Quote:
Originally Posted by AGPapa
I'll work on the 50 and 100 match splits and put them up later.
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I've calculated the errors in match score predictions for every 10th split from 50 to 150 matches.
The X axis in the attached chart is the number of matches in each division used as training set. The Y axis is the square root of the averaged squared error per match in the testing set (the remaining matches).
You can see that adding apriori estimations makes the predictions better across the board.
Interestingly, the MMSE (Oavg prior) estimation starts out pretty good at 50 matches (a little under a third of the way through). I wonder why Will's simulated results are different? You can see that the gradual improvements still exist, just as in the simulation (except for the last datapoint. I think that on the last day teams played differently than before).