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AFLW 2024 - Round 8 - Chat, game threads, injury lists, team lineups and more.
What I mean is, if you can middle say -27.5 somewhere and +28.5 somewhere else, what do the effective odds have to be before it's value, generally?
Calculating this requires constructing your own push charts. You can even retrofit a vig free push chart of line value from a sportsbook's alternative line market. Take an average from 2-3 though, because some books are off.
However it is better to do it clean yourself, if you have the match data, it'd take you less than an hour with some programming ability. With none (I did this a few years ago), it takes about half a day in excel.
brett128 one more question for you, if you have a moment... if you're pricing up all margin possibilities, how far out do you price? Say you predict Hawthorn will beat GWS by 85 points, then 85 is your most likely margin, and each point either side is the next likely, and so on... where do you draw the line? 90 points either side of your predicted margin? 120 points? 180??
You'd need to know the market line in the match though, wouldn't you?
You really need to understand how the Gaussian distribution works.
Many natural physical processes (including football) conform to this distribution. If you have a standard deviation (sigma) and a mean (mu) of the margin of victory, you can construct a simple formula to price any > or < points line.
http://en.wikipedia.org/wiki/Gaussian_distribution
http://en.wikipedia.org/wiki/File:Standard_deviation_diagram.svg
Google "push chart" or "NFL push chart". I found a few articles and went from there. The reason why you input 'NFL' is because American sources of info for doing this type of thing are all over the web.
Yeah I get the Gaussian distribution... I just don't calculate it based on standard deviations. Being of racing background I don't believe stdev's for Gaussian distributions work well enough.
I assume those links will say you price out to three standard deviations?
I don't like copying charts and things though, I like to work them out for myself. It's the give a man a fish, teach him to fish thing.
I've discussed this before with my syndicate partners, the old fella in our group somewhat takes your stance. He says reality is a funny thing and that sigmas and standard deviations don't properly conform to what is actually happening.
I tell him if it doesn't conform to the Gaussian distribution, then it's another distribution.
That's not the point of what i'm trying to say. I'm trying to say you can calculate this easily for any points line given the right formula.
You can tell your old fella (so to speak) that I'm with him. They don't. And I've proven it in my own racing research... this is why I am reticent when stepping into the world of you quants (so to speak ).
OK, I'll re-read.
The final distribution essentially looked like something to be derived from a power law. It had a massive left skewed spike, and then an extremely long tail.
I've done some work for a horse racing professional not too recently ago. I looked at 1.5M runners in UK racing over many years of data. He wanted to find the right conversion approach of win odds to place odds. You have flawed methods like the Harville formula, etc. So I decided to empirically derive an equation through plotting a distribution.
The final distribution essentially looked like something to be derived from a power law. It had a massive left skewed spike, and then an extremely long tail. Funnily enough, the distribution looked almost identical to an article I read on the relationship of the magnitude of earthquakes to the magnitude of aftershocks. Reality works in strange ways.
In the end I created a better place formula, but it still wasn't 'smooth' enough to create a tight 300% place market, we needed to slightly compress/expand to fit it properly where there was either small or large fields.
I've done some work for a horse racing professional not too recently ago. I looked at 1.5M runners in UK racing over many years of data. He wanted to find the right conversion approach of win odds to place odds. You have flawed methods like the Harville formula, etc. So I decided to empirically derive an equation through plotting a distribution.
Sounds like a lognormal.
hawks line -42.5, $600 at 1.943 pinnacle
gws line +80.5, 1075 at 2.01 pinnacle
gws line +80.5, 200 at 1.962 pinnacle
rich line -28.5 230 at 1.909
this total 2105
Total for round: $6065
Yeah much better looking outlays. I think you're still over betting by not properly adjusting for simultaneous Kelly.
These essays are an excellent reference, Dr Bob's been in the game for a while, his edge is eroding (hasn't been profitable on the NFL for years) but still one of the better cappers out there:
http://www.drbobsports.com/essays.cfm?cat=0
and read about simultaneous Kelly.
Thanks for that. Remember though,I'm using a static 10k BR, which negates the simultaneous play problem.
Last night's game... Had swans to win by 34. On your model, what price would you have the swans to cover an 18.5 point line, if you had them as winning by 34?
No it doesn't.
That's too far dude. Lines are only very rarely that wrong. A 15-16 point difference vs the spread implies a win % going into mid 60's% in AFL. Either increase your Kelly fraction or re-work your model.
That's too far dude. Lines are only very rarely that wrong. A 15-16 point difference vs the spread implies a win % going into mid 60's% in AFL. Either increase your Kelly fraction or re-work your model.