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07-31-2012, 12:10 PM
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To study home ice advantage, we need to have a starting point for the analysis.

First, what is it that we are trying to measure? Are we solely measuring the cumulative effect of travel, first change, sleeping at home, etc., or do we want deconstruct the cumulative effect?

If we are deconstructing the cumulative effect, it may be worthwhile to look at some of the 'abnormal' cases first to test various hypotheses. This would include one-game road trips, teams within a close distance of each other (day-trips), teams at higher altitudes, etc. to see how these situations compare to the 'normal' situations.

From thinking on this for just a minute, it seems most effective to focus on removing travel distance, trip length, time between games, etc. from the data to isolate a better measure of home-ice advantage.

As a starting point, it would be interesting if the data could be separated by trip length, position on trip, etc.

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