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Tag: AFL

2 Things Holding Back Quality Footy Writing and Analysis Analytics Among Fans and the Media (Part 2)

Posted in Analytics Landscape, and Opinion

This is a follow-up article to one I wrote last week about the state of analytics at AFL clubs. That article has been my most…

4 Things Stopping Analytics from Providing AFL Club Success (Part 1) A Look into the Role of Analytics in the AFL

Posted in Analytics Landscape, and Opinion

This post is¬†dedicated to my musings about the footy industry and the role of analytics both now and in the future. There won't be much…

2016 Round 1: Tips and Predictions Who's rated what?

Posted in Ratings, and Tipping

After almost 6 months of mindnumbingly football-free weekends, the 2016 season is set to get started this Thursday night at the MCG. Having recently unveiled my new team ranking model, FFSS, I now have a system by which to predict probabilities for upcoming matches.

I have translated my calculated probabilities into inferred match odds and compared these to the current prices offered by some of the bigger bookmakers around the country, highlighting any major discrepancies. The reason I have done this is not to recommend or even advocate having a bet on any particular team (although I will certainly talk about "good bets" and "value"). But it is rather used as a way to explore the strengths and weaknesses of the model in greater detail.

Bookie prices can be seen as a general "public consensus" about what the true probabilities of a team winning a match are. When the model differs greatly from the public view it is good to know why. Is it seeing something else that the public are not valuing? Or, as you'll see this week, is it missing entirely something that others are taking into account? If it's the latter, then there is clear improvement that can be made, if the former, then I guess we're on to a winner.

NOTE: All betting amounts will be discussed as unit bets assuming you have 100 units to play with as your full bankroll. For example if you have $10000 that you're willing to lose over the year if worst comes to worst, then 1 unit is $100. A higher unit bet shows more confidence in the models assessment and the value to be made. If you are interested in betting as a serious money building exercise, first I would question whether you really want to cope with the stress of the virtually guaranteed big losses you will experience week to week. If the answer to that is yes, then read as much as you can on Bankroll Management and the fractional Kelly Criterion. You are very likely betting too much to be sustainable.