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A bajillion people have said the dice are flawed - and Marky Mark comes along as the Lone Crusader to say they are fine lol!
Dude, ya obviously aren't up to speed with the probabilities... check out this website for a basic primer =
Like I said, we still have a level playing field as everyone has the same crappy dice (although it does mean you have to adjust the strategy of how you play) - however the monumental problem is, crappy rolls kill the popularity and profitability of the game...
Right now it seems about 5 million people have downloaded Risk - which is great... but it could/should/would be double or even triple that!
More importantly, only a small percentage of people go ahead and pay for Premium - that percentage would be much higher... if SMG fixed all the many minor and major issues!
Anyway, seeing as you're even more obsessive than me (way to go bro lol!) and have recorded/uploaded some games - I'll go through them and put the data into a public Google spreadsheet... so we can all analyse till the kangaroos come home!
See my previous posts. The collective dice outcomes are not randomly distributed. I logged just short of 1000 battles then removed combinations that had less than 13 observations. When entering into a battle, the probability of losing 1,2,3, etc armies was significantly lower than the actual outcomes. It was persistent and repeatable. Yet, the frequency of the numbers were more or less normally distributed.
There were two distinct patterns. The distribution of armies lost for an overwhelming attacking force was bi-modal. Either the attacker didnt lose enough armies or lost way too many. Even when accounting for the lower bound.
When attacker & defender were within 3 armies of each other, if the attacker rolled lower numbers, the defender tended to roll lower numbers and the when the attacker rolled high numbers the defender rolled low number. You can see how this is problematic when individual die rolls are normally distributed right?
The dice sequence is dependent on what SMG refers to as "transition matrix" (TM). The random number sequence if conducted in a "serial mode" requires many more random numbers (one for each state) than the TM approach. In Discrete Event Simulation, to go from State A to State B given a probability P, throw 1 random number in a uniform probability distribution between [0,1] and assign State A if the random number is < P, or State B if the random number is > P. Thats for a simple transition of one state to one other. Now if you want to go from State A1, A2, A3...Aa to State B1, B2, B3 ..Bb then you would need an axb size matrix, where the matrix elements correspond to the individual specific transitions. I would think SMG ran say 10 million dice simulations with all types of combinations to populate their overall BlitzMode TM. They have to simulate enough transition states to get whats called The Law of Large Numbers (normal distribution) mean and variance.. The issue is that their matrix element values may be juiced or skewed so when the one dice is thrown Blitz Mode, it might not seem to be in accordance with the probability distribution of the TM.
The Random Number Generator (Merseinne Twister) is a very robust algorithm. However the TM values are not subject to the same statistics as the generator.
If SMG gets the message their TM elements are hosed, then they will correct it.
There is a small probability that 5 armies will prevail against 15.