1X2 Network revolutionising volatility

    “We wanted to identify how we can continuously improve the mathematics behind our games” noted Kevin Reid, CCO of 1X2 Network as he explains the inspiration for the company’s new ‘revolutionary’ standard, The Probability of Getting Your Money Back.

    The new PMB standard is set to identify a 3D footprint of a game and combined with mathematical equations, determines the odds of the player achieving specific returns after a set spin amount.

    With this new information 1X2 Network states that operators can target specific player types instead of the current ‘scattergun’ approach to the industry’s ‘non standardised’ term of volatility.

    Speaking to SlotBeats, Reid explains how the company came up with the new standard, the accuracy of the maths, why there’s been a lack of evolution when it comes to volatility and the future plans for PMB.

    SlotBeats: Why did you decide to come up with your ‘revolutionary’ new standard The Probability of Getting Your Money Back or PMB for short?

    Kevin Reid: There are two main reasons why we identified this as an important metric. 

    First, we wanted to identify how we can continuously improve the mathematics behind our games. Our 1X2gaming and Iron Dog Studio teams develop games for different types of players, and we wanted to better understand why certain games performed better with certain operators, markets and player types. 

    There is the “visual”, which is in truth pretty obvious as to what does and doesn’t appeal for the most part, but it’s the unseen, ie the maths, that we wanted to better understand, and the impact that has on the gameplay and how that in turn impacts the type of player the game appeals to and is successful with. 

    Secondly, with two different studios we wanted operators to be aware of where we are targeting our games, and who to. This statistic provides insight into who we are targeting and why. 

    Before PMB, developers would provide information around the RTP and volatility, but volatility as a metric for matching games to operators and players is simply too generic. 

    PMB takes the volatility metric and breaks it down into different areas to provide a 3D blueprint of the game and when and how it pays out. 

    Armed with this information, operators can more accurately market games to players knowing that from a math and payout perspective, it meets their expectations. 

    SB: With each individual player being different, how accurate would you say this new standard is?

    KR: The standard identifies the win potential of a game a lot more accurately and clearly. 

    This is a lot better at positioning but is not going to be the only factor to use to identify the game to match to a player. What it will be, however, is a lot more definitive than the current standards and metrics being used to match players to games. 

    Math arguably is more than 50 per cent of why a game appeals to a player (design, sound, etc the other main factors) and PMB allows operators to identify if a game will appeal from a core math perspective. 

    As a developer, it also allows us to understand potential reasons as to why a game is or isn’t successful as we can use the standard to potentially rule out math being the reason why players like or dislike a specific slot. 

    Again, this is not one hundred per cent accurate, but it is far more accurate than the current standard metrics being used to understand game performance. 

    SB: Due to the way volatility is currently understood and gauged, operators have been working on a scale of low to high and have been pushing games to players based on this. 

    KR: So, for casual players seeking smaller, stable returns, operators recommend games at the lower end of the scale. For those seeking big win potential, they recommend games at the higher end.

    But this doesn’t take in other factors such as their bankroll, the length of time they wish to play and the size of their stakes vs that bankroll. 

    Under the current standard, operators are taking a scattergun approach as they are recommending games to players simply based on where they sit on the volatility scale. 

    PMB allows operators to apply volatility and the impact it has on several factors (bank roll, bet size, session time, win expectation, etc) to better match games to player preferences.

    A player that is going to play 100 spins and wants to only double their money we believe will be much more suited to a game that has a 40 per cent chance of that happening in 100 spins than a game that has a 30 per cent chance. 

    SB: Why has volatility been so vaguely explained over the years?

    KR: I think that developers and operators simply haven’t had to. But as players become more educated and discerning, and where attention spans are dwindling through social influences, but also through the sheer number of choices within a game, there is a need to identify more information about games. 

    Both casino managers and in turn many players are more interested in how the games work and also because they expect operators to push them towards slots that meet their preferences. 

    In the past, game developers have also been cautious about sharing too much information about the math behind their games in order to not share secrets with their rivals, but in doing so are holding back information that can help operators make their games succeed further. 

    SB: Gray Wagner said PMB would “reverse engineer” some of the finer maths that most designers would prefer to keep secret, why would they keep it a secret?

    KR: Because the math is the soul of the game and once a developer has cracked the code, they can have a hugely successful game that others wish to replicate. 

    Our PMB standard shines more light on the finer math of the game, but it does not give everything away which again is why we are happy to apply it to our own slots.  

    If a rival wanted to replicate the underlying maths of a game, they cannot get this result from the PMB graph itself. It would require obtaining millions of simulations of the competitors game. Which is possible in theory, however practically quite a challenge.

    SB: What are your future plans for PMB?

    KR: We will use PMB to learn more about our games and how they perform and then use this information and insight to refine and improve the slots we develop and launch. 

    We will also use it to help operators better understand why games appeal to certain types of players and match different players to our different games. 

    This will allow operators that stock our games to be more efficient and effective in the games they take from us as there will be an increased level of trust regarding the games we recommend.

    For the operator, it will also help them to market games more responsibly and ethically, based on player bank rolls, the size of bets they place and the returns they seek.