9 blocks mined in 22 minutes 👀
The target is 1 block, on average, every 10 minutes.
The last 9 blocks were mined over 4x faster than usual.
165 sats \ 1 reply \ @Arceris 12h
Look at a poisson distribution... A set of fast blocks will happen occasionally, as will a set of very slow blocks.
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yep! 👀 #745741
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HAHAHAH yea crazy but happens
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840 000 blocks - 20 april 2024 867 970 blocks - 29 october 2024
867 970 - 840 000 = 27 970 blocks - 192 days
192 days = 276 480 minutes
276 480 / 27 970 = 9.88 minutes
tik tak ... next block!
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54 sats \ 0 replies \ @Arceris 11h
from scipy.stats import poisson # On average, 1 block is found on average every # "block period" which is 10 minutes avg_blocks_per_period = 1 # but we actually found (for example) 5 blocks obs_blocks = 5 prob = poisson.pmf(k=obs_blocks, mu=avg_blocks_per_period) print(f"Probability of {obs_blocks} blocks in {avg_blocks_per_period} ten minute period is approximately {prob*100:.2f}%")
This should result in: Probability of 5 blocks in 1 ten minute period is approximately 0.31%
At that rate, a 5-block run in a single 10 minute period should happen roughly a few times a difficulty period, even when the overall average is still just at 10 minutes.
I think this is correct anyway, it's been awhile since I had to do these kinds of stats.
The above doesn't work well if you want more fine grained stats, but you can, for example, see what the chances of 145 blocks a day are if you set 144 expected per day. There are other ways to get down to inter-block periods, but you have to adjust everything.
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