A Comparison of SOGR & VSRS Ratings

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Earlier posts on the Very Simple Rating System (VSRS) and Set of Games Ratings (SOGR) included a range of attractive graphs depicting team performance within and across seasons.

But, I wondered: how do the two Systems compare in terms of the team ratings they provide and the accuracy with which game outcomes can be modelled using them, and what do any differences suggest about changes in team performance within and across seasons?

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Set of Games Ratings: All Teams' Charts

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The Set of Games Ratings post from late December introduced a twist on Tony’s VSRS concept. For any given set of games, the SOGR approach produces a rating for each team indicating its relative scoring ability within those games. Each SOGR model is optimised for the set of games on which it was fitted (in the least squares sense).

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Introducing ChiPS

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In years past, the MAFL Fund, Tipping and Prediction algorithms have undergone significant revision during the off-season, partly in reaction to their poor performances but partly also because of my fascination - some might call it obsession - with the empirical testing of new-to-me analytic and modelling techniques. Whilst that's been enjoyable for me, I imagine that it's made MAFL frustrating and difficult to follow at times.

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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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Estimating Team-and-Venue Specific Home Ground Advantage Using the VSRS

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In the Very Simple Rating System as I've described it so far, a single parameter, HGA, is used to adjust the expected game margin to account for the well-documented advantages of playing at home. We found that, depending on the timeframe we consider and the performance metric that we chose to optimise, the estimated size of this advantage varied generally in the 6 to 8-point range.
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Optimising the Very Simple Rating System (VSRS)

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In the previous blog, introducing the VSRS, I provided optimal values for the tuning parameters of that System, optimal in the sense that they minimised either the mean absolute or the mean squared error across the period 1999 to 2013
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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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