Today at SB Nation's main site, Andrew Sharp wrote a long, obviously thought-out piece on the Sloan Sports Analytics Conference that just took place at MIT. This conference is a place where fans, front-office folks, media, and plenty of others get together to talk about analytics -- new ways to look at sports data, and how to measure sports.
Andrew went to Sloan as a skeptic, and he says so early in his article. And while I appreciate the fact that he says he wanted to understand where his skepticism of advanced stats comes from, I came away from this article feeling like there's something missing in his article and argument.
I'm not here to slag on Andrew or his article. But as the managing editor of one of SB Nation's sites specifically dedicated to advanced stats and analytics (along with Football Study Hall), what I am here to do is provide, what I see, as the democratic response. I'd like to take a couple of points that Andrew made specifically in his article, and talk about what they mean to someone who's very much a part of this new wave of "analytics" -- especially appropriate as I have three staff writers on site at the SABR Analytics conference in Arizona today.
What I'd like to do is pull a few arguments against the increased use of analytics from Andrew's post, and provide my personal reaction to them. I think that there's plenty of room for other viewpoints, but some of the arguments brought up in this article are ones that don't quite ring true to someone who spends a lot of time around analytics, and the people who use advanced analytics.
There's one section in Moneyball where Michael Lewis spends a few pages on a scene from an Oakland front office meeting where they're arguing over a prospect named Jeremy Brown, a catcher from the University of Alabama. He's overweight and the scouts don't like him, but he scores high in a lot of the categories that Billy Beane and his assistant Paul DePodesta use to predict success. An argument ensues and lasts several pages, and it ends like so:
The fat scout looks up from his giant chocolate chip cookie and seeks to find a way to get across how unimpressed he is. "Well," he says, exaggerating his natural drawl. "I musta severely unnerestimated Jeremy Brown's hittin' ability."
"I just don't see it," says the vocal scout.
"That's all right," says Billy. "We're blending what we see but we aren't allowing ourselves to be victimized by what we see."
This argument is fat, slobby ignorance vs. Billy Beane, the grinning badass who's here to shake up the game whether scouts can handle it or not.
That doesn't actually sound like an argument of ignorance vs. Billy Beane. That sounds to me like someone making the argument that there might be a way to examine player performance beyond what a person sees. If Andrew wants to make the point that we don't need analytics to tell us whether a player is good or not -- something that he points out when deriding Kirk Goldsberry's NBA infographic comparing Larry Sanders to David Lee -- okay, I see his point to an extent.
The point of advanced analytics, at least the way I see it, is in part to bring together what we see with what we don't see. But sometimes we don't see everything. If one person were to see Jeff Francoeur play baseball, especially sporadically, they might think that they're seeing a good baseball player, because he occasionally hits the ball well, or he has a cannon arm, or because he looks like a good ballplayer.
But isn't there room to say that what we see isn't always what's the right.
Oh, and the Moneyball caricatures are at times embarassing, both in the movie and the book. I don't see it as much different than any sort of perspective, which spins an account due to a particular viewpoint.
Analytics experts are never wrong.
This is a truly bizarre blanket statement, in my opinion. I can't imagine ever speaking to an analytics expert who claims to be right all the time.
I've read Nate Silver's book, where he talks about forecasting in terms of probabilities. Any good forecaster is wrong at times, and it allows you to refine your models and make adjustments. Analytics experts, like anyone else, are wrong often.
In the comments, Kurt Mensching mentions that the "smugness" associated with sabermetrics hurts the cause, and I think Andrew implies this in his article throughout. Personally, I couldn't agree more that taking a know-it-all or smug stance that analytics is the "right" way to view baseball is detrimental to getting other people to appreciate your viewpoint.
You know who's great at explaining analytics without being smug? Rob Neyer at SB Nation. And Jonah Keri at Grantland. And Tom Tango. And dozens of other analytically-savvy writers and analysts. If you look, it's easy to find plenty of people who believe in analytics and express their opinions without coming across as a know-it-all. We all have our opinions, and anyone can sound smug at a given time. The more that we can do to talk about this branch of sports enthusiasm with a measured tone, the better.
But ... I also don't think this is any different from any non-analytical talking heads that you see on any sports studio show, or writers who advocate that analytics isn't the "right" lens to view a game through. Smugness is a turn-off no matter which side presents it. I understand that just because sabermetrics or analytics produces a data-based view of the game, it doesn't mean that that view is always right.
On the same token, I feel like data-based views of the world are more likely to be correct than non-data-based views. That's why I value things like natural science over things like non-scientific explanations for natural phenomena. I have my viewpoint on the matter, and it's a strong one ... but there's room for reasonable people to disagree. And I do feel like many analytics experts understand this.
