I literally just tried this after the pity of the alyce.
You should not have went for her
1 Like
Well Iâm done paying in this game at this point. Hitting pity once should be frustrating and infuriating, but four times!? I find it baffling how unfortunate it is to hit pity four in a row. Iâm sure in the history of this game nobody has been screwed this bad. Not a good look for the game coming from a loyal customer.
4 Likes
Ok tht just sucks 
I wanna see that happening to everyone during anniversary 
1 Like
Im going to miss the two new anniversary monsters because of this
3 Likes
@Killerdog I came up with a small experiment related to this, but I donât know if itâs good
import random
import math
tb = {} #table
X = 10000#amount of attempts
Y = 0
for i in range(0,30):
tb[i] = 0
for i in range(0, X):
for j in range(1, 301): #the hurts is 300 eggs
r = random.randint(1,400)
if r >= 1 and r <= 3 or j == 300: #0.75% = 3/400 or hurt
m = math.ceil(j/10)
tb[m-1] = tb[m-1] + 1
break
#calculated at how many eggs 10 was obtained, or hurt
for i in range(0,6):
v = 0
n = i*5
for j in range(0,5):
v = v + tb[n+j]
print("egg packages numbers "+str(n+1)+"-"+str(n+5)+" probability of output "+str(math.ceil(v/X*1000)/10)+"%")
for i in tb:
Y = Y+(1+i)*tb[i]
print("attempts "+str(X)+"\naverage "+str(Y/X)+"\nhurt "+str(tb[29]/X*100)+"%")
conclusion
2 Likes
Just edited it for you to be in code format. You can do this by putting three ` symbols above and below it.
Looks very good to me. Two things though:
- The chance of a featured mythic is 0.75%, not 1%.
- I think itâs unnecessary to do the math.ceil on the final result. Itâs more useful to have a more precise final result. You can round to, say, 5 decimal places.
I appreciate how you properly implemented how the pity works and doing the math.ceil correctly counts how many packs were bought rather than purely the number of eggs until the mythic hatch⌠this is the aspect often left out of binomial calculations for this, itâs a big advantage of using code to calculate it.
One other improvement you could make, to help with scaling, is to turn the table (tb) into a dictionary from 1 to 30 with each value starting at 0 then each time you get a number to append you instead add +1 to the value in the dictionary with the corresponding key. Therefore youâre not going to create an X-length list that needs to have its assigned memory increase at intervals and iterated through at the end⌠it will be a dictionary set at length 30.
2 Likes
It was a small experiment, but it seems incredible that the 0.75% average is 13 ~ 14 packages, the table was because I wanted to see the results in it, and it is true, it is difficult to see two 30 in a row
approximately 11% will be hurt and 23% will be ahead of 20 packages
That was last year, and it turned out exactly that way. Out of the 10 myths I targeted and awakened, I hit pity on 6 of them. So it really is not that uncommon if you are spending and opening a lot of packs.
That the average is 13 packages means that if you make 1000 attempts in a baner until the mythical obtain, or 1000 people try, the average will be 13 packages, some will have bad luck, others very good luck, do not notice when there are few attempts, but when you look at a great whole you will see that there were good and bad
@Killerdog You would have to take a look, still the shame is close to 12%, the players experience a lot, or the game is playing with the players, or I do not know what it can be
Nice bit of code you edited it to and those results look good. 12.41 average number of packs means itâs basically bang on 2000 gems to awaken a mythic when you include pity.
If you wanted to find out about hitting pity consecutively Iâd put another dictionary for two/three/four in a row and then track them with some kind of counter that gets added to each time thereâs a pity hit but reset whenever there isnât, logging in the dictionary when itâs reset and is 2+.
In terms of what youâre saying about 12.4% being too common for hitting pity, I think youâre actually looking at it backwards. The higher the number, the more the pity is reducing the average gems we have to spend. What the pity does is stop us from experiencing the bottom 12% of luck, where we could sometimes go 30+ packs with no featured mythic.
1 Like
The Google translator I think my idea is said backwards, what I say is that 12% is low, but the users are experiencing the pity counter a lot
I already did it, but I did not update the script. It seems to me that the generated data differ greatly from the real player data, with a high value for the attempt variable X = 10000, the pity counters obtained consecutively are between 1% and 1.5%, much lower than what has been observed. Additionally, with the same variable modified to a low value X = 100, the pity is rarely obtained, and even less often two pities in a row
1% to 1.5% sounds correct, doesnât it?
I think when people say that âhit pity twice in a rowâ they are sometimes saying they hit pity once for two mythics being awakened in a row. I.e. once in four shards and then once again in four shards.
Generally what Iâve found is that if what people are saying doesnât align with the data then the people are not being completely honest.
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my avrage is hitting pity ones a mythic, usualy the third shard lol i think thats fine cutting the cost of the third shard by god knows how much
2 Likes
The counter I made increases from the second pity consecutively; the first one wasnât counted, and if after a pity there wasnât another one, there would have to be two more pities in a row for the counter to increase, but if thatâs the case then it wouldnât work because players donât provide the data as they are.
what are the odds for 4 in a row? This further confirms the scam. Btw another pity shortly after maybe three shards from the fourth pity 1200x 5 =6,000 gems wasted on just a pity shard they gotta do something about this, x20 for pity is better value for the long run if it hits it. Since it is so common
6 Likes
So sorry for you. Did you get any other mythics at least??