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SUBMIT YOUR IDEAHere's my solution:
Solution attached.
Yes, I peeked...
For some reason, the Tree Model got me closest predicting the Super Bowl...?
Anyway, great to be learning this topic, slowly dawning on me...
...and I know it's close to blasphemous, but I even got the Pearson's correlation choose the variables for a predictive macro...
Kind regards,
Arjan Loogman
Interesting to look at what data sets produce more accurate results. In addition to predicting results using all data I broke out regular season from post season to see if it was more accurate (it was not), but not enough data for post season to return a result. I found some feeds for NHL data, so I might try my hand at building predictive models for hockey. I read an article that hockey is going to have about 3,000 data points per second for games, so lots to analyze.