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#21
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Strange, an ancient systematic approach from the UK was to target the Favs in the 1st 3rd and last races. Looking at Chromes' list maybe there's some thought behind it after all.
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#22
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To address Mark's observations,
I don't think many will take advantage or for that matter should take advantage as they are only raw stats. The picture changes somewhat when adjusting for certain other reasons. For example, field sizes, and jumps races are often the first race in winter. Class races are usually later as well, so more often open events price wise. Note the win %, place % and POT all decrease accordingly, not denoting overbet horses, but denoting average field size. In general, increase in average field size relates to increase in average price, so naturally the loss percentage will increase. Due to the favourite longshot bias, the longer the favourite price, the more percentage you lose. The shorter the price of the favourite, the less percentage you lose. These are general comments only, obviously there are specific differences, but I certainly wouldn't be rushing out to back the favourite in a maiden in field size of 4, when I can bet on a good horse with good form in a Group One race in a field of 4, that just happens to be race 7. Just my thoughts.
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#23
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Agree 100% CP.
I take note of those stats and I also use short-term stats. eg yesterday on Syd, Melb, Gold Coast races up to race 6 there had been 7 favs & 10 in-the-market winners, this told me that some "bolters" were overdue and so I laid accordingly. Races 7 & 8 at those meetings were won by 1 fav and 5 good priced winners....thank you. Of course it's not alwasy that simple but it helps to know roughly where you're at. |
#24
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Quote:
Just seems like yesterday (2003 or around that time when I raised this same issue, fast forward a decade and here we are again). First up, most this isn't really going to be helpful for the "backfitters" here as most continually mix Strike rate and ROI together. Remember Strike Rate only applies to Handicapping/Rating and ROI applies to Wagering. It's not too hard to develop a list of variables or a combination as all have been listed here previously in database threads and just putting on your "joe public thinking cap" instead of the computer handicapper cap, you should be able to develop your list. To know how the crowd looks at all handicapping variables, you have to test each one and then see which one or combination they use or the ones they don't use. To do that you need to build a generic , single factor simulator that can give you probabilities studies for each factor. All you will do once you have run a test is to determine the relationship between each factor and the crowd odds (not strike rate, not ROI just plain simple ODDS) Using a simple application of multivariate analysis will do this easy. A simple test is to use the above to determine a set of "win" probabilities and then plot them against the actual post time odds in a scatter diagram, all you do then is to use Correlation Analysis and Correlation Coefficient and you will be on the road to success. Just remember. for crowd "measures" accurate means close to actual odds , not observed finish percentages |
#25
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Everyone does that already .
It works good They are called Bookies. They make a living out of it. But can you pick a little vinner.
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#26
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Quote:
Woof, I understand everything your saying above except for one point and thats my fault because I just can't get my head out of the sand. Happy to discuss in email if you don't want to post it here. You can email me at betfinder@exemail.com.au The part I am missing is how does this help us profit. Lets say we take barrier position and we find that it has some correlation to the win odds. (I haven't tested just picked a variable at random). How does this help us when analysing the race ? Lets assume we find the correctation is X*1.222222 (made up) which means barrier 1 has avg odds of 1.22, barrier 2 has avg odds of 2.44, etc. How do we use this information to profit ? Do we now disregard this variable because we know the public uses it ? Or do we somehow put this information to our own use for laying/betting. |
#27
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Once you have tested and found all the variables that work to some degree, that is the odds step down smoothly, you start to then categorize the favourites. This where you earn your money, there are infinite ways of doing this, i'll leave this up to you, but do a lot of thinking, success depends on how well you can learn to categorize races.
Your next step is to then go back thru your historical database for races that match each categorization. Then from your actual observations (statistically speaking), you then develop a probabilty matrix for every runner in each race or down as far as you can. Should'nt be too hard to work out where it is all going now. Obviously the categorizing is the key. pick a bad category you botch the race, but fortunately there is a fair amount of "forgiveness", but once you study this a little and eliminate the obvious bad way of doing things, it's not too hard. I remember in the late 90's this type of categorizing was being developed where they had limited set "probability" tables but now with super computers set ups such as in HK, can develop far more complex catergory models and then "on the fly" search thru your database spaces searching for exact matches. Something to think about |
#28
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I'm at a bit of a loss also.
There are so many variations, and subsets that surely you'd need an infinite and changing matrix.
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#29
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Seeing that the 1st & 2nd fav win 50% of all races .
My dont you just separate them using all that stuff . Bingo 50% winners. One will be a millionaire by lunch time next week.
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#30
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And Leon's getting LARRRGGGGER
I can't remember what happened in The Matrix but I remember Flying High. |
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