In today's post I'll review the performance of all the teams that have been assessed as favourites by the TAB in games played during the period 2006 to the end of Round 17 in 2015, excluding only those games where the TAB bookmaker installed equal-favourites.Read More
Recently, I noted, somewhat in passing in this piece on close game and blowouts, the decline in overall team scoring, a topic that's receiving not a little attention within the football community at the moment, fuelled partly by some recent low-scoring games, in particular the Dees v Lions encounter.Read More
In the last blog on this part of the site I introduced the MoSSBOD Team Rating System, the defining characteristics of which were that it Rated teams based on Scoring Shot Production and Concession and that it provided both a Defensive and an Offensive Rating for all teams.
Today I want to explore the history of those Ratings across the last decade to see what MoSSBOD has to say about the strongest and weakest Offensive and Defensive teams across that period.Read More
The last few blogs here on the Statistical Analyses part of the website have used a model of team scoring that I fitted late last year to explore features of game scores and outcomes that we might expect to observe if that model is a reasonable approximation of reality.Read More
So far this season, eight teams have lost after generating more scoring shots than their opponents and three more have been defeated despite matching their opponent's scoring shot production, which means that the outcome of over 15% of games might this year have been reversed had the losing team kicked straighter.Read More
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
Discussions about the final finishing order of the 18 AFL teams are popular at the moment. In the past few weeks alone I've had an e-mail request for my latest prediction of the final ordering (which I don't have), a request to make regular updates during the season, a link to my earlier post on the teams' 2015 schedule strength turning up in a thread on the bigfooty site about the whole who-finishes-where debate, and a Twitter conversation about just how difficult it is, probabilistically speaking, to assign the correct ladder position to all 18 teams.Read More
The idea of ensemble learning and prediction intrigues me, which, I suppose, is why I've written about it so often here on MoS, for example here in introducing the Really Simple Margin Predictors, here in a more theoretical context, and, much earlier, here about creating an ensemble from different Head-to-Head predictors. The basic concept, which is that a combination of forecasters can outperform any single one of them, seems plausible yet remarkable. By taking nothing more than what we already have - a set of forecasts - we're somehow able to conjure empirical evidence for the cliche that "none of us is better than all of us" (at least some of the time).Read More