Examining underlying data for abnormalities
It turns out that we will get one more NBA basketball game this year on Sunday. We won’t get any more hockey this season, and it turned out that this particular Stanley Cup series had some pretty terrible ratings from 4.17 million last year to 2.5 million this year.1 Having the series behind effectively a paywall on the TNT network apparently dramatically changed the ratings trajectory. A lot of goodwill was created during the 4 Nations Face-Off this year. That was great television. Apparently, one of the games had 16.1 million views in North America alone.2 You really have to take a moment and examine the underlying data for abnormalities when a promotional nation vs. nation one-time tournament substantially outperformed the final series of the year. By substantially, I mean that it just blew it out of the water. If you were interested in the overall health of the sport, you would want numbers trending in the right direction. That would mean having viewership closer to the 16.1 million number compared to the partly 2.5 million they managed. I mean, seriously, if you were a part of the NHL head office, this is something you would have to consider a major failure.
This is a lesson in understanding the value of abnormal underlying data. It’s a question of potential and opportunity. This time around I’m using the built-in footnote feature that Substack provides. One of the things that should not be discounted is just the extreme drop-off in viewership that was mentioned above. Any time 10 million people wander off, some cause has to exist. Using the footnote feature does have one big disadvantage in terms of being able to replace the content in a post by pasting from the Pages application. You cannot just paste content back and forth between Substack and Pages using the built-in footnote feature. That might be the reason I elect to go back to using my standard footnote method. This time around we are going to go with the built in feature, but it might very well be the last time.