There are a wider array of possible critical strike item choices for Caitlyn and Nasus than there are for Master Yi. This results in more variance in the plots for Cait and Nasus than that of Yi. Comically, in the entire forty-thousand game dataset there were two champions that didn't have a single critical strike. Zero critical strike damage done between these two over the entire dataset. I appreciate you taking the time to read this article.
This data was all taken from relatively serious high-level ranked solo-queue games. There are YouTube videos of some ginormous crits, but I think it is neat to see that someone made it over 3k in an at-least-semi-serious game. Writing this article definitely got me thinking about which champions to build critical strike change on, I hope you got something out of it too. Let me know what you think.
Then head back to the home page and mash F5, there will soon be more league and more math here at LeagueMath. If this is the case, we can reject our null hypothesis and can claim with confidence that crits are not generated independently for that particular attack sequence. The tables below are the results of our analysis. The index of the table represents the sequence of attacks we are observing. Note that Random will refer to any data from our simulated attacks while Data refers to our observed attacks.
Note: Rnd Counts and Data Counts do not count the sequence if the last attack of the sequence is the final attack in our dataset. PCTL of DataCrit describes the percentage of generated crit rates that fall below our data crit rate. The last two columns describe the 5th and 95th percentiles of the randomly generated attack crit rates, respectively. Keep in mind that a percentile above the 95th percentile or below the 5th percentile does not guarantee a crit or a non-crit if that sequence were to be observed in-game.
Rather, we have evidence that supports the claim that the crit strike algorithm has some dependence on that particular sequence of that crit rate when generating crits or non-crits. However, it may be useful for players to track the sequences of their attacks and, depending on their crit strike chance, use that information to judge the likelihood that they will crit or not crit on their next attack which can provide a calculated edge in engagements or assassinations. There are two other interesting takeaways from the tables.
Here, the crit algorithm is smoothing the crit rate, but in an unexpected way. Rather than boosting the [0, 0, 0] sequence up, the crit rate is being pulled down. Conversely, the [1, 1, 1] sequence is being boosted up. The other takeaway comes from the data counts column. This attribute, expressed as a percentage, determines how much bonus damage your character does when an attack hits critically. Crit Damage can be increased by equipping artifacts and weapons that provide a bonus to it.
Hear this out loudPauseTrue Damage, essentially, allows for champions to ignore all armor or other resistances and deal pure damage based on their attack damage. This should help to counter some of the Knight and Brawler buffs that are coming through on this patch. As this streamer also shows, it makes critical hits that much more powerful.
There is no particular protection per se against it. If there were more paths to choose from, crit might stop feeling so ubiquitous and annoying. Image courtesy of LoL Wiki. Video courtesy of Flip , Gosu , and Phylol. Top Games. Krystof Senfeld 31 Jul Related Topics: LoL.
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