Cricket markets

‘Where have you been?’ Well sorry things a little hectic at home with the new baby likely to make an appearance in a month!

The cricket season is hotting up, the big bash starts, BPL and as I speak England have started well out in the hot 3rd test.

The draw option gives us an extra market to consider. Some traders only trade this market, but I think that’s wrong as the other 2 are always connected; the 3 have to be evaluated together and can be profited from.

I advised this to a client who I programmed some automation from earlier in the year. This was for small field horse racing markets, so we adapted that for cricket.

We targeted a scenario where two markets behave in unison against the third, causing it to move. By working out the average number of runs scored per session and time remaining we found scenarios where this might occur.

the big bash has seen some big first innings scores, around 20% higher than the average 1st innings mean. ill be cross referencing data from prwvious years, remember groundstaff and instructions given to them change match to match and season by season – not all grounds remain the same size too!

Batting aggression is often lazily thrown at this argument but in reality the truth is often more subtle than that when you add the match ups inti the equation. as a starting point however, ground trends cannot be ignored.

have a fantastic new year and thanks for your support with the blog.


Mid year analysis

One of things I like to do as the summer finishes is take a detailed look at what I’ve done over the year. 

I started off with a 12 new bots this year aimed at horse racing markets. They are purposely pretty generic, by that I mean apply to more scenarios that I would typically aim for. As a result they have a higher turnover of my bank with a smaller than average ROI. 

I don’t have a problem with that, the fact I can just leave them to do their own thing frees up my time to develop other stuff and for stuff outside trading.

If you are close or have been hit by the betfair premium charge then this does wonders the alleviate that. Look at how betfair calculate this and you will see why.

Of the 12, 5 have outperformed my expectations and I am looking to push these on. What’s the best method to do that? These adjusted stake internally, so for example if bot A yielded 5%, and bot B -2% then my daily stake for A would be higher until that yield changed. 

Now I am confident of their performance, I will take the monthly p/l for all 5 and apply the same staking to all 5. I think it’s a good thing to do where you have consistent performers, means less administration and will roll over any downturns. 

Of course that means if I’ve overlooked something or a trend changes dramatically then I will be overstaking as the same staking is used for everything.

I’m not sure if this is the way forward to be honest. It was born out of one bit having a superb month and the staking increasing wildly as I’d allocated a small bank to each bot. 

 I reacted by reducing the % bank stake of everything but the return it was giving me wasn’t worth the administration i was doing in logging the results. 
I know I harp on so much about staking but it’s a key fundamental. My last blog mentioned busting the bank, well correct staking could have prevented the spiralling effect leading to that big bank busting, losing bet!!

I think this will work and I’ve made the correct decision, we’ll see. Have a great autumn and I’ll be back with another double header blog soon. 

Reset the bank

Not one for sharing news usually but myself and my wife have a new arrival on the way in January. Along with a new motor, a few other unexpected bills have arisen meaning I’ve taken a significant draw-down on my account. I hate doing this, it goes against all economies of scale but is unavoidable.

Operationally wise, I quite like I though and the staking takes me back to the early days when my outlook was perhaps less cynical and fresh. It’s the 3rd time I’ve done it, the first time forced with no option during my very early days went the bank blew! From the number of people inactive traders I see on Twitter selling information, databases, advice or tips i bet it is a common occurrence!

I don’t actually mind trading with a smaller bank, for a number of reasons. I log every trade I do which is linked back to a spreadsheet which gives me my staking. That is at new level and even though I carry the same risk of losing my bank compared to the higher stakes I previously used, the psychologically the pressure seems less. 

Be sure to adjust your staking as every trade you place will be reminder of where you’re at, and where you’ve fallen from.

It also gives a good opportunity to reset, re-evaluate approaches, right or wrong and to give a new target to focus towards. If your monthly  P/L over a yearly forecast has lots of variance it’s a sign you are doing something wrong, maybe discipline or staking. 

If you are starting out, blowing the bank is something that is likely to happen. It natural to experiment and the greedy, dangly carrot will almost certainly contribute. There’s nothing wrong with that, however I would almost guarantee anyone starting out is trading with a bank 50% to large. What that means is you are paying double the price to learn your trade. Be humble and accept that there is lots to learn!

Use a big bank loss as a positive to address the mindset issues you many have faced, reflect on what went wrong and nurse your wounds to make sure you don’t fall next time when climbing the mountain. 

Climb steady!


I have been running a bot on tennis for a while now, probably started 4/5 years ago and has developed since. I’ve assessed its performance in ROI and it’s done pretty well, like all automation I develop i try and look at it from a new angle.

Here’s how it performed this week, a WTA match in Japan, i think the semi-final:


Pretty good, 25 or so successful trades and i achieved what i wanted to achieve with it during the match. Here’s how it began:


and ended:


Here’s the second match, B which achieved the same profit:


It started like this:


And ended here:


We have 2 major variables I look at, number of triggers (bet placed) met and time the bot ran for. Match B had less triggers which might tell me I was exposed for a greater amount during the match. It makes sense because the bot ran for 1hr 20 mins less time than the first match.

