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.

Read More

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.

Read More

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.

Read More

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).

Read More

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.

Read More

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.

Read More

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. 

Read More

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.

Read More

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.
Read More

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
Read More

How Many Quarters Will the Home Team Win?

/
In this last of a series of posts on creating estimates for teams' chances of winning portions of an AFL game I'll be comparing a statistical model of the Home Team's probability of winning 0, 1, 2, 3 or all 4 quarters with the heuristically-derived model used in the most-recent post.
Read More

The Changing Nature of Home Team Probability

/
The original motivation for this blog was to provide additional context for the previous blog on victory probabilities for portions of games. That blog looked at the relationship between the TAB Bookmaker's pre-game assessment of the Home team's chances and the subsequent success or otherwise of the Home team in portions - Quarters, Halfs and so on - of the game under review.
Read More