The idea of the smug, arrogant analytics expert who listens to no one else and watches no baseball games, focusing on his spreadsheet instead is just as much a caricature as Art Howe in the Moneyball film. It's an easy fiction, and hardly representative of the whole
A growing faction of the media uses advanced stats to write mythbusting articles to make the sports conversation smarter, but it actually just makes things more pedantic. We are not scouts. Rather than couch all of our 2013 sports arguments in data that's not as conclusive as it seems, it's more fun to just have an argument.
Is the claim here that analytics are ending arguments, and that's taking away the fun of arguing? I don't see it. I see people who dismiss or de-value analytics, arguing with people who value analytics or advanced stats. Saying that analytics ends arguments, when it's created a whole new subsection of things to argue about, doesn't make sense to me.
(And for the record, I don't really find arguing to be much fun. This is not a fun article for me to write. It is a chore. Arguing for advanced analytics has been done in a number of other places, and in a number of different ways, by people plenty smarter than me.)
Analytics have value as we try to learn more, and anyone who really cares about sports will end up using them in one way or another. But in the end, all the data and process revolves around humans, and there's a big part of this that'll always be a guessing game.
Has anyone ever argued the opposite of this second sentence? That the human factor of sports is something that cannot be controlled for simply using stats and analytics and numbers? In all seriousness, who is making this argument? I'm not sure that anyone here at Beyond the Box Score, or anyone at any other major analytics site, would insist that analytics can be a one-stop-shop for everything having to do with sports.
And if we're talking about what the analytics movement means for people like you and me, that's the point that seems missing from all the analytics panels about the future of sports.
I'm not entirely sure an event like Sloan is designed to speak to the casual fan -- it's something that caters very specifically to the analytics crowd.. The way I see analytics, in regards to being a fan, is just as another angle with which to view sports. People watch sports for all kinds of reasons. Some watch to see phenomenal acts of athleticism. Some watch because they identify closely with a particular city or team. And some might watch to see acts of statistical achievement
When you take the misleading data that distracts teams and all the insufferable Internet arguments that distract fans and put it next to the handful of analytics approaches that actually add insight, the plus and minuses really might equal zero.
This sounds like someone is advocating an analytical approach to figuring out whether analytics are worth anything. I think we've hit analytics Inception.
And it's an argument against arguments, which if confusing given the previous argument that having arguments is fun. Is it only that internet arguments are insufferable?
Now and forever, everything you can't quantify is what makes sports worth loving.
This last line, the last of Andrew's article, probably frustrates me most. Different people love different things about sports. Some people love sports because they identify with a particular team, some people love sports because they love seeing acts of physical grace or strength or skill. Some people love sports because they gamble on it, and it makes them a boatload of money.
I love sports, in part, because when I was growing up, I had a baseball card collection, and my dad and I would spend hours and hours poring over cards, and talking about the crooked numbers on the back of them, and watching games. And part of what we talked about, part of how we communicated, and made sense of the game, was through the statistics. The fact that we can still do that, to this day, is something I think is important.
I love sports, in part, because we have the ability to see the forest for the trees, and vice versa when we look at it through the lens of baseball. When I look at a game, and I see David Wright make a boneheaded throwing error and go 0-4 the one Mets game a year when I can make it down to Citi Field, I don't have to think that he's a bum. I can use the entire set of data for his year, and recognize that, not only is he not a bum, but he's a great player -- and that doesn't change just because he had one bad game.
I love sports, in part, because investing time and energy into analytics is an intellectual exercise that gives me a lot of joy -- the joy of problem-solving, the joy of discovery, the joy of feeling part of a team.
So yeah, things you can quantify at least contribute to the way I feel about baseball. They matter to me, just as they may not matter to someone else.
I'm glad Andrew doesn't love sports because of analytics, in part or in whole -- I'm just glad he loves sports at all. Sports are great. But for some people, analytics is the way they view the sport and it gives them joy. It's not the only way for us to look at sports, but it's another way. Maybe it's useful, maybe it's not.
I'm not a casual fan of baseball, I'm an insane person. I study it intently, and analytics is part of my hobby. I have strong feelings and opinions.
But I am a rather casual fan of NBA basketball, and analytics has added to my enjoyment of the game, not taken from it. Knowing usage rate, PER, true shooting percentage, and the fact that the Nuggets a crazy amount of assists at home compared to on the road has made the games I watch more enjoyable, the same way that learning a little more about pick-and-roll defenses has.
In the end, analytics has become a large part of sports, but it's a part that can be just as much fun to fans as it is to the potential GM or internet writer or anyone else. It's just another way to look at the game.