All Things Techie With Huge, Unstructured, Intuitive Leaps

Super Bowl XLVIII Predictions From A Datamining Geek

First of all, let me say that these predictions will probably be somewhat wrong.  But what if they aren't?  These predictions are made without looking at the football performance of the two teams -- Seattle and Denver.  But rather they are made with an analysis of social media and datamining the web for crowd chatter.  There is the premise that the crowd is always right, and perhaps they will be on this one.  I like to call this technique "crowd mining".  So lets get to it.

My research and dubious math skill predict that going on crowd behavior alone, I predict that the winner will be the Seattle Seahawks.  After I crunched the numbers, I was disheartened to learn that Peyton Manning is the Broncos quarterback.  He is a formidable force and I am glad that I didn't recognize this fact before I started this exercise, otherwise it would have skewed my results.  And it may be the reason why these predictions could be wrong.

But what numbers does the crowd sentiment suggest:



Then I decided to apply some statistical normalization to the numbers, and I got the following result:



So, I am going to do something that I have never done before, and lay a bet on those two results.  Various pundits figure that over $100 million will be bet on this Super Bowl

As a further step in statistical analysis, you have to take into account fat tails, or random events.  Suppose that for some reason there is a blowout, an injury, or a team can't play well in the weather, or if the awesome Manning offence is brought down by the Seattle defense.  So, to cover the entire range of possibilities, the following are the complete fat tail results.  The left column is the Seahawks and the right column is the Broncos.  If these predictions are accurate and we get a weird game like a high scoring or a very low scoring game, here is the range of predicted results.

Seattle       Denver

3       to     0
7       to     3
10      to     7
13      to     10
17      to     13
21      to     14
24      to     17
27      to     20
27      to     21
30      to     23
31      to     24
33      to     26
35      to     27
35      to     28
36      to     29
37      to     30
38      to     35

It will be interesting to see how these geekazoid predictions turn out.

No comments:

Post a Comment