Comments on: Predicting Football Results? Use a Bayesian filter! http://konquest.org/predicting-football-results-use-a-bayesian-filter Because Science Matters Thu, 27 Aug 2009 08:40:28 -0700 http://wordpress.org/?v=2.8.4 hourly 1 By: Jim Ashburn http://konquest.org/predicting-football-results-use-a-bayesian-filter/comment-page-1#comment-6139 Jim Ashburn Mon, 28 Aug 2006 20:32:03 +0000 http://konquest.org/predicting-football-results-use-a-bayesian-filter#comment-6139 Paul and I appreciate the acknowledgment. As far as "too much time on our hands," the reason we have a geeky hobby like this one is that it's cheaper than golf and can be done from our homes after the kids have been put to bed. I do hope folks with an interest in the topic will take the time to read the paper, and I strongly encourage comparisons with other published methods. Most "solutions" offered up for this problem seem to fall into one or more of three different categories -- 1) they are unpublished, 2) their underlying model is weak or incomplete, 3) they have subjective inputs. Failing to publish a solution one is touting only raises suspicions -- is there something to hide? Any good model will follow basic rules of statistics. An obvious one for this problem is the Central Limit Theorem (http://en.wikipedia.org/wiki/Central_limit_theorem). Any model with "knobs" that cannot be determined self-consistently is incomplete. Subjective inputs indicate that the solution has failed to fulfill its most fundamental purpose -- removing all subjective elements from the rankings. We believe that overcoming this hurdle is our key contribution. One final note: We don't take this nearly as seriously as the tone of the paper might suggest. Except between September and January. Paul and I appreciate the acknowledgment. As far as “too much time on our hands,” the reason we have a geeky hobby like this one is that it’s cheaper than golf and can be done from our homes after the kids have been put to bed. I do hope folks with an interest in the topic will take the time to read the paper, and I strongly encourage comparisons with other published methods.

Most “solutions” offered up for this problem seem to fall into one or more of three different categories — 1) they are unpublished, 2) their underlying model is weak or incomplete, 3) they have subjective inputs. Failing to publish a solution one is touting only raises suspicions — is there something to hide? Any good model will follow basic rules of statistics. An obvious one for this problem is the Central Limit Theorem (http://en.wikipedia.org/wiki/Central_limit_theorem). Any model with “knobs” that cannot be determined self-consistently is incomplete. Subjective inputs indicate that the solution has failed to fulfill its most fundamental purpose — removing all subjective elements from the rankings. We believe that overcoming this hurdle is our key contribution.

One final note: We don’t take this nearly as seriously as the tone of the paper might suggest. Except between September and January.

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