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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Are Some Games Harder to Predict Than Others?

If you've ever had to enter tips for an office competition where the the sole objective was to predict the winner of each game, you'll intuitively recognise that the winners of some games are inherently harder to predict than others.

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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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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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Modelling Team Scores as Weibull Distributions

A recent paper on arxiv provided a statistical motivation for that interpretation of the Pythagorean Expectation formula by showing that it can be derived if we consider the two teams' scores in a contest to be distributed as independent Weibull variables under certain assumptions.

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Team Scoring Shots and Conversion Rates

In response to my earlier post on the explained and unexplained portions of game margins, Friend of MatterOfStats, Michael, e-mailed me to suggest that variability in teams' points-scoring per scoring shot - or, equivalently, teams' conversion rates - might usefully be explored as a source of unexplained variability. 

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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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Really Simple Margin Predictors : 2013 Review

MAFL's two new Margin Predictors for 2013, RSMP_Simple and RSMP_Weighted, finished the season ranked 1 and 2 with mean absolute prediction errors (MAPEs) under 27 points per game. Historically, I've considered any Predictor I've created as doing exceptionally well if it's achieved a MAPE of 30 points per game or less in post-sample, live competition. An MAPE of 27 is in a whole other league.
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Game Statistics and Game Outcomes

My first Matter of Stats blog looked at how game statistics, averaged across an entire season for each team, are predictive of key season outcomes like ladder position, competition points and MARS Ratings. This post summarises similar analyses, but here performed on a per-game basis
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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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Team Scores - Statistical Distribution and Dependence

In the most recent post on the Simulations blog I assumed that Home Team and Away Team scores were independently and Normally distributed (about their conditional means). I'll investigate both these assumptions in this blog.
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The Increased Importance of Predicting Away Team Scores

In an earlier blog we found that the score of the Home team carried more information about the final game margin than did the score of the Away team. One way of interpreting this fact is that, given the choice between improving your prediction of the Home team score or your prediction of the Away team score, you should opt for the former if your goal is to predict the final game margin. While that's true, it turns out that it's less true now than it once was.
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What's Easier - Predicting the Home or the Away Team Score?

Consider the following scenario. You're offered a bet in which you can choose to predict the final score of the Home or of the Away team and your adversary is then required to predict the final score of the other team.
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Line Betting : A Codicil

While contemplating the result from an earlier blog, which was that home teams had higher handicap-adjusted margins and won at a rate significantly higher than 50% on line betting - virtually regardless of the start they were giving or receiving - I wondered if the source of this anomaly might be that the bookie gives home teams a slightly better deal in setting line margins.
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Predicting Head-to-Head Market Prices

In earlier blogs I've claimed that there's not much additional information in bookie prices that's useful for predicting victory margins than what can be derived from a statistical analysis of recent results and an understanding of game venues.
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