Gather Round Tips and Head to Head Bets

Gather Round (Round 5) Tips

Adelaide v Carlton (57%, 7pts)

Fremantle (56%, 6pts) v Gold Coast

Richmond v Sydney (57%, 7pts)

Brisbane (79%, 33pts) v North Melbourne

Essendon v Melbourne (66%, 16 pts)

Port Adelaide (53%, 3pts) v Western Bulldogs 

Geelong (79%, 33pts) v West Coast

GWS v Hawthorn (50.0001%, 0.0006pts)

Collingwood (51%, 1pts) v St Kilda

Wow. A lot of these games are a lot closer than I would have initially predicted. Carlton and Fremantle are both worthy favourites although I would have thought both would be 5+% more confident.

Sydney being a 57% favourite over a depleted Richmond is massively under the odds for me. At first glance I had this in 60-65% Sydney range, I guess the loss to Port Adelaide did a lot of harm to their rating.

Collingwood also probably should be a little more favourites based on what we have seen this year but the model only knows a win or loss and by how much and St Kilda are 4-0 so there is evidence there to support them. You can only beat who you play and whether the Sainters have been rewarded for an easy schedule or not, they are undefeated and deserve some respect.

Suggested Bets for us to Gather (A)Round

Season performance so far: 0.00 bits, 28.94 MAE, 19/36 tips (53%), -1.8 units, -21.2% ROI

Essendon at $3.60 to beat Melbourne - 1 unit.

Western Bulldogs at $2.45 to beat Port Adelaide - 1 unit.

Hawthorn at $2.85 to beat GWS - 1 unit.

St Kilda at $2.75 to beat Collingwood - 1 unit.

After four rounds we now see some more confidence on display from the model with 4 units of bets being suggested for the weekend's games.

We are hoping for some underdogs to show out this week with all four teams being the lesser favoured of the pairing. We need a couple good results to make up for the -2 unit round four so good luck if playing and let's get some winners!

Comments

Post a Comment

Popular posts from this blog

Model Performance - Round 3

How Did the Model Perform? Round three threw up quite a few unexpected results, with somewhere between 4 and 5 underdogs getting the victory, depending on which source you use. For the PPP model  it was the best round so far to date in terms of tips and MAE with a -0.11 bit round being second only to round 1's -0.07 bits.  It is too easy to say this year has been unpredictable and not easy to model, the evidence for this however is in the Squiggle  model competition, with only four models in the net positive on bits. Having three straight rounds of negative bits does notr bode well for your model but so far in 2023 we can all be given a pass while the ratings and teams find their running order and settle down going into the first turn and back straight. If the betting markets are your preferred yardstick then we can safely say we have the bookies covered on MAE and bits, only being one behind on tips. For round three alone, the model tipped 5/9, lost 0.11 bits and had a M...
Read more

Model Performance - Round 1

How Did the Model Perform? Throughout 2023 I will be comparing my model to those in the Squiggle model competition with hopes of competing in it next year.  The Squiggle competition is a very well respected group of modellers who all predict the outcome of every match in the AFL season and then analyse their performance using various methods. In this post  I explained how these were but for those in need of a refresher we have bits (confidence based picks), MAE (the average of how many points you were wrong by) and just general tips (how many games did you pick the winner). On Squiggle the top models by bits are The Footycast  who leads the way with 0.79, Elo Predicts  who is second on 0.59 and AFLalytics  a close third on 0.58. My model finished round one in a would be 17th place with -0.07 bits. Not to worry, 23 rounds of AFL football to go. Looking at MAE now and we have  The Footycast   again in first with 27.13, The Cruncher in second with ...
Read more

AFL 2023 Season Preview

Image
2023 Initial Ratings and Model Explaination The 2023 footy season is upon us and it's time for wannabe modellers to break out their coding skills and put their brain and football knowledge to the test. I have refined and improved my previous models for sports like rugby, baseball and tennis to come up with what I believe to be an accurate and realistic model for the AFL season. My model works mainly from elo as its base rating system but includes variables like a fluid home ground advantage multiplier, expected score (or xScore) and previous head to head results to skew the probabilities one way or the other. The Elo Rating System Elo works on a couple main principles. Firstly is that it is a zero sum rating system, which means whatever points you add to one team you must take the same number of points away from the other team.  Secondly there is no "perfect" rating for each team as it is fluid and changes after every game.  For this reason two teams may play 10 matches a...
Read more