More Ways to Derive Probability and Margin Predictions From Head-to-Head Prices

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A couple of weeks ago, in this earlier blog, I described a general framework for deriving probability predictions from a bookmaker's head-to-head prices and then, if required, generating margin predictions from those probability predictions.

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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 Simple Margin Predictors

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Having a new - and, it seems, generally superior - way to calculate Bookmaker Implicit Probabilities is like having a new toy to play with. Most recently I've been using it to create a family of simple Margin Predictors, each optimised in a different way.
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Can We Do Better Than The Binary Logit?

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To say that there's a 'bit in this blog' is like declaring the 100 year war 'a bit of a skirmish'.

I'll start by broadly explaining what I've done. In a previous blog I constructed 12 models, each attempting to predict the winner of an AFL game. The 12 models varied in two ways, firstly in terms of how the winning team was described ...
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