There is one analytical metric which was not discussed in the analysis of results article - the system’s Strike Rate.
The reason for its omission is that, such is its importance, it is deserving of its own article.
Although the Strike Rate of a selection system is not the be-all-and-end-all, ignore it at your peril. We’ll see why later.
The Strike Rate of a selection system is usually expressed as a percentage.
To calculate it, the number of winning bets is divided by the total number of bets made. The result is then multiplied by 100 to convert it to a percentage.
By way of an example, let us suppose that a laying system selects 100 horses and 80 of them lose. The strike rate is given by: 100 x (80)/100 = 80%.
Likewise, if a backing system selects 100 horses and 20 of them win. The strike rate is given by: 100 x 20/100 = 20%.
We now know what the strike rate of a selection system is and how to calculate it, but, how do we use it?
Firstly, together with the average odds of the losing bets, the strike rate can be used to determine whether or not a selection system is profitable.
This is more fully discussed in a future article.
Secondly, the strike rate can be used to determine the maximum number of consecutive losing bets that the system is likely to encounter.
This, in turn, can be used to determine what percentage of the betting bank it is reasonable to risk on each selection. This is more fully discussed in a future article also.
Earlier it was stated that the strike rate of a system is not the be all and end all.
Here are two examples which illustrate this point: In each example, all of the selections were layed to a stake of £1 and 5% commission was paid on each winning bet.
When we compare the results for system 1 with those for system 2, we see that although the strike rate of both systems is identical and equal to 80%, their profitabilities are very different.
In the case of system 1, the profit was £3.60 whereas system 2 made a loss of £0.40.
What this shows is that the strike rate of a system, alone, has no bearing on the profitability of a system.
Now let’s look at two further examples where, again, all of the selections were layed to a stake of £1 and 5% commission was paid on each winning bet.
If we compare the results for system 3 with those for system 4, we see that although the strike rate of system 3 (70%) is less that of system 4 (80%), system 3 made a profit of £0.65 whilst system 4 made a loss of £0.40.
What this shows is that the system with the highest strike rate may not, necessarily, be more profitable than a system with a lower strike rate.
This is more fully discussed in a future article.
One last thing before I end this article: I was always puzzled as to what factors determine a selection system’s long-term strike rate. After much research, I finally identified the factors, or, more accurately, the factor.
At this stage, I must confess that I felt more than a little foolish because the factor had been staring me in the face all along. It was both strange and frustrating that it took me so long to identify it.
Still, such is life.
So, what factor determines the long-term strike rate of a selection system?
The average odds of the selections that are generated by the system.
For example, if a system has generated 100 selections in the past and the sum of the odds of those selections is 400/1, then the average odds of a selection is400/100 = 4/1. Now, odds of 4/1 means that the selection has 4 chances of losing and 1 chance of winning. Therefore, the total number of chances is 4 + 1 = 5.
So, our selection actually has 1 chance of winning in 5 chances in total.
So, in decimal terms, the horse has 1/5 chances of winning.
To convert this to a percentage chance of winning, we multiply by 100.
So, 100 x 1/5 = 20%.
If the average odds of the selections generated by a backing system is 4/1, the long-term strike rate will be in the region of 100 x 1/(1 + 4) = 100/5 = 20%.
To calculate the strike rate of a laying system that generates selections whose average odds are 4/1, perform the above calculation and subtract the result from 100. So, 100 x 1/5 = 20. 100 - 20 = 80.
Therefore, if a laying system generates selections whose average odds are 4/1, the long-term strike rate will be in the region of 80%.
It should be noted that the larger the number of bets, the more accurate will be the average odds of a selection generated by the system and the more accurate will be the resulting estimated long-term strike rate.
The accuracy of estimates is more fully discussed in a future article.
What I have also noticed is that systems are subject to fluctuations.
These fluctuations consist of varying runs of winning and losing bets.
The fluctuations are quite normal and are due to random variations in the results.
These fluctuations can cause the strike rate of a system to differ from the expected long-term strike rate.
Therefore, when the strike rate of a system is measured, it may not necessarily be equal to the expected long-term strike rate.
Although the strike rate of a system will, eventually, return to its normal value (i.e. the estimated long-term strike rate) it is impossible to calculate when this will occur.
In this article, we discussed the strike rate of a system and how to calculate it.
We also showed that two systems with the same strike rate may have vastly different profitabilities and that the system with the highest strike rate may not necessarily be the most profitable.
We also discussed what causes a system to have the long-term strike rate that it does and also how to calculate it.