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Re: "standard error" of OPR values
Here's a poor-man's approach to approximating the error of the OPR value calculation (as opposed to the prediction error aka regression error):
1. Collect all of a team's match results.
2. Compute the normal OPR.
3. Then, re-compute the OPR but excluding the result from the first match.
4. Repeat this process by removing the results from only the 2nd match, then only the 3rd, etc. This will give you a set of OPR values computed by excluding a single match. So for example, if a team played 6 matches, there would be the original OPR plus 6 additional "OPR-" values.
5. Compute the standard deviation of the set of OPR- values. This should give you some idea of how much variability a particular match contributes to the team's OPR. Note that this will even vary team-by-team.
Thoughts?
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Last edited by wgardner : 16-05-2015 at 14:14.
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