Team Scoring Model Parameter Sensitivity
/In recent blogs we've being exploring a range of topics related to team scoring, all of them based on a model I created in a series of blogs
Read MoreEstimating Game Margin Variability: Empirical Challenges
/Lately I've been thinking a lot and writing a little - a mix that experience has taught me is nearer optimal - about the variability of game margins around their expected values.
Read MoreSuperMargin Implications? Yes, They Are Atrocious.
/In a recent blog I developed an empirical model of AFL scoring in which I assumed that the Scoring Shots generated by Home and Away teams could be modelled by a bivariate Negative Binomial and that the conversion of these shots into Goals could be modelled by Beta Binomials.
Read MoreWhy AFL Handicap-Adjusted Margins Are Normal : Part II
/In the previous blog on this topic I posited that the Scoring Shot production of a team could be modelled as a Poisson random variable with some predetermined mean, and that the conversion of these Scoring Shots into Goals could be modelled as a BetaBinomial with fixed conversion probability and theta (a spread parameter).
Read MoreWhy AFL Handicap-Adjusted Game Margins Are Normal
/This week, thanks to Amazon, who replaced my unreadable Kindle copy of David W Miller's Fitting Frequency Distributions: Philosophy and Practice with a dead-tree version that could easily be used as a weapon such is its heft (and assuming you had the strength to wield it), I've been reminded of the importance of motivating my distributional choices with a plausible narrative. It's not good enough, he contends, to find that, say, a Gamma Distribution fits your data set really well, you should be able to explain why it's an appropriate choice from first principles.
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