I have been preoccupied with more important business this week, so unfortunately there won’t be much of discussion about this week’s matches Instead I’ll just…
Week 1 proved to be a very successful round of tipping for the FFSS (Figuring Footy Scoring Shots) predictor. 8 out of 9 games were tipped correctly, and if you followed through on my recommended bets you would have netted yourself a tidy little profit of +13.02 Units (which would be about $130 if you started with a total bankroll of $1000). However, I also wrote this week about grounding our expectations in reality, and why last week’s results may have been a bit lucky.
This week poses us a fresh new challenge. As has been discussed a fair bit on Twitter, last round saw every home team get up. With the way the AFL draw is organised in the early rounds, this means that every single one of Round 1’s winners, goes into Round 2 as the away team. This means that each of them will face a handicapping by FFSS’s Home Ground Advantage calculator. HGA takes into account distance travelled by each team, ground experience by each team and the AFL designated home team (for games that are played at shared stadiums). This week, HGA varies between ~7 ratings points for Essendon at the G against Melbourne and ~110 ratings points for Freo at home to the Suns.1
My new computer predictor algorithm FFSS (Figuring Footy Scoring Shots) fared pretty admirably in her first week of tipping, nailing 8 out of 9 possible results. Only a bit of Dangerfield-inspired magic late on Monday afternoon prevented a perfect start to the season.
Anybody who has read this blog before will know that before the upcoming round I publish expected win probabilities for each match to be played. These probabilities are calculated by looking at the FFSS ratings of both teams and accounting for the venue. For example, I gave Sydney a 75% chance of beating Collingwood at home. They of course went on to thump them by 80 points. So then, if Sydney were so good, why didn’t the model rate them even higher and know ahead of time that they would dispatch Collingwood with ease?
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.