Scoring Catenation: An Alternative Measure of Momentum

Almost two years ago, in a post-GF funk, I recall painstakingly cutting-and-pasting the scoring progression from the afltables site for 100 randomly-selected games from 2012. I used that data to search for evidence of in-game momentum, there characterising it as the tendency for a team that's just scored to be the team that's more likely to score next.

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Scoring Shot Conversion Rates: How Predictable Are They?

In my earlier posts on statistically modelling team scoring (see here and here) I treated Scoring Shot conversion as a phenomenon best represented by the Beta Binomial distribution and proceeded to empirically estimate the parameters for two such distributions, one to model the Home team conversion process and the other to model Away team conversion. The realised conversion rates for the Home team and for the Away team in any particular game were assumed to be random, independent draws from these two fixed distributions.

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Scoring In Bursts: Evidence For In-Game Momentum?

The notion of momentum gets flung about in sports commentary as if it's some fundamental force, like gravity, that apparently acts at both long and short distances. Teams have - or don't have - momentum for periods as short as a few minutes, for perhaps half a quarter, going into the half-time break, entering the Finals, and sometimes even as they enter a new season, though I think when we start talking about momentum at the macro scale we wander perilously close to confusing it with another fundamental sporting force: form. It's a topic I've addressed, in its various forms, numerous times on MoS.

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Why 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).

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Why 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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Entropy in AFL Scoring (Revisited)

At the distinct risk of diving yet deeper into what was already a fairly esoteric topic, I'm going to return in this blog to the notion of entropy as it applies to VFL/AFL scoring, which I considered at some length in a previous blog. Consider yourself duly warned - this post is probably only for those of you who truly enjoyed that earlier blog.

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Modelling Team Scores as Weibull Distributions : Part II

In a previous post I discussed the possibility of modelling AFL team scores as Weibull distributions, finding that there was no compelling empirical or other reason to discount the idea and promising to conduct further analyses to more directly assess the Weibull distribution's suitability for the task.

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How Many Eras of VFL/AFL Football Have There Been?

Most sporting codes with a history of any significant length will eventually be described in terms of having passed through a number of eras, one or both ends of which are usually defined by some relatively obvious characteristic that forms the basis of the discussion.

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Assessing Probability Forecasts: Beyond Brier and Log Probability Scores

Einstein once said that "No problem can be solved from the same level of consciousness that created it". In a similar spirit - but with, regrettably and demonstrably, a mere fraction of the intellect - I find that there's something deeply satisfying about discovering that an approach to a problem you've been using can be characterised as a special case of a more general approach.

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Modelling Miscalibration

If you're making probability assessments one of the things you almost certainly want them to be is well-calibrated, and we know both from first-hand experience and a variety of analyses here on MatterOfStats over the years that the TAB Bookmaker is all of that.

Well he is, at least, well-calibrated as far as I can tell. His actual probability assessments aren't directly available but must, instead, be inferred from his head-to-head prices and I've come up with three ways of making this inference, using an Overround-Equalising, Risk-Equalising or an LPSO-Optimising approach.

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Home Team and Away Team Scores Across VFL/AFL History

About 18 months ago I investigated the statistical properties of home teams' and away teams' scoring behaviour over the period from the start of the 2006 season to the middle of the 2012 season taken as a whole. In that blog, using the VGAM package, I found that the Normal distribution provided a reasonable fit to the scores of Home teams and a much better fit to the scores of Away teams over that entire period.

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What's More Important: Who You Play or Where You Play Them?

The benefits of playing at home have been extensively investigated both here on MAFL for Australian Rules football and more generally within the sports prediction community for this and other sports. Put simply, teams that play at home win more often and score more points than you'd otherwise expect them to after adjusting for the quality of the opponents they face.
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