Exposure and time are the 2 most important pieces of data I look at. The first match took almost twice as long to hit the same profit amount than match B.

It got me thinking about other markets. Take horse racing, you create a back to lay rule, how often do you aim for a target price? and how has this come about over the years? Obviously we have a fixed amount in our minds which we want to achieve.

Back to lay is so popular these days, I see more and more punters looking to take their cut at 80% of the target price, dog eat dog it might move to 85% and so on until the price become back-able.

Relating back to the tennis, i often grade a successful trade based on the time spent in the market. It has to be your number 1 aim to be in and out of the market as soon as possible and to achieve that automation can help.

Look back to some previous blog and I like to talk about multiple trades reducing liability for further trades and it’s something that can be implemented perfectly what with the National Hunt season round the corner.

It is competitive however, as the races are run at a slower pace than the flat there is more time to decide what to do. Of course this means more thinking time for the on-course traders and those with a better knowledge of jumping/running style than you.

It is tough, but I will be keeping an eye on the early money left on the ladders to lay, chances are it won’t move and I can take advantage. I will be logging my trade times this season, based on furlong length along with liquidity in running and volume pre-race to see where I stand at the end.

To conclude, one simple piece of advice I will be following is to keep an eye on liquidity in running, the days of getting ahead of the market above a whole number on the ladders are gone, be flexible and if the price isn’t moving consider the time your money has been at risk for and decide if it’s worth it. Good luck, i might need a slice too!

Bet analysis part 2

So this is the follow up post to: 

A bit more background on this project. It’s a tipping service who the client pays for and the stakes he used justified further analysis. 

Lets get stuck in. I will be frank and put it out there that lots of tipsters with a slim profit margin put up unrealistic prices which a bettor who is limited by bookmakers, cannot profit from. 

Take another look at the graph and the spikes are where a bet is successful. At these points the difference in profit between his and the model was mixed. 

Not shown on he graph were whether the selections were each way or to win. The each way bets produced a difference in favour of the bettor. He was using the exchange which paid less places but offered a higher price. There were no selections which benefitted for he extra place in the data I was given. I suggest long term it might. 

His each way staking was also different to the model, for 1u each way he was staking 2u where as the model staked 1u in total. His staking was biased toward the each way selections which would is not true to the overall staking in the model.

We have a slump around bet 42, this was a missed winning bet.

I highlighted a trend around bets 102-115 which was interesting and could refer to what I mentioned about unrealistic pricing. This was a sequence of winning trades yet the difference decreased. 

So my recommendations were as follows:

1) correct the each way staking and continue to monitor whether the extra bookmaker place (where advised) benefits longer term.

2) be consistent in following selections 

With these addressed and with a bigger data set we could see if the difference is still negative. One strategy I use is to look at the difference % long term and retrieve that difference in asking for a higher price in running. 

In running price analysis is something I would apply to this data if there were over 3 months and then filter based on race type. 

I will leave it there but that is a snippet of what I do. If you are busy punter or tipster and like what you see do get in touch. It is quite time consuming so I don’t do a lot of it. 

Should this particular project continue I will update should it be of interest.

Appreciate this is the unsexy realm of punting, but it’s important – well done if you got this far!!

Bet analysis

I’ve been working a new project last few weeks which doesn’t involve betting. I’ve always been open to help other in the betting world so it made sense to offer some detailed analysis and consultancy. I wanted to provide something relevant to the person I was helping, rather than the general advice handed to novices going in one ear and out the other.

For one client, I took a months work of results (blue) and matched them against a model (green). Here it is – 181 horse racing bets for the calendar month of August.


You’ll see the individual under-performed against a losing model (for this month). The yellow line is particularly important as that shows the difference between the model and actual results. The fact the system under-performed this month is not relevant to me, the difference in yellow is.

I haven’t fully analysed the reasons for the difference, but thought I’d share the level I think you need to go to, to analyse where bettors are going right, and wrong. Its too easy just to keep on trading without giving enough time to review performance and fine tune methods to become more profitable.

For system bettors amongst you, its great to see how you compare to a system with positive expectancy, the aim would be to mirror it as closely as possible. For more flexible traders, I have encouraged regular notes that accompany trades with financial input coming from limits of risk per trade and sometimes a target profit per trade if the system is rigid enough and suits that punters risk profile.

I’ll put up analysis of the graph above next time, and suggest some pointers going forward to drag that difference from the negative into the positive.


Hole in won.

A shorter golf-specific blog this week, in preparation for the open which starts next week. 

There are 2 tournaments normally to trade each week, on the European and US tours, so plenty to get stuck into.

Markets can be particularly thin at times, with low amounts of money flowing in and out. The trading properly begins on the 4th day particularly when a player goes short below 3/1 which is the area I will concentrate on today.

