Wednesday, November 18, 2015

Slides from my talk "Evil by Design" at Build Stuff

Third time attending Build Stuff, first time doing a talk. I'm happy that it's out of the way and can now just enjoy the conference, but I'm even more excited that it was well-received! The talk should have been recorded, but you can already find the abstract and slides below.
Last year I ventured into the domain of (online) gambling. Given that the industry has been around since forever, I expected most problems to be of the technical kind. As it turned out, the struggle with technology was only part of a bigger problem; to move forward we needed to fully grasp the industry and its consumers. 
Events started out as a way to dismantle a legacy system, but quickly proved to be an effective tool to gain a deeper understanding of our domain. Visualising event streams, we discovered patterns that helped us identify what drives different types of users. 
Having a better understanding of what customers are looking for, we dove into existing literature to learn which techniques and models casinos use to cater for each type of user. We learned how to program chance while staying true to the Random Number God. Even when variance is brutal, casinos have enough data and tools to steer clear from the pain barrier. 
All of this entails interesting problems and software, but isn't my code damaging society? Or is gambling just another human trait?

Monday, November 16, 2015

Defining big wins

Casinos invest a lot of energy selling the dream. One way to do this is by showing off people winning big in your casino. Everyone has seen those corny pictures of people holding human-sized cheques right? It's a solid tactic, since empirical evidence shows that after a store has sold a large-prize winning lottery ticket, the ticket sales increase from 12 to 38% over the following weeks.

If we look at slot machine play, what exactly defines a big win? The first stab we took at this was quite sloppy. We took an arbitrary number and said wins bigger than 500 euro are impressive. This was quick and easy to implement, but when we observed the results we noticed that when you have players playing at high stakes, a win of 500 euro really isn't that impressive, and we would see the exceptional high roller often dominate the results.

What defines a big win, is not the amount, but how many times the win multiplies your stake. Betting 1 euro to win 200 euro sounds like quite the return right? Coming to this conclusion, we had to define a multiplier threshold that indicates a big win.

Having each win correlate to a bet, we could project the multipliers, and look at the distribution.

In this example I'm using matlab, but we could do the same using Excel or code.

So first we load the multipliers data set.

For then to look at its histogram, visualizing how the multipliers are distributed.




Here we notice that there is a skewness towards large values; a few points are much larger than the bulk of data. Logarithmic scales can help us here.


This shows us a pretty fitting bell curve, meaning the multipliers are somewhat log normally distributed. We could now use the log standard deviation to pick the outliers.

But we can also tabulate the data set and hand pick the cut-off of normal wins.

We could now write a rule in our projection of big wins which states that a log(multiplier) larger than 3 is considered to be a big win.

Matlab, Excel and the like are great domain specific tools for data exploration which can help you reach a better feel and understanding.