Three years ago, I detested baseball. I thought it was endlessly boring, I didn’t enjoy watching it, and I never thought I could enjoy playing it.
However, a job opportunity opened up and a cursory knowledge of baseball was required. Interested in a job in the sports industry, I gave baseball a second chance and sat down with some buddies to take me through the game.
I ended up loving it. Which brings me to this year.
Watching the Giants sweep the Tigers in the World Series on Sunday night, I was struck by the ways in which metrics in baseball and social media are similar.
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In the midst of the announcers discussing ridiculous stats (the most ridiculous of them all was the fact that relieving pitcher Affeldt for San Francisco had his third child this year, and the last two times he had a kid the team he was playing for won the world series) I reflected on how the way stats are viewed has changed over the course of baseball’s history.
One of the biggest changes is the slow shift in understanding from what are useless metrics and which metrics actually matter. This is comparable to the shift in understanding of useful metrics in the social sphere and surprisingly there are a number of useful parallels between the two industries.
Runs and RBIs
A run is a point a team earns by advancing a player around all the bases and back to home plate to score. The team with the most runs wins the game. How can this not be an important thing to measure? As it turns out, measuring a player’s runs is actually one of the most useless stats in baseball.
Yes, runs themselves determine wins, but measuring them on a player to player basis is not as useful as it seems. Unless that player hits a home-run, they have no control over whether or not they get to cross home plate. The people who have all the power are the ones who bat AFTER them, because if they succeed in getting a hit they get to send the runner home.
In social media metrics, even as we continually grow and learn how to track this uncontrollable beast in better ways, many marketing reports are still plagued by a “tracking runs” mentality.
In the social media world, runs are the number Likes, Followers, Subscribers, etc. They are inarguably useful as they determine the audience who will see your message, give some form of credibility, and in some circumstances can even be viewed as what determines a metaphorical winner.
I mean, there are even people who will go so far as paying in order to win (similar to Barry Bonds and the steroid era of baseball).
Using this as the only measure of someone’s capabilities is tantamount to only paying attention to a ball players Runs stat. Just because you have a lot of “runs” attached to your account doesn’t mean you are an expert in bringing them in.
Unless you hit a lot of home-runs, it may very well be other people who are helping you win at Social Media.
Baseball clued into this shortcoming early on (1920 to be exact), and although runs are still tracked, they now primarily focus on Runs Batted In (RBIs). For those who aren’t familiar with this term, this is the number of base runners you send to home plate after succeeding in getting a hit.
This is a much more valuable stat as you can see who performs in clutch situations, converts on scoring opportunities, and helps your team win ball games.
Similarly, we need to track our online or social RBIs, which would be a measure of an individual’s engagement with their audience. This includes both conversations they have with people and the number of times their content is shared.
Other than performing as a star player and bringing in fans through brand awareness, the level of engagement that people have with your content, either through feedback, endorsement, or sharing, is the best way to “bat in runs”.
Content is usually shared because it is good. Good content is usually recognized by a wide audience. People want to follow people who produce good content.
This are how you collect your runs and showcase yourself as a social media powerhouse.
Wins Above Replacement
Wins Above Replacement (WAR) is a measure of how many wins a team would have with a star player playing their position versus a replacement level (minor league or bench) player playing in their place.
For example, if you have a solid first baseman with a WAR of 5 who gets injured and replaced by a bench player, the team would supposedly win 5 less games with this new player playing their position.
These calculations, however, are unstandardized as a variety of different sources calculate WAR slightly differently, measuring slightly different variables to produce a value.
There are so many factors that need to be taken into account that this kind of predictive modeling starts to seem pretty fantastical. It also can’t account for a minor leaguer who tears it up at the majors, or the rest of the team going on a hot streak.
The reason I bring up such a controversial statistic is that companies and marketers continue to try and come up with their own version of the WAR statistic: influence.
The problem is that influence in the real world isn’t really something that you can measure. It’s something that we might be aware of but we just can’t look at someone who is an expert and simply know that they are influential.
Arguably it should easier to get a handle of this in the realm of social as there is concrete data available, but there are too many factors (some that are not currently quantifiable) that we simply don’t have the ability to track.
Influence calculations are not only unstandardized, but several of the formulas are not openly available for critique or scrutiny. Even with the best of intentions and regardless of how popular they may be, most measures of influence are not credible or useful simply because they lack the necessary scope.
Until a formula is determined, or a standardized understanding of what “influence” is, tracking it seems to be an act of futility. All these attempts may result in the discovery that some things are intangible, out of quantifiable reach and will remain (at the very best) only educated guesses.
Along with all of these statistics, I find myself constantly needing to remind myself that these numbers aren’t being attributed to robots, but to human beings. Even though these athletes might be (arguably) the best players in the world, they aren’t perfect nor are they perfectly consistent. Any number of things could render these trend indicators completely valueless.
The same goes for metrics in the social space because the value of a certain page or profile is only as good as the person (or people) who runs it. And even with the vast experience and a statistically sound portfolio even the best of those people will make mistakes.
So as useful as metrics might be to give you direction, don’t treat them like the end all be all. Some of the most talented people I know only use metrics as guidelines, and go with their gut most of the time (similar to a good manager would when substituting in a pinch hitter late in a game).
There is a level of innate ability within each person who has found success online, and sometimes that needs to be trusted over the stories the numbers are telling you.