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A Response to Michael Wilbon on Sports Analytics

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Why the sports analytics discussion raised in Michael Wilbon's piece is not a racial one, and how statistics should actually fit into the broader sports discussion.

Kyle Terada-USA TODAY Sports

Michael Wilbon of ESPN and The Undefeated posted an article this morning about sports analytics (mostly in basketball) and their presence in the African American community. It immediately elicited strong reactions from all corners of the internet, including yours truly. He definitely raised some interesting discussions, and I don't disagree with everything he said, but I feel like Wilbon is missing the point. Here are the three main issues that need to be addressed: race has nothing to do with the topic at hand, basketball analytics are vastly misunderstood, and the "eye test" is more complicated than it seems at first glance.

To start with, the whole context of the article revolves around how African Americans don't use or follow sports analytics. Wilbon talks about how people don't discuss analytics through "texts", or "at the barbershop", or "around the water cooler". Yet I could say the exact same thing about most of my friends regardless of race. Comments about analytics are rare no matter who is saying it, or where. Two of my buddies aren't going to be debating LeBron against Kobe by bringing up their Win Shares (WS) or True Shooting percentage (TS). They probably don't know what those are, and couldn't be bothered to find out. No, they will cite points per game, maybe assists and rebounds, and talk about titles. Lots and lots of talk about titles.

The main point is that discussion of sports statistics has nothing to do with race. White people or Asian people or Hispanic people or any other race don't care more about sports analytics than African Americans just because of the color of their skin. Wilbon isn't wrong that most fans don't talk about that stuff with their friends, but I disagree that it is a racial issue. It is very simply a basketball nerd vs. non basketball nerd divide, of those who like statistics and those who don't.

Sports analytics are being portrayed by Wilbon (and other anti-analytics people such as Charles Barkley) as something they are not. Very few sports writers or analysts think that a single statistic, or even a bunch of statistics, can completely sum up a player's value and worth. When I cite Chris Paul's incredible efficiency by using his effective field goal percentage (eFG), it's a commentary on one aspect of his game. I can say, "Chris Paul was a more efficient scorer than Kyrie Irving this year based on their eFG percentages", and it would be true. That is entirely different from "Chris Paul is better than Kyrie Irving". There is no be all and end all statistic for basketball, and probably never will be.

The bigger problem I have with Wilbon's arguments are that most commonly-cited basketball statistics are very simple, and based on high school level math (at most). Effective field goal percentage accounts for the basic mathematical truth that three is greater than two. Hence, three point shots are more valuable than two point shots. EFG really is that easy, and it takes an hour at most of research to figure out how it and other advanced shooting stats work. Plenty of useful advanced stats are just as quick to understand, and almost all of them can be found on nba.com or basketball reference.

The more advanced analytics get, the more frequently they are misused. RPM (real plus minus) is displayed on ESPN as a ranking, a number to judge players against each other. Except that's not really how the stat works or should be used. It is a way of measuring the effect a player has on his team when he is on the floor, nothing more or less. PER is another tool used to compare players, but it fails to take into account team context, player role, and position (big men generally have higher PER due to the way it rewards rebounding). Again, it has its uses, but broad comparisons miss the point.

So there are real failures in the way many people use the analytics we do have. But that is not the point Wilbon is trying to make. Instead, he is arguing for the age-old standard of judgment and comparison over any advanced statistic: the "eye test".

Basically, he argues (as many people have over the years) that you can tell just by watching the games who is good and who isn't. And I actually agree with him! The difference is.... the people who he is talking about can't do that. As mentioned earlier, when most NBA fans sit down to talk about players or teams, they will go for the simple stuff first: points mostly. And while those comparisons might be correct, they can't possibly tell the whole story. Steven Adams (before these playoffs anyway) is probably someone who few casual basketball fans would know. And if they would watch him play, they would see a guy who doesn't score the ball much, who doesn't even really have the ball very frequently. He doesn't record a ton of emphatic blocks like a young Dwight Howard, or vacuum every rebound in sight like a young Kevin Love. They might think he isn't all that good.

What fans who only watch the playoffs or other big games (what I think of as casual fans) might miss is all the activity he does that isn't immediately evident, or that doesn't show up on a stat sheet. How many times has an opponent gone into the lane, seen Adams there with hands raised, and then passed out or forced up a poor shot? A heck of a lot. People who watch games only casually mostly don't pay attention to that kind of stuff, or to his pick and roll coverage, or to a guy like J.J. Redick's incredible off ball movement.

I am by no means a NBA expert. There are thousands of people out there who watch more of it then I do, are better analysts of it, and know more about the game. But I watch at least one NBA game almost every day of the season (sometimes more), and just about every playoff game. So when one of my friends gets in an argument with me over "eye test" matters, I take my word over theirs (and usually they do too). Similarly, I may think some way about a certain player, read what a respected NBA writer has to say about them, and consider that my opinion might well be wrong. Mostly, I listen to people who have good NBA knowledge, and who have proven such through writings or their opinions.

Emotion is all well and good. Without emotion, there wouldn't be fandom, and nobody would care about sports. It is perfectly reasonable to fight for your favorite player or team and argue as to why they are good or undervalued. Nobody is trying to take that emotion away. And very few people think that statistics are all that matter. Human elements such as morale, momentum, and chemistry are all clearly relevant, and are impossible to quantify with numbers.

Sports analytics are a tool to be used, not the entire conversation. In fact, the people to whom they would be most useful are the same ones who ignore them for hot takes and loud shouting over one another. When two of my friends start arguing about how James Harden is better than Steph Curry, it doesn't do anyone any harm. When two prominent ESPN or Fox Sports personalities/writers make arguments that sports analytics roundly disprove, they are in essence misleading their audience. Sports are about a holistic understanding of the issues and context in each situation, not simply statistics vs. eye test. Refusing to ignore the facts at hand, however, is mere ignorance.