This is a good support price, but what other indicators would we look at in order to construct some automation rules?

As mentioned, market volume preferably over time will provide a good base.  

Prices change at this point either if the player gets in trouble, or chasing after players catch up so I will often apply historical course and player data from my database. Courses are often setup harder on the final holes and although it is not as common as 3 years ago, it’s often hard for a player who has led going into the final day, to hold onto that lead. Jim Furyk comes to mind, go check his history in this area.

Weight of money is another variable I use, one which shows short term movement referencing weighting close to the live price. A second looking at a wider range helps with long term movement.

Finally, the price relationship between players often give create clues as to whether the leading player has potential to move in further or out, in essence whether the current price offers value.

I have several long term clients I have worked with this over the years, so I cannot reveal more but preparation and patience will give some great opportunities to brighten up your Sunday evening!

Wot no tech

I received some feedback this week on my blog, complaining about the lack of ‘tech’ in my ‘tech’ blog. It’s a fair comment, but in my eyes the markets lead the technology, not the other way around – so that’s what I tend to concentrate on.

In a former life I programmed touch screens for audio visual control systems and I see parallels with the sports trading bot world, in terms of the tools used to create these.

10 years ago I would be editing lines and lines of text code. It would be laborious, complex and training was limited which protected those programming in that field. Over time, it became more graphical, logical and accessible by the end user.

I played around with the new bet Angel update this week and it paints a great picture of how things have moved on. No longer any need to configure API access, create your interface or write the code.

Their signals introduction is fantastic and opens up so much flexibility. I set up a simple back to lay file in an hour that will operate with any SP and fire off the lay bets that I require. I copied the whole set, to fire again once first cycle is complete so in essence I am playing with free money earned.

The ironic this was with 30 rules present and set to increase, I was essentially looking at teams of code again!!

I won’t be able to sell my bet Angel code, so from a business sense it may not be great, but I don’t mind. It’s a fantastic development tool and will be a fresher way to come up with new ideas. It will certainly impact the IR markets as this style of trading becomes more popular.

I see traders love tech for tech’s sake but don’t think it should be the driving force in what you do. The tools are there to create complex rules with ease, to the point where the technology or platform used to create will become transparent over time.

the money man.

An aim for me with this blog was to increase my interaction with like-minded traders. I wouldn’t say that has been a resounding success, but I do get the odd interesting (and sometimes far-fetched) line of enquiry. Like this weeks:

Mr X: I am new to trading and want to make £10k.

Me: How much do you want to stake?

Mr X:£10.

I ignored this email for a while, but it began to eat away at me over the course of last week. Often the starting point for those wishing to write bot’s is from a sporting angle, with which they hope to find an edge. Approaching from a purely financial angle was something i hadn’t done in a while.

I opened my spreadsheet and it actually surprised me how simple this could be done. It actually took £15 instead of £10 stake. It’s a 2 trade automation.

Back selection A: £15 @10.0

Lay selection A: £1355 @1.1

Back selection A: £1355 @10.0

Green @ 1.1 for £10801

Ok so, it 4 trades if you do it manually and you can probably find my calculations out a couple of quid (i altered my commision rate on the sheet and it went a bit funny), but the principle is there.

We went on to discuss the likelihood of this happening, i explained you needed this to hit approximately once every 2 years to break even. My conclusion that although possible, it’d be tricky for a novice to retain the temperament and the will to be able to carefully pick scenarios where this might hit, 18 months into the program.

We’ll see where we go, my guess is the margins and bet frequency will be lowered to give a higher strike rate, returning a more realistic profit. And of course mr X will need to pick his chosen sport – we’ll see how it goes!

Pull the rod outta the water

I heard a brilliant analogy years ago about trading, akin to fishing in dangerous waters. I’m reminded of it whenever i see Deadliest Catch, the show about deep sea crab fishing; the rewards are great but stay at sea for too long and you increase the chance of getting caught in a storm.

As always i devote some time to analysing what i do, this is a T20 game from the other week. On the surface it looks like some scalping on the Hampshire market with the larger margin being taken on Kent, not a bad result. Of course these are average odds and stakes, in reality my staking would have been £50-£200 per trade

Screen Shot 2016-06-07 at 16.53.54

Thing is, when you get under the hood, it all starts to get a little murky. The automation functioned as it should, i felt the rules I applied matched my reading of the game. What i noticed is the time of my first and last trade.

Screen Shot 2016-06-07 at 16.55.13

I think the match began about half 7, in total i was in the market for 2 hours out of the 3 odd it lasted – my bank was exposed to varying levels for just over 66% of the match. It seems like a long time, in reality i know my rules don’t allow exposure above 2% of my bank so it’s possible that my p/l sat in profit for the majority of this time.

In reality, i really don’t know – i could have been at -£181 but it is data that needs evaluating – ideally a graphical export per trade.

I may have landed the fish today but in future I’d like to reduce this time and to monitor the timeline of my P/L during the course of the match.