I tried to get some players to collect data for trashmobs, but nothing appeared so far and I don't play any more.
The quoted calculation assumes that trashmob-drops and elite drops have the same quality. As legendary items are the interesting drops, this might be true (but I did not see convincing data yet).
- 12/30/2012 5:24:54 PM Posted in: Theorycrafting and Analysis
12/26/2012 12:28:11 PM
Posted in: Theorycrafting and Analysis
I think you are referring to true randomness as source for a PRNG - well, that is not relevant if the bug is somewhere in the PRNG.Quote from m4st0d0n
I don't consider using hardware RNG being an overkill for a game like Diablo 3. Millions of items are generated every minute, and the economy can be easily flooded, so chances need to be infinitesimal - but still measurable. Diablo's economy is built upon probability. If math doesn't do what it's supposed to do because of a badly implemented (P)RNG, the game won't work as developers planned either.
I don't think the economy is sensitive to issues of the RNG, unless it completely changes drop rates for items. If there is a bugged double drop every 100 legendary drops, we might get 1% more legendary items. So what.
That was my point. A source of true randomness for every drop (perfect in terms of randomness) would be overkill.Quote from JKlimek
Those just generate a starting point for the seed program. Even though the starting seed may be "more random" it's still not technically random from a statistical perspective.
12/23/2012 3:50:53 PM
@Bagstone: Doubled drops/crafts appear to be too common to be explained with pure randomness. I know one player who got two pairs of identical craft items from the blacksmith, and saw many more reports of such pairs from others. 6 random affixes, exactly identical stats - while it might be possible to see that at some players in the whole Battle.Net, you would not expect that any player sees that twice.Posted in: Theorycrafting and Analysis
A nice example of bad random numbers are the superchest patterns in diablo 2. They are well-studied, and it is confirmed that they use a very small set of different seeds (2^16) to generate their drops.
Don't get me wrong - most posts "RNG is bugged!!!!" just show that the RNG (usually) works as intended - if there would be no such posts, we would have to worry. But the RNG algorithms used for D3 are not perfect, and you can see this.
There is hardware to generate true random numbers from atmospheric noise or even from quantum mechanics, but that would be overkill for a computer game.There is no real true RNG, because computers are always deterministic.
12/13/2012 1:04:30 PM
Anything I can import into excel - csv (or similar), .xls, .xlsx are no problem, other formats might be possible.Posted in: Theorycrafting and Analysis
100 legendary items in 6 days? Wow.
12/3/2012 9:30:19 AM
If you want to contribute to a data collection: Wonderful!Posted in: Theorycrafting and Analysis
A simple way to do this, with a focus on legendary items:
- before a run, write down your kill counters (regular mobs and elite mobs). Write down your MF-value and the used MP-level. The chosen act can be interesting as control data, too.
- after a run after you left the ga,e, write down your kill counters again. It would be better to count the elite groups ingame, but the counter works, too.
- during the run, note the number of legendary items from regular mobs and the number of legendary items from elite mobs.
- for key wardens, act bosses and other special monsters (siegebreaker, ...), save the current MF-value there, NV-stacks, and the number of legendary items for each monster.
With ~30 legendary items in the data collection, it would be possible to estimate the legendary drop rate with an uncertainty of ~20%. With 100-200, the uncertainty goes down to ~10% and it is possible to compare drop rates for elite mobs and trashmobs.
Another interesting thing would be a calibration of the drop chances of regular mobs:
Keep track of the total kill counter before/after cleaning 1-2 areas, those areas itself, and the total number of items (everything a character/follower can equip, not potions and so on). If you want to do it even better, split that total number by color, and keep the same MF-value during the run.
It would be interesting to see which slot is used by plans (blacksmith+jeweler): If a plan drops, write down the complete drop (including crap items, potions, gems, whatever).
11/25/2012 3:15:15 PM
I would be really surprised if there is anything related to specific legendary items. I think your drops are just a random fluctuation.Posted in: Theorycrafting and Analysis
10/20/2012 5:13:45 PM
What about a 1.0.5-list of ilvl/slot distributions? Could reveal the changes to 1.0.4.Posted in: Theorycrafting and Analysis
I think I can provide plain texts of items like this:
Name: CINCH JUSTICE
+43 Physical Resistance
20% Better Chance of Finding Magical Items
Edit: We should check the color distribution for the bonus drop: Similar to slot 1/4? Similar to slot 2/3? Similar to NV slot?
10/13/2012 8:15:38 AM
Just 1 rare from a pack can happen - with 70% chance of rare drops in slot 1 and 2, you have a ~10%-chance to get just 1 rare item.Posted in: Theorycrafting and Analysis
It should not happen at Siegebreaker, Cydaea and Azmodan.
When there are many items on the floor, it can happen that some items are not shown. Maybe you missed one rare item this way?
10/10/2012 12:45:27 PM
I think it could be useful to add the expected numbers of keys per ring, for many rings. That is simply 3*10/MP machines per ring, and 3*10/MP runs per machine.Posted in: Theorycrafting and Analysis
Divide the first number by 4 for a full party.
After some runs at MP 1, the 10%/MP-level assumption looks more reasonable again. However, the size of the dataset is poor, just 33 key runs, 7 plan runs plus 19 organ runs.
10/8/2012 11:25:46 AM
I can confirm that different allowed affixes have a different frequency, but the dataset is too small to extract specific numbers. When there are multiple affixes with the same stat, high-level affixes seem to be preferred in my dataset.Posted in: Theorycrafting and Analysis
I crafted 57 apprentice leather cuffs (ilvl 10). They can get 6 different prefix stats with 10 affixes and 5 different suffix stats with 1 affix each.
Prefix distribution with "Name (affixlevel, min-max value): number":
Gold 1 (6, 5-10): 12
MF 1 (1, 2-5): 4
MF 2 (6, 6-10): 4
GoldPickupRadius 1 (1, 2-2): 4
Experience 1 (1, 1-2): 3
Experience 2 (5, 3-4): 2
Experience 3 (9, 5-6): 14
HealthGlobeBonus 1 (4, 2-29): 1
HealthGlobeBonus 2 (10, 30-48): 12
Regen 1 (1, 1-2): 1
Str 1 Secondary (5, 1-5): 7
Str 1 Secondary (5, 1-5): 15
Str 1 Secondary (5, 1-5): 14
Str 1 Secondary (5, 1-5): 10
Thorns 1 (5, 1-1): 11
The lower number of str-crafts is reasonable (but not significant), as there is just one char with str as main stat.
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