Last week I went through the rather complex calculations of working out an Archie Score and how this can be done to help us determine our bank size. If you managed to get your head around that then well done because it took me several months ðŸ˜€

If you missed that mathematical delight then you can find it here.

So onto today then and we need to move onto how we use the Archie Score to help us calculate our EXACT bank size. Well it’s more about knowing that our system or selection process will continue to perform successfully. It’s all very well having a process that has shown a profit over the last month but do we know that success will continue? That’s where the Archie Score comes into it’s own. It effectively predicts whether our previous selections have been down to skill or chance.

I’ve out-lined a table below that will explain how the increasing number produced by your Archie calculation will reduce the likelihood of your selections being based on “luck.”

As you can see the higher the Archie score the less the selection process is down to just chance or “luck.”

So how do we use this, combined with last weeks understanding of the process, work out the exact bank that we need. Looking back at last weeks example which I’ve laid out below I’ll go onto explain the process.

There are three calculations we need to do before calculating the eventual Archie score. Firstly the number of bets. Thatâ€™s easy we just count them but letâ€™s assume weâ€™ve got 100. Secondly we need to count how many winners weâ€™ve had. Again easy as we can just count these. Letâ€™s say weâ€™ve got 30 winners for a strike rate of 30%.

The third calculation requires a little more work as we need to find the expected amount of winners. This is done by finding the average prices of ALL our selections. We simply add all the odds together and divide them by the number of bets that we have. Now the example below is very simple and of course you wouldnâ€™t get 100 3/1 shots but for the purposes of explaining this it will have to do!

Convert your odds into decimals (3 divided by 1 = 3 + 1 = 4) and then add them all up. In this case itâ€™s of course 400. You then divide it by the number of bets. In this rather simple example it is of course 3/1 as the average odds. It will of course be different when doing a real example.

We then divide 1 by the average odds to arrive at a percentage. So in this case 1/4 = 0.25 multiplied by 100 = 25% or from a 100 bets we would expect 25 winners.

So we have a result set of the following:

Number of bets: 100

Number of winners: 30

Expected winners: 25

Now for the complicated bit:

Number of bets(100) x (Winners(30) â€“ Expected Winners(25)) 2

Archie = â€”â€”â€”â€”â€”â€”â€”â€”â€”â€”â€”â€”â€”â€”â€”â€”â€”â€”â€”â€”â€”â€”â€”â€”â€“

Expected Winners(25) x (Number Of Bets(100) â€“ Expected Winners(25)

So we have 30 â€“ 25 = 5 x 5 (squared) = 25 x 100 = 2,500

100 â€“ 25 = 75 x 25 = 1,875

So 2,500 divided by 1,875 = 1.333333

With the above example we would need to have more selections as the Archie score is too low and we know that there is still a 25% to 30% chance that we’ve just been lucky. However if the selection process continues to perform as it has and we now have 1000 selections with 300 winners and 250 expected winners then we would have an Archie Score of 13.33 which is excellent.

With this we now know that because the process is purely based on skill and NOT luck that we can use our expected winner calculation and combine this with our strike rate. Going back to an article I wrote back in February looking into How to Create a Betting Bank and Keep it All I went into calculating betting banks using our strike rate. Using this article and to save me having to write it all again we know that (you can click the link above to go to the article) with a 30% strike rate over a 1000 sample set we would expect 19.36 losers in a row or rounded up 20 losers. We know that with our Archie Score being high that this will be an accurate calculation but we can go one step further. We use the same formula in the above article and use our expected winners calculation.

This would now be 24.01 losers in a row or just 24 to be exact. By averaging the two of 20 and 24 we get 22. So by using the trusted multiply by three to protect us against the losing run we end up with a bank of 66 units. Divide this into the bank you have, for example Â£1000 and you would get Â£15 bets per selection. You could rest in the safe knowledge that you have absolutely safe guarded your bank and can keep betting and growing your bank.

That’s it for this week, if you have any questions then please let me know and I’ll answer you back in the comments below.

I’ll be back next week with more betting knowledge but until then enjoy the punting!

Eddie

VATR

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