I'll try to give your initial question a shot. I would recommend an online tutorial into probabilities and statistics if this area interests you. I find the subject both fun and useful.

Let take a coin toss for example. There are two different outcomes, and if the coin is fair, the outcome each have equal chance of happening. Therefore, you have:

Heads:Tails = 1:1 or another way of saying it is you have a 50% chance of the coin landing on heads and 50% chance of it landing on tails. Each coin toss is independent, that is, the previous coin toss does not affect the subsequent ones.

Now, we can assign values to the heads vs tails. Say, if the coin lands on heads, you get $1, but if the coin lands on tails, you get $0.

Let's say, you have to pay $0.50 for each coin toss.

Since the odds of head and tails are equal (50% each), out of many,many,many coin tosses, you expect to have 1 heads to every 1 tails.

So your expected return is 50%*$1 + 50%*$0 = $0.50, for every coin toss. (This is what some call the expected value, or EV).

Since the cost of each coin toss is the same as the expected return (both are $0.50), after many, many tosses, you would expect your input to equal your output. Therefore, you would have a return of 100%, meaning you would never lose money, and the house would never gain any money.

However, on single independent events, you could gain 2x your bet, or lose your entire bet.

In this simplistic version, how might you get something like 96% return? The simplest way to see this is to increase the cost of a coin toss.

If we increase the cost of the coin toss to $0.52, and keep the payout the same, we would end up $0.50 returned for every coin toss, and we pay $0.52 for every coin toss. This results in 0.50/0.52 = 96.2%. So on average, your return would be 96.2% of your input. The more coin tosses you make, the closer to this number you get.

Of course, MA's system have more possible outcomes, but the concept is the same. Each outcome has some probability, and you can calculate an expected return value based on the sum of the probability multiplied by the expected return value for each possible outcome. The overall return % approaches the expected number as the number of loot events become very large.

Your other question, how does MA ensure that they do not pay out more than the loot pool is a bit more complex, but here's how I would explain it simply. This is my guess of how their system works and NOT OFFICIAL! So take all this with a grain of salt and don't accept at face value disclaimer disclaimer

:

1) Based on the probability of the largest multiplier, MA can estimate how many extremely large events can occur within a certain number of events. One 1000x multipler is very likely to occur in 1,000,000 events, but n=1,000,000 1000x multiplers is very unlikely to happen in 1,000,000 events, as a very extreme example.

2) MA just needs to make sure they have sufficient funding to cover these bigger payouts.

3) MA caps the largest multipliers. This prevents extremely large swings in the 'pool', or volatility, and ensures MA always has sufficient cash to cover.

I hope these help to answer your question.