Reoptimisation and the Fear of Overfitting : ChiPS 2016

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Richard McElreath, in one of the lectures from his Statistical Rethinking course on YouTube aptly and amusingly notes that (and I'm paraphrasing) models are prone to get excited by exposure to data and one of our jobs as statistical modellers is to ensure that this excitability doesn't lead to problems such as overfitting.

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Set of Games Ratings: A Comparison With VSRS

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A few weeks back, Tony introduced the Very Simple Rating System (VSRS). It’s an ELO-style rating system applied to the teams in the AFL, designed so that the difference in the ratings between any pair of teams plus some home ground advantage (HGA) can be interpreted as the expected difference in scores for a game involving those two teams played at a neutral venue. Tony's explored a number of variants of the basic VSRS approach across a number of blogs, but I'll be focussing here on the version he created in that first blog.

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A Very Simple Team Ratings System

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Just this week, 23 year-old chess phenom Magnus Carlsen wrested the title of World Champion from Vishwathan Anand, in so doing lifting his Rating to a stratospheric 2,870. Chess, like MAFL, uses an an ELO-style Rating System to assess and update the strength of its players.
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Building Your Own Team Rating System

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Just before the 2nd Round of 2008 I created MAFL's Team Ratings System, MARS, never suspecting that I'd still be writing about it 5 years later. At the time, I described MARS in the newsletter for that week in a document still available from the Newsletters 2005-2008 section section of this website (it's linked under the "MAFL The Early Years" menu item in the navigation bar on the right of screen). Since then, MARS, as much to my surprise as I think to anyone's, has been a key input to the Line Funds that have operated in each of the ensuing years.
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