Scoring Shot Conversion History in the VFL/AFL (1897-2015)

The off-season always seems a good time for adopting a more sweeping historical perspective in the analyses here on MatterOfStats. Today we're going to be reviewing Scoring Shot Conversion rates across the 119 seasons of the VFL/AFL from both a venue and a team perspective.

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An Improved VFL/AFL Team Rating System: MoSSBODS 2.0

Earlier this year in this blog, I introduced the MoSSBODS Team Rating System, an ELO-style system that provides separate estimates of each team's offensive and defensive abilities, as well as a combined estimate formed from their sum. That blog post describes the main motivations for a MoSSBODS-like approach, which I'll not repeat here.

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Predicting Bookmaker Head-to-Head Prices : Five Years On

Recently, in light of the discussions about the validity of the season simulations written up over on the Simulations journal, I got to thinking about modelling the Bookmaker's price-setting behaviour and how it might be expected to respond to the outcomes of earlier games in the season. It's a topic I've investigated before, but not for a while.

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Who's Best To Play At Home?

The 2015 AFL Schedule is imbalanced, as have been all AFL schedules since 1987 when the competition expanded to 14 teams,  by which I mean that not every team plays every other team at home and away during the regular season. As many have written, this is not an ideal situation since it distorts the relative opportunities of teams' playing in Finals. 

As we'll see in this blog, teams will have distinct preferences for how that imbalance is reflected in their draw.

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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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Modelling the Total Score of an AFL Game

Over the eight seasons from 2006 to 2013 an average AFL game produced about 185 points with a standard deviation of around 33 points. In about one quarter of the games the two teams between them could only muster about 165 points while in another one quarter they racked up 207 points or more.

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

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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Estimating Home Ground Advantage by Venue

In the previous blog I fitted models to the game margins of each team separately, seeking to explain the margin in any game in terms of the Venue at which the game was played and three "Excess" variables summarising from the designated home team's perspective its relative Venue Experience, MARS Rating and recent form.
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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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Does Crowd Size Affect Game Outcomes?

Based on empirical evidence we know that there is a home ground advantage in AFL which, in part, might be attributable to the pro-Home team leanings amongst the majority of the crowd. In this blog I want to explore a slightly different question about the effects of the crowd: specifically, does the size of the crowd matter too?
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Do Fans Really Want Close Games?

The AFL Draft is predicated on a belief that the equalisation of talent across teams across time is somehow good for the sport. It seems a reasonable premise, but how might we test it? Well, if it's true, one of the ways it should manifest is in attendance figures. Put simply: do games where the result is more uncertain draw larger crowds?
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