decisions, the management of salaries, line-up creation and other in-game moves, and so on.

Someone should poll fans of all 122 teams and with the results build a spreadsheet, then measure the findings against team performance, attendance figures, regional climate, the city’s GDP, and other relevant factors to create a Fan Contentedness Index to be used for the scheduling of promotions and ticket pricing.

Or, you know, they could skip all that and just listen for cheers and boos.

More Than Meets the Eye: Moneyball and Poker

Last Christmas Vera got me a Kindle. Since then I’ve managed to read a half-dozen titles or so on the device, although whenever I find myself desirous to pick up a new read I still more often than not choose a used hard copy (often cheap) over an electronic one (sometimes cheap, sometimes not).

For instance, Jonathan Lethem’s Motherless Brooklyn (1999) was recently recommended to me, and I ended up ordering a used paperback rather than go for the Kindle version. It’s a cool read, a very inventive and smart example of “hard-boiled” fiction. Also shares some of the same territory I tried to cover in my Same Difference (which is why Lethem’s book was recommended to me).

With Amazon Prime, though, I get to take a book out of the “Kindle Lending Library” each month, and for August I chose Moneyball (2003) by Michael Lewis. That’s the best-seller telling the story of general manager Billy Beane guiding the Oakland A’s to success on the field despite spending relatively little on salaries via innovative methods of evaluating talent. (A well-regarded film adaptation starring Brad Pitt appeared last year.)

The book is about more than just Beane, though, relating the whole history of so-called “sabermetrics” or the analysis of baseball statistics pioneered by Bill James and others. I’ve written here about James and his Baseball Abstract before, noting how as a young person I was fairly fascinated by James and his unique way of crunching baseball’s endless numbers to come up with new and different ways of interpreting what exactly is happening when we watch a baseball game.

I’m about halfway through Moneyball and so far am appreciating Lewis’ way of telling the story as well as his understanding of the historical context of baseball, generally speaking, and sabermetrics in particular. And -- perhaps unsurprisingly -- I’m finding myself struck time and again with how the question of evaluating players’ talent in baseball overlaps with similar questions about the skill of poker players.

The parallels are seemingly endless. In both cases there exists objective evidence from which come ideas about performers’ skills. We see poker players win hands. We see baseball players make plays. And in both cases stats are produced which can be later examined and from which further conclusions might be drawn.

But there’s mystery in both cases, too, as well as other factors that cloud our judgment, making it harder to understand the significance of, say, a baseball player earning a walk or a poker player making a well-timed three-bet and forcing a fold.

Here’s just one short passage from early in Moneyball illustrating three different points of comparison. It comes in the context of characterizing how scouts tended to evaluate talent prior to the rise of sabermetrics and advances in technology that enabled a lot more depth and breadth when it came to statistical analyses:

“There was, for starters, the tendency of everyone who actually played the game to generalize wildly from his own experience. People always thought their own experience was typical when it wasn’t. There was also a tendency to be overly influenced by a guy’s most recent performance: what he did last was not necessarily what he would do next. Thirdly -- but not lastly -- there was the bias toward what people saw with their own eyes, or thought they had seen. The human mind played tricks on itself when it relied exclusively on what it saw, and every trick it played was a financial opportunity for someone who saw through the illusion to the reality. There was a lot you couldn’t see when you watched a baseball game.”

The parallels to poker here are obvious. Most of us interpret others’ decisions at the poker table by comparing them to our own, sometimes to our detriment. Our views of others are also often swayed heavily by what happened recently, with what happened on the last hand often given undue importance. And there are many examples in poker where we see something clearly yet interpret it wrongly.

That latter point becomes kind of a theme in the book, what Beane comes to refer to as being “victimized by what we see.” The work of James and others helped Beane realize that “the naked eye was an inadequate tool for learning what you needed to know to evaluate baseball players and baseball games.”

