Who is Peter Mac

It’s fair to say that not many people have a working life like mine. Let me tell you a bit about myself...

My pen name is Peter Mac. I don’t use my full name as I’m still very much active in the industry. But everything else that I’m about to tell you is the full truth...

A life-long quest to find the ‘perfect price’...

Starting young in this game isn’t a ‘must have’ but it certainly helps. And ‘doing my time’ working as an odds compiler at the bookmakers has given me experience that few other people have. Since then, it has literally been a never ending journey to learn how to construct the most accurate price possible for any ante post market...

You not only pick up pricing methods used by the bookies that can be useful to also adopt, but you also get wind of pricing techniques that are no good at all and are there to be attacked…

I look for opportunities that most people don’t even think of or know about. For example, one such method would be how to price up ‘mini group’ markets accurately – like the Top Northwest Club in the Premier League… or Top Man in Big Brother. It’s a technique that leans heavily on the master price (eg. who will win the event outright, before taking into account the ‘group’ in question), and when you have that right, you can tap into the market with confidence.

Some bookies are up to speed with this type of pricing, but there are quite a few that are not – and of course their slowness in catching up to the right master price has a huge effect on the category pricing...

I’ll make money with that technique for us, of that I’m sure – the more obscure the market the better and there are plenty of those coming up in 2017!

The upshot of the bookie having a wrong priced favourite, for example, is an inefficient market – in other words, a market which is priced wide of the mark in real terms. The easiest way to explain this is pricing up a coin toss at odds of 4/6 Heads and 6/4 Tails instead of Evens for each selection… or pricing the roll of a die being a six @ 7/1 instead of 5/1 – these are both examples of an inefficient market, in other words markets that are ripe for attacking.

If you want an example of an efficient market, look no further than the world of the ATP Tour tennis matches or Premier League match betting, the Starting Prices of both of these markets are about as efficient as you could hope for with only soft factors (for example injuries, weather, rotation) giving you a chance of any significant edge.

In the pregame department, I spend my days looking to attack the ante post markets that are inefficient. They are inefficient for a couple of reasons. The first, is that whilst ‘one off’ results can damage a bettor’s bottom line, over the course of a season or series of events, ante post punters benefit from the ‘long game’ – in other words, a decent sample size where class counts.

The other main reason is simply the odds compilers’ failure to price up a long term event properly – this is often a guess or a simply copy of the first bookmaker up, and if that starter price is wrong, you will often see multiple books sitting in or around that pricing level without really understanding why they are actually sitting with that price.

You might think it sounds strange that a bookmaker would get their prices wrong. But it happens – especially in ante post and outright markets...

The bookies and odds compilers are busy people, and they are under a lot of pressure. They have no choice but to concentrate on the hundreds of weekly football matches and horses races taking place: that’s where the attention of the majority of their customers is, and that’s where the big money will be going, too. But what about the market for something like the US Open tennis, months down the line? The bookies are going to spend significantly less time and effort on their market and prices for that. And those are exactly the kind of opportunities we can thrive on.

My time at the bookmakers taught me a great deal. But my big breakthrough came from elsewhere...

My secret weapon – ‘Monte Carlo modelling’...

Monte Carlo modelling is the technique and it has allowed me to price up literally anything… from the Ashes Correct Score to the number of Seats the Liberal Democrats will win in the next Election... The list is literally endless.

This technique revolutionised my betting overnight – and I have spent literally hundreds of hours building bespoke tools that model both in play and pregame markets. And the great thing about using this type of technique is that it WILL uncover opportunities.

On the pregame front, Monte Carlo modelling is a powerful beast. Take for example Seat betting – in any given Election there will be key seats – as the results of these seats are known, you will be making huge moves on the prices for the remaining seats. You can model various scenarios in the pregame department that take into account a range of outcomes. And looking at these outcomes provides the opportunity to create prices and compare them with what’s on offer with the bookmakers.

All of the above (and more) enables you to genuinely cite whether or not a position is value – that term is bandied around quite a bit these days, but more often than not that assumption is just a guess.

Maths has always been a strength of mine – right from an early age – so it was only natural to integrate that interest into what has turned out to be a bookmaking career spanning just short of 30 years (that’s not including the experimental tax free lays struck whilst I was ‘learning my trade’ at college).

And although I love maths, working in the betting industry has taught me to communicate in Plain English sometimes, too! If mathematical jargon isn’t your thing, don’t worry – you can still benefit from my methods...

