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2016 Round 16 – Tips and Predictions

Posted in Tipping

Today’s article and the shortened week mean I haven’t had the time to write up a proper preview and possible value bets for this round. I’ll hopefully try and get something up by tomorrow.


No preamble about the general state of footy this week. But there is now some general discussion below on some potential value bets the FFSS model has flagged up this week.

My usual qualifiers about using model predictions for betting apply.1


FFSS Round 16 Predictions

Round 16 2016 FFSS RatingsThe graphic above highlights all of FFSS’s probability estimates for the week. The prices next to each team are the minimum suggested price to take if you were to bet on them to win the match, assuming that FFSS predictions are perfect. In reality this is, of course, very likely not so.

The graphic opposite shows the FFSS team ratings at the start of the round. These, along with a concession for Home Ground Advantage are the direct inputs for the final probability estimates.

Rather then write previews for every match of the week, I will instead comment on interesting discrepancies between bookie odds and FFSS odds, why these may exist, and whether there is any value in betting at the available price.

Geelong v Sydney

This was flagged up yesterday as being a potential value situation for Geelong. Following news of the inclusion of Mitch Clark, the market has corrected to be pretty much in line with the FFSS predictions. Whether you think this sort of movement based on the inclusion of one player (particularly a forward) is sensible or not is certainly up for debate.

Outside of that, with the odds the way they are, FFSS can’t in good faith recommend a bet either way. So there’s likely not much interest here outside of a cracking good game.

Melbourne v Fremantle

Bookies have Melbourne at around the $1.55-$1.59 range. This is likely where FFSS would put them as well, if this game were being played at the MCG.

Instead, the Dees have sold their HGA once again and the trip to Darwin really levels things up. The last time they did this was in Round 10 when they were beaten in an important match by Port Adelaide in Alice Springs and effectively lost touch with the 8.

Will we see more media debates this week about the “value” of a home game and whether struggling clubs should be so ready to sell them? Well the model still thinks the Dees will win, so maybe not. But I definitely think that Freo hold some value with a bookie implied win chance of 40%.

Bet 3 Units on Fremantle @ $2.50 – Sportsbet, Centrebet, William Hill…

West Coast v North Melbourne 

Well the North bandwagon has been well and truly emptied over the last month or so. When the public get off a team so hard and so quickly they often over-correct, and value bets may present themselves.

Whether this is one of those instances is probably up for debate. But the FFSS model has the Kangas at a 35% chance of causing an upset, while bookmakers will let you take an implied chance of about 31%. This difference, assuming the FFSS model is correct2, spells potential value.

Bet 2 Units on North Melbourne @ $3.25 – Luxbet


As it often does, FFSS thinks there may be some potential value to be had on other outsiders this week. Collingwood, Richmond and maybe even Brisbane and Essendon get flagged as value bets. It’s important to remember that these are all still pretty big outsiders. Looking at lines may be more beneficial in these cases, but I’m not going to recommend any bets on this for the time being.


  1. 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, is it missing something entirely 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. 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 $1000 that you’re willing to lose over the year if worst comes to worst, then 1 unit is $10. A higher unit bet shows more confidence in the models assessment and the value to be made.

  2. Which it almost certainly isn’t. It’s still a relatively dumb, “beta” model ignoring many bits of information.

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