What will you write when computers write all the game stories?

The press corps of the future heads to the locker room.

If you’ve covered enough games or events, you’ve probably had this thought, which I’ve said out loud many times: “Well, there’s your lede writing itself.”

When Santonio Holmes makes a brilliant catch for the game-winning touchdown with 35 seconds left in the Super Bowl, your lede is pretty much written. You have to put the words together, but those words are going to include Santonio and Holmes and 35 seconds and touchdowns, Steelers, beat and Cardinals.

It’s almost like a really smart computer could do it.

Well, guess what.

A New York Times story this week described the work of Narrative Science, a software startup in Evanston, Ill., that, according to the company’s website, “transforms data into high-quality editorial content. Our technology application generates news stories, industry reports, headlines and more—at scale and without human authoring or editing. Narratives can be created from almost any data set, be it numbers or text, structured or unstructured.”

A box score is a data set, and so is a play-by-play description. Sporting event “gamers,” the story that describes the facts of what happened in the game, lend themselves well to what Narrative Science does, as any beat writer could tell you.

A great game story, like a great anything else, is an art form. But over the last century more than one ink-stained wretch on a late-night deadline has been heard to mutter that a well-trained monkey could write a passable one.

And in today’s media world, a passable gamer is good enough for most readers and most games. As Rory Brown wrote in this space the other day, once the reader knows the basics of what happened in a game, the game is old news. The real value is in other types of writing:

When the stock market falls, people want to know how far. Once they know that, the story is old news. Immediately, folks are looking ahead to what the market could do tomorrow, the next day, the week ahead, monthly, quarterly and yearly forecasts.

When we’re in front of a computer, we look ahead. Same goes for sports.

Narrative Science first gained attention early last year, when a mini-flurry of stories described its early work.

Now, the Times reports, Narrative Science is really in business, with 20 clients, including the Big Ten Network, which first used the automated service to report on baseball and softball games, then expanded into football and basketball.

The stories get good reviews from Big Ten Network execs and other clients, including a construction industry trade publisher that uses Narrative Science to provide monthly reports on local housing markets.

It’s safe to assume that the technology is only going to keep getting better and cheaper, which is what technology tends to do. It’s already cheaper than sending a reporter to the game.

Does that mean reporters are doomed?

One way to look at it is that using computers to generate simple game stories frees up human reporters to do more actual reporting, to investigate and write about things that an algorithm isn’t going to be able to figure out.

But this is the real world we live in, and in the real world when companies see a chance to have a machine do a job a human used to do, that human is at least as likely to be laid off as reassigned.

The question for you, successful or aspiring sportswriter, isn’t what sports news organizations should do with the money they’re going to save by having game stories written by machines. It’s how you will be able to make a living writing sports in a world where the job description “person who writes game stories” is likely not to exist any longer.

What can you do that, for the foreseeable future anyway, a computer won’t be able to do?