My sporting investments are made based on one or more of these key indicators:

  • Simulation modelling produces a different price
  • The maths of the market is wrong
  • Soft factors that produce a variance

Let’s first look at the ‘juicy topic’ of simulations and dependencies…

Simulation modelling produces a different price…

There are a selection of methods that can be used to conduct such calculations – I often use them all during the course of a month, with one method in particular taking pride of place on the mantelpiece...

Risk analyst and former trader Nasim Nicolas Taleb used the Monte Carlo method to revolutionize the way he traded the financial markets. It allowed him to produce artificial thinking and compare it with non-random constructs. His holy grail-like writing is revered the world over… and let me tell you, the adulation that he has received is not misplaced.

As Taleb himself explained, Monte Carlo is basically the replication of a perfect roulette wheel (upon discovering Monte Carlo modelling, Taleb spent hundreds of hours in his attic with his newfound toy – simulating the financial markets with laser sight precision) – and whilst I didn’t grind out the hours in an attic, the back garden of my Queensland home was a decent enough substitute for me.

It is indeed a revolutionary tool when you run your first simulation – Serena Williams was the subject of my first calculations and let me tell you now, the numbers I produced were frighteningly blunt… so simple, and perfectly fitting for our purpose. Serena is a tennis legend, but my findings tell me she is rarely betting value.

Here’s another example. I once built a Scottish Seats simulator that ran 200,000 Elections (or ‘random sample paths’ as some might prefer). That gave me a price that I was then able to compare with what was being offered by the bookmakers.

Many sessions ending in the early hours but that’s the nature of this tool. I’m here to do all that hard work for you. My Ahead of the Market service provides you with the fruits of my labour.

One event can strongly influence another...

The beauty of this first simulation exercise was that it introduced me to ‘dependencies’ (that’s my terminology by the way – purely because it gets down to the nifty gritty that us punters need at this stage of events)...

In other words, how the result of one event can strongly influence that of another...

And being introduced to that aspect of modelling so early in my ‘career’ ended up being a defining moment as it permanently changed the way I produced these simulations/paths ongoing.

In fact, since that day I haven’t once ran a simulation that didn’t take into account dependencies.

I don’t want to get too deep into the technicalities but here’s an example of how a ‘soft factor’ (something that is a variable outside of the dataset) gatecrashes a sporting moment and from that point, has the potential to destroy the path the data takes...

Say you are playing a notoriously big serving player at your tennis club in the yearly men’s singles event – he has served well all tournament and you have only won one point on his serve in his opening three service games...

You are 0-30 down.

How do you think the mindset is right now of the returners? Well if he’s in any way human he isn’t going to be brimming with confidence, and therefore I would have to be shorter that he wins the third point in the game than I was for him to win the opening point.

Just as I would have to factor in a similar dependency at 30-30.

That’s an obvious illustration, but allowing for dependencies has, since its introduction, dominated my calculations.

It doesn’t matter what the simulation type, within every sim there will be some kind of dependency – tennis, NFL divisions, football relegation markets… all contain valid dependencies that will affect the final outcome.

And it is the consideration of these dependencies that sharpen up your prices.

Here’s a throwaway one to mull over – Australia get beaten in the opening Test (at the Gabba) is that going to result in some pretty serious decay being applied to England’s price for the second Test?… Yep it is, so any sim that kicks off with an England win should be loaded from that point with some significant action on England’s price...

That’s a real life example of what will be winging its way over to you come the 2017/18 Ashes Series – a event which has produced some of my finest wins … and the above mentioned scenario is the reason why.

The maths of the market is wrong...

It’s not all about the Monte Carlo method though – sometimes the price is just mathematically wrong. And I’ll be outlining to Ahead of the Market members a few price checking techniques that serve as an excellent measure of just how wrong a price is, and how this illustration clearly indicates the pricing mistakes that the bookies make on a regular basis. It’s these mistakes that my members will be continually feeding off.

I’m not talking opinion here – this is just the analysis of price sets which quite often make no sense at all.

For example – a bookmaker is chalking up the right price about flipping Heads on a coin toss, yet is laying 10/3 about back-to-back Heads.

A brutally explicit example, but it’s one that perfectly sums up how the bookmakers go wrong… and I’ll be giving plenty of examples of more such ricks in the future… with each step of the process broken down in such a fashion that it proves without any doubt that we are not only taking genuine value about a selection, but also where the bookmaker has gone wrong. And as I say, the bookmakers do get it wrong sometimes – especially in the ante post and outright markets.