;)
Saturday, January 8, 2011 at 11:44AM In this blog I'll be reviewing the 2011 draw in terms of Venue Experience, a term that I defined and explored in an earlier blog. A team's Venue Experience for a given game is defined as the number of times that the team has played at that game's venue during the immediately preceding 12 calendar months, including finals.
Thursday, December 30, 2010 at 10:38AM In AFL, playing at home is a distinct advantage, albeit perhaps a little less of an advantage than it once was. So, around this time of year, I usually spend a few days agonising over the allocation of home team status for each game in the upcoming season.
Wednesday, November 24, 2010 at 8:15PM Last blog I identified a banker's dozen of algorithms that I thought were worthy of further consideration for Fund honours next season.
Experience has taught me that, behind the attractive veneer of some models with impressive historical ROIs often lurk troubling pathologies. One form of that pathology is exhibited by models with returns that come mostly from a handful of bets, one or two of them especially fortuitous. Another manifests as a 'bet large, bet often' approach that would subject any human on the business end of such wagering to the punting equivalent of a ride on The Big Dipper that's just as likely to end with you 100 metres above the ground as 200 metres below it. The question to be answered in this blog then is: do any of the 11 algorithms I've identified this time show any such characteristics?Wednesday, November 17, 2010 at 8:20PM To say that there's a 'bit in this blog' is like declaring the 100 year war 'a bit of a skirmish'.
I'll start by broadly explaining what I've done. In a previous blog I constructed 12 models, each attempting to predict the winner of an AFL game. The 12 models varied in two ways, firstly in terms of how the winning team was described ...Friday, October 29, 2010 at 8:16PM In conversation - and in interrogation, come to think of it - the key to getting a good answer is often in the framing of the question.
So too in statistical modelling, where one common method for asking a slightly different question of the data is to take the variables you have and transform them. Consider for example the following results for four binary logits, each built to provide an answer to the question 'Under what circumstances does the team with the higher MARS Rating tend to win?'.