Quote:
Originally posted by str8outavannuys
On the Super Bowl contest:
Future contests like this (closest to final score) should have used lowest sum of squares method. It sounds complicated, but it really isn't.
(New England's actual points-Entry's guessed points for N.E) squared, + (Carolina's actual points-Entry's guessed points for Carolina) squared = Entry's score. Lowest sum of squares score wins.
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It looks like your algorithm does not distinguish the following case:
Actual Score: NE: 32; CAR: 29
Entry#1: NE: 30; CAR: 24
Entry#2: NE: 34; CAR: 24
The calculation for Entry #1, according to your algorithm, would be: (32-30)^2 + (29-24)^2 = 2^2 + 5^5 = 29
And the calculation for Entry #2 would be: (32-34)^2 + (29-24)^2 = (-2)^2 + 5^5 = 29
This is why, as I had mentioned in my
post on the superbowl contest thread, that you need an additional metric for accuracy -- I chose the absolute value of the difference between your guess for the point difference and the actual point difference. In this case, the point difference in the actual game is 3 (=32-29) (which, in some ways, indicates that the teams were evenly matched; a higher point difference would, presumably, indicate the opposite). The point difference for Entry #1 would be 6 (=30-24), while that of Entry #2 would be 10 (=34-24). Thus, under my algorithm, Entry #1 would win, which, I think, is a fairer result.
As for the sum of squares method in general, it penalizes guessing in a non-linear manner. This is why I suggested using absolute values.
Edited for spelling and a missing comma. 
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