Micro-Angles A Quick Look At How They Work Part II
We've published a lot about how we trade, staking and various selections that we've bet on. I thought it was time that we showed you guys how we came up with some of our selections, how we trade/bet them and what we do with them.
Over the course of around four articles, we'll be looking at all the lowdown! The first article was published, last week.
But, the first thing that we need to do, is to define how we want to bet?
If it's straight-up betting, then these articles are for you!
If it's trading, then it's still worth a read, but there are many more “criteria” that we need to analyze. That will be covered in articles in the future.
In terms of betting, we need to find angles that give us an edge. Now, this is something that everyone is capable of!
Moving on from the last article, we need to look at how “back-fitting” can completely cock up a system that looks to have merit!
You'll remember that we were using a system that used/or thereabouts –
- Top weights in handicaps
- Jockey Claimers
- Left/right handed tracks
- Horse fitness i.e had run in the last 31 days
Let's assume that we'd come up with 400 selections over the last 4 years and this would average 100 selections per year.
Simply, looking at the top weight in handicaps would have given us 1,000's of selections over the 4 year period. Narrowing that down to top weights with “claimers” on board would have certainly narrowed that down to 100's of selections.
Now, this is where we need to get really analytical.
Let's assume that we've found the data for all of the top weights running in the year 2018. It would amount to thousands of bets.
In fact, I can tell you that in 2018, there were 7,483 top weights running in handicaps. Just for interest, they won 15% of their races!
Now, we move onto rule number 2. By adding claimers into the system, we get 2,583 qualifiers for a strike rate of 12.31%
Moving on, we add the left/right handed track rule. In this case, we're going to focus on left-handed tracks only. This would have given us 1,413 qualifiers for a strike rate of 13.45%
Now, finally, we move onto the final rule of the system, the horse's fitness. Narrowing the data down to horses that have run in the last 31 days, we have a strike rate of 14.37% from 1,246 runners.
Overall, this system has actually produced a loss of -£147.61p to BSP (Betfair Starting Price)
So, why am I telling you all about a losing system?
Because I used to use this system back in 2010. It worked on paper having built it using a data set downloaded from a popular data website. There was a little bit of market monitoring to do, but I was confident about using it because the data had shown a profit for the last couple of years.
However, it failed! I didn't make a profit and lost 50 points in the first 3 months!
So, how did I change it around and start to make it profitable?
You'll have to tune in next week 😉