I started class on Friday with a though experiment.
You're playing blackjack, I told my sports writing and reporting class. You draw a pair of Kings. 20.
You say "Hit me."
You get an ace.
"So," I asked the students. "Did you make a smart decision?"
The students didn't hesitate. No, of course not. It was an incredibly stupid decision. One that just happened to work out. You got lucky.
I smiled. I had them.
That brief experiment is how I started introducing my sports writing students to using analytics in their reporting. This is the first time I've introduced any kind of serious analytics in my sports writing class.
I taught analytics in two sections. The first was a lecture that introduced the idea of probabilistic thinking to them - the idea that whether or not something is good decision is separate from the outcome. Just like you can't say hitting on 20 is a good move simply because you lucked into an ace, you can't say that a move or decision worked just because a team won a game. At their core, analytics are about thinking things through probabilistically, putting yourself in the best position for an outcome. That conflicts with The Sport Ethic, where winning is the only thing that matters. The lecture also used a short film on Kevin Kelly aka The Coach Who Never Punts to showcase a.) analytics do not have to be boring and b.) how the traditional media in that movie view analytic thinking as "risky" or "crazy" when it's actually often rooted in data.
The second part was an in-class assignment. Students were given a half-dozen analytics based questions and had to find the sources online on their own and answer the questions. (Both the assignment and the powerpoint are free for anyone to use). They also had to start thinking of story ideas that could be based in analytics.
There are countless ways I can make it better and more useful to students. But teaching in 2016, it's important to at least introduce students to the idea of using WAR, DVOA and Player Efficiency Ratings in their stories. For one thing, access to sources is shrinking, and in a lot of circles we're beginning to question the usefulness of post-game interviews in the first place. With this in mind, being able to tell stories through the use of analytics is an important skill. If access is shrinking, we should be thinking of ways we can cover sports that don't rely fully on that access.
Analytics aren't perfect. But neither is talking to human sources. It's important for young journalists to have as many tools in their toolbox as possible. In sports journalism in 2016, that includes an understanding of analytics - what they can and can't tell you, what stories they can help you tell.
I'd welcome any edits, things I did wrong, or suggestions I can teach this better in the future.