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Influence Explained

I like to publish some sort of projected standings throughout the season, and I have always wanted to come up with something unique. For a couple years, I used the baseball pythagorean theorem with the unbalanced schedule in mind. This past year, I threw in predicted standings that were weighted, based on how far we were through the year.

There are other places out there that do great work projecting team records though, and as a general rule, I try to avoid duplicating readily available work elsewhere.

I've chosen to call this post "power rankings," but I should take time to think up a better name for it. The picture aims to capture two basic things: how good a team is, and how popular they are. The basic premise is that the higher the team's bubble, the better they are. The bigger the team's bubble, the more popular they are. The methodology is simple too.

I use the playoff odds provided at coolstandings.com to judge how "good" a team is.

Popularity is a bit trickier, and my method has its limitations. Simply put, I measure popularity by hits on Google. It's not as simple as that though.

Google, in their continuing amazement, has something called insights. Essentially, it is an archive of their search data. So, I went into the archive, and typed in every team name, narrowing the focus to the past 30 days, and only for hits in the "baseball" category. Teams with more hits get higher scores. So, a bubble twice as big as another on the graph is a team that was searched for twice as much on Google.

Like I said, the method certainly has its limitations. For instance, for a search term like "Angels," less than 10% of the hits are in the baseball category - and some of the hits include "Dodgers," interestingly enough. "Los Angels" pops up as a general hit for "Angels", I'm pretty sure because enough people misspell "Los Angeles"...but a person could conceivably type "Los Angels," really mean "Los Angeles," and really be looking for something about Angels baseball. This is all to provide a picture of how gray the line I'm looking for is.

Furthermore, searching "Mariners" with no specific category filters returns highly relevant hits to the baseball team, but a noticeable percentage of them are filed under "Entertainment" and "Local." Presumably, limiting the search to baseball cuts out relevant hits for most teams - but, thanks to teams with generic enough names like "Angels," expanding the net throws in a ton of hits that aren't relevant.

For now, my best solution is to use the baseball filter, and acknowledge the limitations. I will refine this method as the season progresses, and eventually expand this explanation as needed.

So, how much does winning lead to popularity and relevance? When is a team underrated, and when is one overrated? Who has faithful fan bases? Does interest wane for losing teams, and increase for winners? Will big stories within a week cause spikes of interest for particular teams? How much is popularity tied to media exposure? Financial resources? Market size? I hope this graphic begins to answer some of these questions. I don't have an intuitive feel for what will happen, to be honest. I hope looking at baseball teams this way leads to some interesting, novel results.