Multiple Features: General Overview
Multiple Features
Games with multiple features usually make absolutely no difference to the average chance to trigger a feature, unless one or more of the features is designed to hit often and return very little.
Generally speaking any game that has multiple features of a standard nature (designed to hit infrequently and have the potential to pay well) will simply make all the features proportionately less likely to hit in order to avoid having the features consume too much of the overall RTP.
A game that has 2 instances, for instance, may have both hitting on average 1 in every 250 spins, yielding a net average expected feature hit rate of 1 in 125.
Feature RTP and Feature Probability Schedules
Free game, pick, re-spin and other features in a game generally consume between 15% and 35% of total RTP (on say a 95% RTP game a typical slot would see between 20% and 30% of that expected RTP being consumed by the features).
Feature play, in a random system, is again all about expected return rather than being set to only return a specific level to the player.
Probability schedules are very often used in random systems to achieve a level of volatility while still maintaining randomness. For instance, a pick feature might be used to award a random credit prize, or a random number of free games.
Not all results that are possible from this pick feature might have the same chance of occurring, so the table might look something like this:
Award: Probability:
5 free games 0.18
10 free games 0.30
15 free games 0.30
20 free games 0.20
100 free games 0.02
Net average number of free games would be: (5*0.18)+(10*0.3)+(15*0.3)+(20*0.20)+(100*0.02), thus 14.40 free games.
The reason is simple, if you had an equal chance on all of these events (so 20% for each), the average number of free games would be 30, which would likely mean that you would have to decrease the free game prize multiplier or make the feature very rare.
Expected RTP from a free game feature is simply the expected return from the feature * the chance to trigger the feature. So if a scatter-based feature will, on average (including retrigger calculations) award an average of 30 times bet and the chance to trigger is 1 in 130, the RTP being “consumed” by this feature would be 23.0769%.
Using a probability schedule to determine how many free games are won in pick features can also work in a slightly different way. In cases where a player has to choose between multiple objects to win prizes it is possible to allocate prizes according to the probability schedule at the commencement of the feature. So if there are 5 locations, for example, the software could test the table at the outset and assign the result to the individual pick locations. In many cases this will result in duplicates, in fact all 5 locations could yield the same result.
Let’s say it tests the table and assigns 15 games to position A, 10 game to position B, 10 games to position C, 20 games to position D and 5 games to position E. The player’s selection does then determine what they will receive, since the locations have pre-assigned outcomes. If the player chooses position D over position E they will end up with the better result. This is unlike pick features that access the probability schedule at the time of the pick, as in those instances it is irrelevant which position is selected.
The second option also allows you to accurately show (after the event ) what the player could have won if they had picked a particular location (usually by showing de-selected “greyed out” prizes for the non-selected spots).
A third option involves identifying to the player the range of different prizes at the outset and then placing those prizes randomly across the pick locations. e.g.: In the RTG game “Aladdin’s Wishes” one of the 5 lamps in the feature will reveal 25 free games. The lamp is determined randomly before any picks are made, and then it comes down to which ones the player selects.
Similarly you may have a game which used the above free game values, for instance, and would always have one of each type. So out of 5 picks, they will always have 5, 10, 15, 20 and 100, randomly allocated. As with the “determine at the time” table, however, you end up with the 30 free game average.
