If You Can't Get Better, Get More Unpredictable
/For the weaker team in any contest which rewards only victory (or at least does so disproportionately to the rewards for proximity to victory), variability can be an advantage.
Read MoreFor the weaker team in any contest which rewards only victory (or at least does so disproportionately to the rewards for proximity to victory), variability can be an advantage.
Read MoreMonash University has been running AFL tipping competitions for over 20 years and this year is offering three, all of which are open to the public.
Read MoreAccurate kicking, obviously, contributes to a team's success. But, just how much does it contribute, what are some of the sources of its variability, and just how predictable is it?
Read MoreDiscussions 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 MoreThe 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 MoreFans the world over, the literature shows, like a little uncertainty in their sports. AFL fans are no different, as I recounted in a 2012 blog entitled Do Fans Really Want Close Games? in which I described regressions showing that crowds were larger at games where the level of expected surprisal or 'entropy' was higher.
Read MoreI've often heard it asserted after a team's close loss that it will "bounce back harder next week". With a little work, that's a testable claim.
Read MoreThe themes in this blog have been bouncing around in my thoughts - in virtual and in unpublished blog form - for quite a while now. My formal qualifications are as an Econometrician but many of the models that I find myself using in MoS come from the more recent (though still surprisingly old) Machine Learning (ML) discipline, which I'd characterise as being more concerned with the predictive ability of a model than with its theoretical pedigree. (Breiman wrote a wonderful piece on this topic, entitled Statistical Modelling: The Two Cultures, back in 2005.)
Read MoreSimple question: which of MoS' 17 Margin Predictors has been best-performed over the past two seasons?
Read MoreI've addressed the topic of fitting a team's winning rate as a function of its scoring behaviour before on MoS, in discussions about Win Production Functions generally and in posts about Pythagorean Expectation specifically.
Read MoreThe AFL draw remains imbalanced, with teams meeting only five of their 17 potential opponents twice, and meeting the other 12 teams only once.
Read MoreFinals series are a significant part of Australian sporting life. No professional team sport I know determines its ultimate victor - as does, say the English Premier League - on the basis of a first-past-the-post system. There's no doubt that a series of Finals adds interest, excitement and theatre (and revenue) to a season, but, in the case of VFL/AFL at least, how often does it result in the best team being awarded the Flag?
Read MoreThis year, Sydney collected its 8th Minor Premiership (including its record when playing as South Melbourne) drawing it level with Richmond in 7th place on the all-time list. That list is headed by Collingwood, whose 19 Minor Premierships have come from from the 118 seasons, one season more than Sydney/South Melbourne and 11 more than Richmond.
Read MoreMuch has already been written about the lamentable and historic-for-all-the-wrong-reasons 2014 Grand Final, which got me to wondering about exactly how atypical it was. Have there been similar Grand Finals and, if so, when?
Read MoreI was updating the MAFL Fund Performance page last evening and found myself pondering the topic of bookmaker overround.
Read MoreThe Sydney Swans were deserved pre-game favourites on Saturday according to most pundits (but not all - congratulations to Robert and Craig for tipping the winners). At some point during the course of their record-breaking loss that favouritism was handed to the Hawks. In this blog we'll investigate when.
Read MoreOnly three teams in VFL/AFL history have trailed by more than three goals at Quarter Time in the Grand Final and gone on to win. The most recent was Sydney in 2012 who trailled the Hawks by 19 at the first break before rallying in the second term to kick 6.0 to 0.1, eventually going on to win by 10 points, and before that Essendon who in 1984 trailed the Hawks by 21 points at Quarter Time - and still trailed them by 23 points at Three Quarter Time - before recording a 24 point victory on the strength of a 9.6 to 2.1 points avalanche in the final term.
Read MoreAlmost two years ago, in a post-GF funk, I recall painstakingly cutting-and-pasting the scoring progression from the afltables site for 100 randomly-selected games from 2012. I used that data to search for evidence of in-game momentum, there characterising it as the tendency for a team that's just scored to be the team that's more likely to score next.
Read MoreIn 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 MoreMAFL is a website for ...