Poker has seen its own version of “sabermetrics” emerge over the last decade with the rise of online poker and tracking programs like PokerTracker and Hold’em Manager that yield all sorts of additional information about players’ tendencies, performance, and -- if interpreted correctly -- skill. Ideas that in some cases challenge the received wisdom of the old guard, represented in Moneyball by the fraternity of old scouts whose methods were challenged by Beane and his statistical-minded cohorts.

I’m glad I chose Moneyball as my Kindle read for this month. I suspect other poker players -- especially those who happen also to be baseball fans -- would like it, too.

Keeping Score

When I was a kid I watched a lot of baseball. Collected cards, scored the games, bought yearbooks, and all the rest. Loved it. Then other stuff came along that had the effect of lessening my interest considerably. Stuff like free agency. Huge salaries. Girls.

Before all that, though, I’d always get a copy of Bill James’ Baseball Abstract each preseason and read and reread the sucker all year. James is a long time baseball writer who specializes in various kinds of statistical analyses. James called his discipline “sabermetrics” (after the Society for American Baseball Research or SABR). Was responsible for all sorts of innovative ways of analyzing players’ performances, including inventing certain stats like “runs created” and “power/speed numbers” and the like.

I was scrounging around in the attic yesterday looking for those Abstracts. Came up empty, though I’m sure they are around somewhere. Hope I find them, as there should be a dozen or so complete sets of cards in the near vicinity, I’m guessing. I wanted to find the one with an essay proposing a new kind of box score, one that provided more detailed information than the relatively sparse ones we used to get in the sports page every morning. (Box scores have changed considerably since then, partially because of James’ influence, I think it is safe to say.)

Looking online I’m seeing the article I’m looking for was probably the one titled “Project Scoresheet.” Besides introducing a new kind of box score, James was also hoping to recruit fans from around the country to help compile data from all games in a more thorough way than was being done in the early 80s. (This was way before the internet, dontcha know.)

After a bit more hunting online, I see that James’ “Project” indeed was successful and continued through 1991, after which James joined a group called STATS, Inc. (“Sports Team Analysis and Tracking Systems”) that tracks statistics for other sports, too. He also apparently was hired by the Boston Red Sox a few years back as a consultant.

Why was I interested in such stuff? Well, I happened to have grabbed Mike Caro’s Caro’s Book of Poker Tells off the shelf the other day and as I was rereading I found myself recalling James’ Abstracts.

Caro and James have certain qualities in common, I think. Both are analytical thinkers, and both in their writings can be found time and again explicitly trying to be iconoclastic or innovative or whatever adjective you want to use for someone who is not satisfied with simply rehearsing “received wisdom.”

In fact, as those of you who have read the Book of Poker Tells no doubt recall, Caro (like James) there introduced a new kind of “box score” or way of recording poker hands. In the book he explicitly (vainly?) expresses a desire that his “MCU Poker Charts” become “universally accepted” as the standard for conveying a poker hand. (“MCU” stands for the fictitious “Mike Caro University” from which emanate all of Caro’s seminars, writings, etc.) If you click on the picture you can see a larger version the chart, if yr curious.

The charts work well enough in the book, although obviously they never really came close to becoming the “standard” for recording and conveying all of the information from a poker hand. In fact, they are probably too busy and non-intuitive, although when reading the book one gets used to them easily enough. No surprise, really, that the “Charts” never really came close to becoming any sort of standard.

In fact, one kind of gets the feeling Caro himself didn’t really have a lot invested in the idea of the “MCU Poker Charts.” I can’t find them anywhere on his website, nor are Word documents with the charts available on planetpoker.com (as even the most recent edition of Caro’s book promises).

I like Caro and would be one of those who’d argue he’s made significant contributions to poker over the years, the most significant being the way he helped shaped players’ awareness and analyses of physical tells. Them “Poker Charts,” though, are somewhat less significant, although I’ll give Caro some credit for drawing attention to the fact that when reporting poker hands one needs to be as thorough as possible.