Can We Use Head-to-Head Market Movements in the Line Market?

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Yesterday's post led to an interesting Twitter thread last evening, which included a suggestion to reanalyse the data to determine whether price movements in the Pinnacle head-to-head market might have predictive value in other markets for the same game, specifically in the line market.

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Is There a Signal in Head-to-Head Market Movements?

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Watching the TAB markets as they've shifted across the course of a week I've often wondered if there might be something predictive in those movements. If the eventual favourite's price has shortened during the week, does it win more or less often than its closing price would suggest?

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

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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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Modelling Team Scores as Weibull Distributions : Part II

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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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The Responsiveness of Bookmaker Prices To Winning and Losing

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In this blog I'm seeking to answer a single question: how are a team's subsequent head-to-head bookmaker prices affected by the returns they've provided to head-to-head wagering on them in recent weeks? More succinctly, how much less can you expect to make wagering on recent winners and how much more on recent losers?

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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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Team Scoring Shots and Conversion Rates

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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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Really Simple Margin Predictors : 2013 Review

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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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The Relative Importance of Class and Form in AFL

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Today's blog is motivated by a number of things, the first of which is alluded to in the title: the quantitative exploration of the contributions that teams' underlying class or skill plays in their success in a given game relative to their more recent, more ephemeral form. Is, for example, a top-rated team that's been a little out of form recently more or less likely to beat a less-credentialled team that's been in exceptional form?
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Bookmaker Overround: A General Framework

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Previously I've developed the notion of taking a Bookmaker's prices in the head-to-head market and using them to infer his opinion about the true victory probabilities of the competing teams by adopting an Overround-Equalising or a Risk-Equalising approach. In this blog I'll be summarising and generalising these approaches.
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Team Ratings, Bookmaker Prices and the Recent Predictability of Finals

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Last weekend saw three of four underdogs prevail in the first week of the Finals. Based on the data I have, you'd need to go back to 2006 to find a more surprising Week 1 of the Finals and, as highlighted in the previous blog, no matter how far you went back you wouldn't find a bigger upset than Port Adelaide's defeat of the Pies.
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The Predictability of Game Margins

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In a recent blog post I described how the results of games in 2013 have been more predictable than game results from previous seasons in the sense that the final victory margins have been, on average, closer to what you'd have expected them to be based on a reasonably constructed predictive model. In short, teams have this year won by margins closer to what an informed observer, like a Bookmaker, would have expected.
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The Predictability of 2013

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Friend of MAFL, Michael, e-mailed me earlier to ask about my claim that 2013 was on track to be the most predictable MAFL season ever, pointing out, quite correctly, that bookmaker favourites have been winning at about the same rate - perhaps even at a slightly higher rate - as they had been at the same time last year.
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Team Scores - Statistical Distribution and Dependence

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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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Estimating Fair Head-to-Head Prices : Part I

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You'll recall that the total overround embedded in the head-to-head market, ignoring the possibility of a draw, is calculated by summing the reciprocal of the head-to-head prices for each team. So, for example, if the head-to-head prices for a game were $1.20 / $4.60, the overround would be 1/1.2 + 1/4.6, which is 105.1%. Some subtract 1 from this figure and would report this overround as 5.1%.
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Finding Non-Linear Relationships Between AFL Variables : Alternative Measures to MIC

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The Maximal Information Coefficient (MIC) that we explored in the previous blog is not the only non-linear measure of the pairwise relationship between any two continuous variables.
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