Thank you very much,very helpful. So , if i understand correctly, it's quite impossible to have such a strike rate with just plain luck. it is like 0,0004 % of chanches.
Edit : for my specific case it s a bit more 0.02%, still relevant
There has to be more in here
False edge? Am i fooled by variance?
"There is such a thing as 'the law of big numbers'.
It means that the more times the same event is repeated, the more actual results stochastically converge on expected results.
Imagine a fair coin toss. The law of large numbers predicts that after 10,000 iterations (plays of the same event) actual results are more likely to have heads coming up 50% of the time than after 100 iterations.
The problem is that in sports you don't get the same idealized event replayed countless times. In fact each event is individual--player injuries, good or bad form etc., circumstances of the match, confidence or mood etc. " askari1
https://en.wikipedia.org/wiki/Law_of_large_numbers
"There are 2 kinds of people on BF. Those who bet based on what they anticipate the result to be, and those who bet against what other people anticipate the result to be. " pxb
I thought stochastically may have been a misspelling but no it is an actual word.
It means that the more times the same event is repeated, the more actual results stochastically converge on expected results.
Imagine a fair coin toss. The law of large numbers predicts that after 10,000 iterations (plays of the same event) actual results are more likely to have heads coming up 50% of the time than after 100 iterations.
The problem is that in sports you don't get the same idealized event replayed countless times. In fact each event is individual--player injuries, good or bad form etc., circumstances of the match, confidence or mood etc. " askari1
https://en.wikipedia.org/wiki/Law_of_large_numbers
"There are 2 kinds of people on BF. Those who bet based on what they anticipate the result to be, and those who bet against what other people anticipate the result to be. " pxb
I thought stochastically may have been a misspelling but no it is an actual word.
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ShaunWhite
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When you don't have a big enough sample to use Emmson's advice you can also look at Central Limit Theorem to see if your sample typical of what's expected. It's essentially the distribution of your results, the simplest being a histogram of your PLs. It's a way to try to see if you're currently winning or losing due to outliers or due to short term randomness.
It's tricky creating an example but your results distribution (the number of times you lost 0-5 or won 0-5, 6-10, 11-16 etc) should start to form a bell curve especially if you squint your eyes a bit, any notable gaps or peak 'could' mean you're due some in that region. But this is where LLN and CLT start to sound like they support the Gambler's Falacy but it doesn't. Prior results have no influence, the universe doesn't 'know' you're due a £50 win, but with a big enough sample you'll win as often as normalised distribution says you will.
Here's the rough 2min example, any band especially far from the distribution or way out at either end could mean your current sample isn't typical yet. Stats aren't really about yes or no they still need to be interpretted though.
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ShaunWhite
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I don't like posting anything that's wrong so i checked...#1 is quite funny.
...and it re-wrote it for us. I might get it to do all my posts, it's faster than I am
When your sample size isn't large, you might still consider the Central Limit Theorem (CLT) to understand if your sample is representative of what's expected. The CLT deals with the distribution of sample means — for example, you might look at a histogram of your data points. This can help you determine if current variations are due to outliers or just short-term randomness.
Creating a sample distribution (the frequency of certain ranges of wins and losses) should reveal a pattern that resembles a bell curve, albeit not perfectly. Notable deviations from this pattern could indicate unusual results, but remember, this is not an endorsement of the Gambler's Fallacy. Prior results don't affect future outcomes; the universe doesn't compensate for past losses or wins. However, over a large number of trials, the Law of Large Numbers (LLN) assures that your results will align with the expected probability distribution.
Please note that a large enough sample size is crucial for the CLT to be applicable, and in practice, 'large enough' can vary depending on the actual distribution of your data.
...and it re-wrote it for us. I might get it to do all my posts, it's faster than I am
When your sample size isn't large, you might still consider the Central Limit Theorem (CLT) to understand if your sample is representative of what's expected. The CLT deals with the distribution of sample means — for example, you might look at a histogram of your data points. This can help you determine if current variations are due to outliers or just short-term randomness.
Creating a sample distribution (the frequency of certain ranges of wins and losses) should reveal a pattern that resembles a bell curve, albeit not perfectly. Notable deviations from this pattern could indicate unusual results, but remember, this is not an endorsement of the Gambler's Fallacy. Prior results don't affect future outcomes; the universe doesn't compensate for past losses or wins. However, over a large number of trials, the Law of Large Numbers (LLN) assures that your results will align with the expected probability distribution.
Please note that a large enough sample size is crucial for the CLT to be applicable, and in practice, 'large enough' can vary depending on the actual distribution of your data.
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Little of what I posted is mine (Only the sto·chas·tic sentence) look closely and see the quotation marks, I even named the sources
This is where I pulled it from
https://community.betfair.com/general_b ... f-averages
it just caught my eye and that is why I brung it here
This is where I pulled it from
https://community.betfair.com/general_b ... f-averages
it just caught my eye and that is why I brung it here
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ShaunWhite
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- Joined: Sat Sep 03, 2016 3:42 am
I need a life... 
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ShaunWhite
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Absolutely but in the same vein as RT's are not endorsements on another platform I brung it here.
Question regarding this video https://youtu.be/z5fyLqVCqjE?si=ngHES8WJV9xvFogx
towards the end 10:26 "If I have a profitable Backing strategy when the market is favourable for laying strategies then you really have something special."
I want to know/confirm if I have a profitable strategy.
Total Number of Markets with bets = 2097
Total Number of Profitable Markets = 1433
My winning Strike Rate (selections losing the race) = 68.3%
My average Lay entry = 3.738 (26.7% implied odds)
The Average BSP of my selections is = 3.754 (26.6% implied odds)
From this data what do I compare to confirm I have or have not got a winning edge? How do I know if the market is favourable for Backing/Laying Strategies?
towards the end 10:26 "If I have a profitable Backing strategy when the market is favourable for laying strategies then you really have something special."
I want to know/confirm if I have a profitable strategy.
Total Number of Markets with bets = 2097
Total Number of Profitable Markets = 1433
My winning Strike Rate (selections losing the race) = 68.3%
My average Lay entry = 3.738 (26.7% implied odds)
The Average BSP of my selections is = 3.754 (26.6% implied odds)
From this data what do I compare to confirm I have or have not got a winning edge? How do I know if the market is favourable for Backing/Laying Strategies?